Human Factors in Design, Engineering, and Computing

AHFE International

Accelerating Open Access Science in Human Factors Engineering and Human-Centered Computing

Human Factors in Design, Engineering, and Computing

book-cover

Editors: Tareq Ahram, Waldemar Karwowski

Topics: Artificial Intelligence & Computing, Human Systems Interaction

Publication Date: 2024

ISBN: 978-1-964867-35-9

DOI: 10.54941/ahfe1005561

Articles

Implementing an AI Fatigue Risk Management System for Aviation Maintenance SMS: A Technology Enhanced Critical Process Human Factors Safety Plan

Commercial aviation maintenance is a safety-critical process that requires adherence to maintenance procedures. Unfortunately, when this maintenance process fails due to human error, it can come as a costly event and potentially keep an aircraft out of revenue service. The researchers have advocated using some form of human factors risk management safety reporting system within a Safety Management System (SMS) framework for airline maintenance to mitigate human error. But the current shortages of aviation maintenance technicians (AMTs) create a fatigue inducive environment that calls for better fatigue mitigation. What is the point of having a good SMS and human factors safety reporting system if AMTs are often exposed to hazardous fatigue levels? Strategically, both a strong human factors risk management safety reporting system and a proactive fatigue risk management (FRM) system would have to work complementary with each other to keep the critical maintenance process safe within the SMS framework. With AMT fatigue in United States (US) identified as a problem, the researchers then analyzed the current Federal Aviation Administration (FAA) FRM system (AC 120-115). From the analysis, the researchers propose a solution in the form of an AI FRM system. To accomplish the proposed AI FRM system design, a research-supported AI integration system framework called CHAAIS was adopted. The proposed AI FRM system complementing a human factors risk management reporting system in SMS could greatly enhance airline safety.

Mark Miller, Bettina Mrusek, Jeff Herbic, Sam Holley, Leila Halawi

Conference Proceedings

Deep Learning Forecast of Perceptual Load Using fNIRS Data

In this paper, we present a novel approach to forecasting perceptual load in demanding piloting tasks, based on neurophysiological response data. We introduce a forecasting framework using a multinomial classification model paired with deep learning sequence-to-sequence models. The study compared the performance of seven different deep learning models, including GRU, Transformer, and linear models with a 10s outlook against a statical model benchmark. For analysis and validation purposes, the dataset was first split into training and testing sets, and the training set was further used to perform a 5-fold cross validation. The cross-validation results were used to evaluate generalization in terms of the regression loss used to train the deep learning models, while the testing set was used to evaluate the classification performance, including macro and weighted recall, precision and F1 scores. The prediction time for each model (computational demand) was also analysed for insight into model viability for real-time perceptual load forecasting.

Nicolas Grimaldi, David Kaber, Ryan McKendrick, Yunmei Liu

Conference Proceedings

Artificial intelligence in the function of improving port systems

Decision-making in port activities is characterized by speed, flexibility, rationality, efficiency and economy. However, the main role in their implementation is played by port employees who are not always able to be reliable, timely and objective. Likewise, their insufficient education, lack of professional knowledge and experience, and insufficient number of adequate port workforce can negatively affect the sustainable functioning of port systems. The introduction of new technologies and systems that can process a large amount of data and imitate human activities such as reasoning, learning, planning and creativity represents a fundamental challenge in achieving goals aimed at improving port operations. Therefore, the application of artificial intelligence seems inevitable because only it can provide a higher level of possibilities in the future development of the port. In this paper, a basic matrix of all the constituent elements that make up a complete port system with an applicable model of their computerization, digitization and automation is laid out. With such an approach, all port activities will be able to take place without direct human activity, and supervision over their implementation will be completely autonomous. In this way, the operations of the ports themselves will be more productive, more competitive, safer and more economical, and port users will get one open, simple and reviewed tool that will be able to meet all their needs for port services in one place in real time.

Alen Jugović, Tanja Poletan Jugović, Renato Oblak, Dražen Žgaljić

Conference Proceedings

Formalizing Trust in Artificial Intelligence for Built Environment Decision-Making

While artificial intelligence (AI) has transformed the planning, design, construction, and operation of physical infrastructure and spaces, it has also raised concerns about algorithmic bias, data privacy, and ethical use in built environment decision-making. Addressing these issues is crucial for designing, developing, and deploying trustworthy AI systems that promote human safety, infrastructure security, and resource allocation. This paper reviews trust issues in AI through the lens of several built environment decision scenarios, e.g., weather prediction, disaster mitigation and response, urban sensing, and bridge health monitoring. It then outlines a framework to formalize trust, aiding researchers, policymakers, and practitioners in designing AI systems that serve societal interests.

Amir Behzadan

Conference Proceedings

Artificial Intelligence and Design: Innovation, Practical Applications, and Future Creative Horizons

Artificial Intelligence (AI) is reshaping the design landscape, from product development to graphics, service and critical-speculative design. This paper explores how AI enhances efficiency and expands creative possibilities, offering insights into its applications, challenges, and opportunities. While AI excels in automating complex tasks, the designer’s role is evolving towards "sense making"—the ability to infuse meaning and context into AI-generated outputs. In product design, AI-driven technologies such as generative design and machine learning enable optimised and personalised solutions, positioning designers as mediators between algorithmic precision and human needs.In graphic design, AI democratizes access to advanced tools, raising ethical concerns about skill displacement. In service design, AI improves user experiences through personalisation, though issues of transparency and fairness must be addressed. In speculative design, AI has become a fundamental support for processes of futures imagining and envisioning. Additionally, the paper highlights the transformative role of AI in education, requiring students, researchers, and professionals to adapt to the evolving technological landscape.Finally, the paper discusses the ethical challenges of AI, such as bias and automation’s societal impact, presenting AI not as a replacement for designers, but as a tool that enhances creativity, fostering a collaborative future where human ingenuity and technology harmoniously coexist.

Salvatore Di Dio, Benedetto Inzerillo, Francesco Monterosso, Samuele Morvillo, Dario Russo

Conference Proceedings

Supporting Informal Sustainability Learning with AI-assisted Educational Technology

This paper presents Waste Genie (WG), a novel web-based educational platform designed to enhance learning about sustainable waste management. WG employs bite-sized interactive content and leverages artificial intelligence to support sustainability education. To assess WG's efficacy, we conducted a user study involving 21 college students. The study aimed to evaluate improvements in sustainability awareness, waste sorting skills, and overall user experience. Results showed a notable increase in participants' understanding of waste management practices and their ability to correctly classify waste items. This research demonstrates the potential of combining emerging technologies like large language models with interactive learning approaches to address environmental education challenges.

Qiming Sun, Sharon Hsiao

Conference Proceedings

An assessment of the maintenance of heritage buildings using AI and IoT: a South African perspective

The paper assesses the possibilities of maintaining South African heritage buildings using Artificial Intelligence and the Internet of Things. Over the years, the construction industry has evolved with AI, creating software to make maintenance of buildings easier for the end-user by collecting data from different systems within the building to be centralised for data storage and future analysis and maintenance planning. The study aims to assess the merits and benefits, and the pitfalls, if any, in the adoption of AI and IoT in the maintenance management of heritage buildings in South Africa. The standardisation of IoT for the maintenance of heritage buildings and the challenges that the industry faces for not adopting AI are likewise discussed in the paper. The paper is based on the assessment of peer-reviewed literature and policies on the current systems used to track the maintenance of heritage buildings in South Africa. The findings concluded the benefits of cost, quality, and time for the end-user and stakeholders while it noted challenges that mainly involved the security of data collected and the standardisation of IoT in the architectural, engineering, and construction industries.

Katlane Seema, Clinton Aigbavboa, Ogunbayo Babatunde

Conference Proceedings

What if we Could Entangle Drones? Towards the Management of a Swarm of Drones as a Non-Local Quantum Object

Since a few years, swarms of drones are used in both the civil and military domains. They might be composed of tens, hundreds if not thousands of drones (e.g. to achieve saturation effect). It thus becomes hard to deal with each of the individual drones that make it. Therefore, making a swarm a single object, that could then be controlled as a single entity, whatever its size and its surface, is the grail.Many projects have been working on this issue. Still, as far as we know, none has been convincingly successful. There are a number of reasons for that.From a conceptual point of view, the controls that make sense at the level of a swarm are not simply an upscale of the operations that make sense for the drones that compose it. Some controls are easy to upscale (take off, land) and to map back from the swarm to its individual components. Some are more difficult. For instance, what does it mean and does it even make sense to move a swarm to a given location? There is an underlying notion of synchronization that remains hidden if stating things so simply: when should the move begin, should the members go together, when is the move terminated, etc.? Whatever the answers to these questions, this requires stable communication and strong synchronization between the members of the swarm, which cannot be guaranteed in most theaters of operations, especially for large swarms. Additionally, there are operations that only make sense at the level of a swarm, not of an individual drone. For instance, it might be useful to split a swarm into two smaller sub swarms, and later reconnect them as a single object.From a technical point of view, two major configurations are to be considered. First, it the swarm is controlled by some central system on the ground (C2, Command and Control) it makes things partly tractable. The C2 has a global view of all the members of the swarm and the above issues can be dealt with, knowing the required information about each unitary system. Still this does not solve the problems of congestion, latences and disruptions. Second, if the swarm is composed of autonomous systems, i.e. when the swarm is composed of drones that decide on their own on their behavior, it becomes much more difficult. Still, this is the most interesting configuration in real world operation because autonomy makes it possible to address BLOS (Beyond Line of Sight) missions and avoids swarm to ground communication.The question to solve is what do we precisely expect when willing to make a swarm a single object? We claim that the perfect result would be to break the locality of each individual drone making the swarm a non-local object as if the drones were some sort of entangled (by analogy with quantum physics and the EPR principle). Therefore, our provocative claim that future swarms generation will be quantum swarms.

Serge Chaumette

Conference Proceedings

Engaging All Elderly Residents in Community Renewal: Designer Spotlight Interview Tool for LLM Building

The natural language processing capabilities of Large Language Models (LLMs) can significantly enhance designers' ability to quantify unstructured information and improve communication with users, which is particularly important in rapidly aging societies. As elderly individuals engage in community renewal projects, they often face comprehension and expression barriers due to differences in cultural backgrounds and cognitive abilities, which complicates the acquisition of tacit knowledge for designers. To address this, we developed an AI community renewal toolkit, CommUnity AI, utilizing the fine-tuned ChatGPT-4o model. This toolkit provides easy-to-understand feedback to older adults through the creation of visual and textual information cards, and its effectiveness was evaluated in our study. The experiment involved 24 older adults and 6 designers, divided into experimental and control groups, and three separate focus group interviews were conducted. Using the SERVQUAL model to analyze the results, we found that the elderly participants showed greater trust and acceptance of the toolkit compared to traditional interview methods.CommUnity AI provides high-quality feedback through language comprehension, data collection, and visual and textual feedback, effectively reducing communication time while considering the needs and comprehension abilities of the elderly. This study underscores the potential of LLMs in community co-design, offering theoretical and practical insights into how designers can collaboratively engage with elderly individuals, ultimately fostering more inclusive and friendly community environments.

Ruchen Hu, Zihui Chen, Mengshi Yang, Qiong Wu

Conference Proceedings

AI Play in Higher Education: Students’ perceptions of play and co-creation of knowledge with generative AI

Playful learning approaches are expected to take a leading role in digital transformation in higher education (HE) (Tonkin, 2019; Whitton, 2022). Artificial Intelligence (AI) is changing the world impacting education, necessitating the development of new skills (Einola & Khoreva, 2023) meaning that aspects of teaching, learning, and knowledge building are set to radically change, and there is a need to strengthen the capacity of learners to engage with the world around them, especially through imagining and envisioning the future in the digital age (e.g., UNESCO, 2020). It is believed that through play individuals can learn to manage the unforeseen (Pors & Andersen, 2015). Therefore, in order to harness the power of play and digitalization for creativity and innovations, learners and employees need new playfulness-based and creative digital literacies. While generative AI (e.g. ChatGPT) is being widely explored, it has been mainly investigated through the functionality of the technology, and not the possibilities for engendering playful learning. Consequently, research on AI-human interaction as playful knowledge co-creation is entirely lacking.This study addresses this challenge by tapping the research on playful learning in the context of HE and educational sciences. Playful Learning (PL) refers to learning activities embedded with playful engagement and exploration, seeking learners to be active participants in their learning process. It recognizes creativity, emotions, narrativity, collaboration, and embodiment as essential elements of learning, complemented by appropriate tools and pedagogical strategies (Kangas et al., 2017). Here, the use of playful tools refer to co-creation with generative AI. During their playful learning process, 17 HE students co-created educational play-based activities and used generative AI in their designs. This knowledge co-creation was conducted as part of a Playful and game-based learning course in collaboration between two Finnish universities. One aim of the course was to increase HE students’ awareness of the potential of playfulness and AI in future pedagogies through playful learning activities. We asked: How do students understand play and non-play, and how do they see generative AI in their playful learning process? Data consists of students’ writings in which they reflected their ideas about play and non-play and the use of AI in the task. Our study contributes to the areas of playful learning, educational sciences, and emerging research on the applications of generative AI used as part of higher education. The findings indicate that the students' perspectives on play could be divided into five different dimensions: 1) openness and freedom, 2) well-being and joy through play, 3) enjoyment of the use of imagination 4) potential for skill development, and 5) playful social interaction. As the opposite of play, the students see a lack of imagination, bleakness, and a kind of greyness. The findings also indicate that generative AI provides a useful tool for playful learning in the HE context due to its potential for 1) Challenges and learning, 2) Ideation and creativity, 3) Opportunities and critical use, and 4) Enrichment and inspiration. Based on our findings, the AI Play framework was constructed, including facets of playful exploration and co-creation combined with critical thinking, which illustrates the dimensions of AI Play as part of HE students’ playful learning.

Marjaana Kangas, Katriina Heljakka

Conference Proceedings

Optimizing AI Involvement in Engineering University Courses Based on Students' Personality

Artificial Intelligence (AI) enhances educational experiences in engineering but varies in effectiveness based on student personality traits. This study investigates the impact of personality traits on engineering students' perceptions of Artificial Intelligence (AI) to optimize AI integration in university courses. Data was collected from students enrolled in two engineering courses during the Academic Year 2023-24. The analysis focused on the Big Five personality traits and various AI perception dimensions. Considering different levels of multivariate regression analysis, we identified key personality traits influencing students' attitudes towards AI. The findings suggest that tailoring AI integration to students' personality profiles can enhance engagement and learning outcomes. Future research should explore additional factors, such as age and attitudes towards technical roles, to further refine educational strategies.

Stefano Filippi

Conference Proceedings

Predictive Model for Partner Agencies Dependency on Food Banks

In the quest for equitable resource distribution within food banks and their partner agencies, understanding the dependencies of these agencies on food banks emerges as a critical factor. This study investigates the intricate dynamics influencing agency dependency ratios, exploring the complex factors that shape the demand for food resources. Leveraging historical self-reported dependency ratio data, this preliminary study employs predictive modeling using Multiple Linear Regression to forecast agency dependencies on food banks. The primary objective is to discern the underlying factors that significantly impact agency dependency ratios. Employing Least Absolute Shrinkage and Selection Operator (LASSO) as a feature selection technique, the study identifies the key variables that capture the essence of the dataset. Identifying the variables that contribute the most to the model paves the way for robust predictive modeling. This study offers a comprehensive approach to understanding and predicting agency dependencies on food banks. The findings hold significant implications for non-profit hunger relief organizations, aiding in strategic decision- making for equitable resource distribution.

Henry Ivuawuogu, Steven Jiang, Lauren Davis, Mikaya Hamilton

Conference Proceedings

Investigating common factors needed for consumers to trust AI\ML

Is there a set of trust factors that might apply to all Machine Learning (ML) algorithm types and domain applications, independent of behavioral variations? Can this common set of factors support a baseline standard represented by a ML trust scorecard? These questions are being investigated by The Technical Cooperation Program (TTCP) involving Australia, Canada, New Zealand, United Kingdom (UK), and the United States of America (USA). This paper describes the results of an initial investigation into whether a common set of factors allows consumers to initially trust ML in critical situations. The goal was to determine if job role variations were statistically unaffected by confounder bias by modeling causal relationships and analyzing influences. Through Qualtrics, questions containing factors derived from TP 8864 AI Level of Rigor, the document used by USA and UK governments to develop official guidance, were deployed to 81 international participants consisting of various roles with technology, specifically developers, operators, and users. Participant roles consisted of a mix of autonomous and ML Systems used in surface, subsurface and land system domains. Not all autonomous participants had ML knowledge. Introducing a Behavioral Dynamics Model (BDM) became key in designing Likert scale questions containing perception, needs, and experience grouping of related factors. This design allowed for a statistical investigation of whether causality between groups affect bias towards ML. The BDM survey grouped trust factors that mapped to a ML Scorecard design consisting of Calibration, Experience, and Fatality (CEF) categories: - Calibration (ML algorithm’s limitation and strengths – represents testing requirements): --- (Likert Scale) Perceptions factors investigated: Safety, Dependability, Reliability, Suspicion, and Comfortability. --- (Likert Scale) Needs factors investigated: Human Oversight, Performance, Development, Teamwork, Adaptation, Improve Ability of Success, and Proof. - Experience (ML Algorithm’s ability to conform to consumer paradigms – represents training requirements): --- (Likert Scale) Experience factors investigated: Positive History, Past Usage, Training Adequacy, and Expectations ML Systems Fail on First Use. - Fatality (ML technology’s ability to provide decision rationale – represents development requirements): --- Open-Ended Questions: Responses aligned to Perceptions, Needs and Experience factors with emphasis on demonstrating transparency, security, certification, and ethics. By using a statistical decomposition approach of 19 hypothesis investigated using ANCOVA, ANOVA and t-test analysis, common factors for a scorecard emerged, with one exception involving adaptation in the Calibration category. From the open-ended questions, different patterns emerged based on role variations for developer, operator, and user. The key similarity was that to establish trust, strong evidence through observation or test is needed. Differences were that developers wanted oversight and reliability of an ML system, while users and operators generally wanted ML operational capability experience. Additionally, evidence indicated that the ML system needs to be trained to replace human interaction either by conforming to the participant’s past experiences or ensuring that the participant is adequately trained to trust a new ML paradigm. The findings showed that the Behavioral Dynamics Model successfully extrapolated TP 8864 guidance into questions about trust that statistically determined a common set of factors in a CEF scorecard for ML algorithms, independent of technical roles.

Alana Nagy, Bruce Nagy, Scot Miller

Conference Proceedings

Exploring the Impact of Artificial Intelligence Generated Content (AIGC) on Game Design and User Experience

With the rapid development of artificial intelligence-generated content (AIGC) technology, the gaming industry is undergoing major changes. This study explores the application of AIGC in game design and analyzes its impact on art, music, text, interaction and user experience. The innovation of this study is the integration of AIGC to enhance the creativity, quality, and interactivity of game design while proposing solutions to current industry challenges. This study uses methods such as literature review, case analysis, and user surveys to evaluate the effectiveness of AIGC by comparing traditional and AIGC-enhanced game design methods. Follow user-centered design principles and analyze data from case studies, user questionnaires, and designer feedback to identify key issues in user experience. The results show that AIGC significantly increases user engagement by creating personalized, immersive experiences and provides new development opportunities for the gaming industry. In summary, AIGC technology has demonstrated the potential to revolutionize game design by solving creative and technical challenges, paving the way for future innovation and prosperity in the gaming industry.

Yi Jing Wang, Xin Hu

Conference Proceedings

Semantic Difference Method for Artificial Intelligence Assisted Cruise Ship Cabin Design

In the traditional design process, for determining the form of a single project or product, designers often need to create hundreds to thousands of sketches. However, in the field of cruise ship interior decoration design, this issue becomes more complex. Each large cruise ship has thousands of rooms. Due to restrictions on room types and user needs, they each require unique interior decoration plans; at the same time they must maintain consistency with the theme of the entire cruise ship. Therefore, in the process of cruise ship interior design, designers often have to draw thousands of detailed interior design drawings. Facing such a huge amount work task under an industrial age background undoubtedly puts great pressure on designers.As we gradually step into the era of artificial intelligence, generative AI technology continues to achieve significant breakthroughs, such as ChatGPT and Midjourney, which can generate required images or text information based on keywords or prompts. Designers leverage these advanced technologies like AIGC to generate images by inputting a few keywords and can thus create vast image resources to provide them with abundant sources of inspiration. This method significantly enhances the design efficiency and creative quality of designers in an academically translated way.However, stark differences exist between the comprehension of images by artificial intelligence generative technology and designers. Machines struggle more with understanding adjectives than other types of words, such as 'luxurious' or 'classical', which are highly associated with people's cognitive preferences. Designers often find in using AIGC that the system-generated images do not fully meet their anticipated needs; a large proportion of the images generated by AIGC require subsequent adjustments and cannot be directly applied. This raises the issue at focus in this research: there is a discrepancy between human cognition of vocabulary and machine understanding.Therefore, in this context, we have chosen cruise ship interior design as the case study for our research. From a designer's perspective, we delve deeply into understanding the cognitive discrepancies that exist between artificial intelligence and humans. Firstly, we thoroughly examine the differences in understanding adjectives between AI and humans, incorporating existing research results to empirically construct a semantic evaluation scale specifically for cruise ship-related terminology. This scale aims to describe, measure and analyse these cognitive discrepancies and ultimately provide an effective tool to assist cruise ship interior designers conduct innovative designs more accurately and efficiently.The method adopted in this research is the integration of Kansei engineering and AI generative technology AIGC applied to the relatively novel field of cruise ship interior design, combined comprehensively with Semantic Differential (SD) approach. The SD method can use adjectives to reflect group preferences for images and environments to a large extent. We have selected the most representative words associated with cruise ship style through analysis, collected typical images, and categorized them. Then we utilized the SD method to conduct detailed analysis on accumulated vocabulary and pictures, creating descriptive statistical reports which ultimately form a language evaluation scale specifically reflecting elements and concepts characteristic of cruise ships.In theoretical terms, this study employs the method of Kansei Engineering to construct a semantic evaluation scale specifically for cruise interior design, thereby further enriching the evaluation framework in this field. In practical terms, it introduces AIGC as an aid to stimulate designers' innovative thinking and provide reference image inspiration to enhance their overall design efficiency.

Yuwen Fang, Yitong Qiu, Anthony Kong, Gang Liu

Conference Proceedings

Voice function operation in hospital intelligent registration systems

Based on the technological development trend of modern society, hospitals use intelligent registration machines to provide support to human workers. At present, the self-service registration machine presents the following interactive problems: due to the inconsistency of department names across various hospitals, the operator struggles to accurately find the target option that meets the needs of their illness on the machine, instead they have to seek manual consultation at the triage desk. However, under normal circumstances, the triage table is often understaffed with no clear queuing rules. In such environments, this is more likely to increase anxiety and other stressful emotions that can result in contradictions and disputes between patients and staff. Moreover, the system used by the self-service registration machine may not be suitable for the elderly and similar patients who are not familiar with technology use, and not as accessible for the visually impaired. Therefore, in order to facilitate the improvement of intelligent registration machines, field research was conducted in three different hospitals currently using said self-service machines. To investigate the interaction process, the researcher observed the use of the equipment in the hospital environment and patients were briefly interviewed on how the machines may be inaccessible. Patient responses were then sorted into key points, coded, and grouped into specific problems. Field research can effectively gather information of the significant problems in the environment the equipment is used such as the user's emotions, grasp the common problems of use by the public, and propose targeted solutions. Finally, this study is aimed to optimize the device interaction by adding the voice recognition function and make a targeted voice dialogue registration system design to the self-service machine. Upon returning to the research site to ask the patients whether the addition of the voice system could improve the efficiency of operation, the consensus was unanimously affirmed. The addition of the new voice functions in intelligent registration equipment can effectively improve the registration efficiency, reduce the error rate of department selection and reduce the probability of hospital disputes, and also can relive the pressure of triage desk manual service, and form a better general hospital environment. The specialised voice registration can reduce the difficulty of operation for the elderly, the visually impaired, and those whose disabilities make it inconvenient to use such machines, and broadens the scope of use.

Xuanhui Yan, Xin Hu

Conference Proceedings

Construction of Japanese-Chinese Onomatopoeia Corpus Based on Events and Behaviors

Numerous manga (Japanese comics) are translated into various languages every year, but the onomatopoeia that depicted in Mangas frequently controls the strength and nuance of the impression by repeatedly using prompts and long notes often remains untranslated, which prevents many manga fans from having the full reading experience. This study focuses on translating Japanese onomatopoeia into Chinese as a first step. The ultimate goal for this research is to translate onomatopoeia into multiple languages. In previous research, the focus was primarily on translating the onomatopoeia itself, whereas this study proposes a method that translates both the onomatopoeia and its related words. Toward this end, we constructed a Japanese-Chinese onomatopoeia (JCO) corpus. Our dataset includes an accurate translation of each onomatopoeia as well as a related word that makes the sound or indicates the event or behavior. The corpus is mainly composed of onomatopoeia found in Manga 109, with additional entries collected from the internet. The most appropriate word is determined by calculating the cosine similarity and Levenshtein distance. If the word cannot be determined from our dataset, we use the International Phonetic Alphabet (IPA) to transcribe the Japanese characters into their closest Chinese phonetic counterparts. The onomatopoeia depicted in mangas frequently controls the strength and nuance of the impression by repeatedly using prompts and long notes, which adds to the complexity of translating these terms accurately. This is because the repeated use of certain characters and the lengthening of sounds in onomatopoeia can convey different intensities and subtleties of the depicted actions or emotions. We also developed a tool to aid manga translators in determining the most appropriate translation for onomatopoeia. The tool works by allowing users to input Japanese onomatopoeia and their related words, and then automatically outputs the most suitable Chinese translation.During our experiments, we randomly selected five manga from Manga 109 and extracted 100 unique onomatopoeic words for testing. The resulting translations were evaluated by native Chinese speakers who are also proficient in Japanese and Japanese speakers who are also proficient in Chinese, and their overall feedback was positive, indicating that the corpus and tool could be used to translate onomatopoeia with sufficient accuracy.

Wenjing Zhang, Amika Chino, Siyu Yan, Takehiro Teraoka

Conference Proceedings

Creative Collaborator: AI-facilitated UI for Creating Engaging and Insightful Memes

Memes have become a prevalent part of digital culture, transcending their origins as simple internet jokes to become powerful tools for communication, social commentary, and even education. Their social and cultural use is diverse, serving as a universal language for expressing complex ideas, fostering community, and providing a platform for social critique. Studies such as Tidy et al. (2024) and Brown (2020) have highlighted the educational potential of memes in STEM fields, demonstrating their effectiveness in simplifying complex concepts and engaging students. Platforms for meme creation have the potential to develop an environment that boosts the meme-making process.Existing platforms (i.e. imgflip.com, an online free memes generator) rely entirely on user input and do very little to guide the users in memes creation. Traditional user interfaces of memes generators are simple and easy to operate, but no contextual authoring support, which may limit the creative potential and content construction. Thus, we hypothesize that AI can expedite the creative process by presenting relevant meme templates, and generating suggested captions, acting as a “creative collaborator” for users. In this work, we explore utilizing OpenAI’s GPT-3.5 to facilitate the creation of educational and engaging memes, leveraging its ability to generate humorous and informative content.To evaluate the effectiveness of our approach, we conducted a comparative case study with Imgflip’s free online meme generator. Participants created waste management related memes using both tools, and we assessed their productivity, creativity, and satisfaction. Qualitative feedback revealed the AI tool's LLM capabilities, hints, and instructions as key drivers of its enhanced performance. These findings highlight the potential of AI to revolutionize meme creation and inform the development of future user interfaces that leverage AI to enhance creativity, engagement, and educational impact.

Romeo Nickel, Sharon Hsiao

Conference Proceedings

Comparison of AI Model Serving Efficiency: Response Time and Memory Usage Analysis

NLP (Natural Language Processing) models are in increasing demand, making the research into effective serving methods crucial. Particularly, cost efficiency and rapid response times are key factors in the serving process of NLP models. This paper compares various methods for optimizing the serving of NLP models. Three serving methods were applied using REST API, TensorFlow Serving, and TensorFlow.js, and each method's response speed and memory usage were evaluated. This research is thought to provide foundational guidelines for enhancing the efficiency of serving NLP models, aiming to minimize potential issues in the serving process and improve user experience through such studies.

Ji Yeon Kim, Seong Hyeon Jo, Ha Sang-hyun, Ki Hwan Kim, Young Jin Kang, Seok Chan Jeong

Conference Proceedings

Examination of Evaluation Indices for Micro-Influencers Considering Community Structure and Post Contents

Social networking services (SNS) have become indispensable communication tools. Consequently, influencer marketing, which leverages users with a significant influence on SNS, has garnered significant attention. Among these influencers, micro-influencers, who have substantial influence within specific domains, are particularly interesting to both academia and industry. This study proposes evaluation indices that can effectively select micro-influencers for product promotion using follower data and past posts from SNS accounts. Specifically, we propose four evaluation indices for micro-influencers: Virality, Commonality, Expertise and Credibility (VC-EC indices). VC indices are based on network features, whereas EC indices are based on language features. In this study, we present the concepts and specific calculation methods for the proposed indices. In addition, we demonstrate how to discover micro-influencers using the proposed methods with practical examples from accounts operated by actual stores.

Kohei Otake, Ryo Morooka

Conference Proceedings

Ergonomic Problem and Solution Identification by Applying Image Captioning with Embedded Ergonomic Knowledge

Work-related musculoskeletal disorders (WMSDs) are a primary cause of non-fatal injuries in diverse industries. Traditional manual ergonomic problem and solution identification for reducing WMSDs is time-consuming and limited by expert availability. Image captioning—interpreting images of workers and their workplaces and capturing interactions therein—is one potential alternative. Yet, due to the absence of ergonomic knowledge, conventional image captioning models are limited in generating accurate captions of ergonomic problems and solutions. Therefore, we aim to automatically identify ergonomic problems and solutions from images by applying image captioning embedded with an ergonomic knowledge graph. Specifically, we developed an ergonomic knowledge graph encoder and incorporated it with the state-of-the-art image captioning model. Comparative testing on eight ergonomic problem-solution pairs showed that our model outperformed the state-of-the-art model. This result highlights the critical role of integrating ergonomic knowledge into image captioning models, paving the way for broader workplace applications to reduce WMSDs.To this end, we first crafted ergonomics knowledge graphs based on essential elements for ergonomic problem and solution identification, such as ergonomic risk factors and task information. Subsequently, we made a pipeline identifying pre-built ergonomics knowledge graphs from images through object detection and pose estimation. Finally, we modified an image captioning model to interpret images based on our knowledge graphs. We used an instruction-tunable image captioning model as the backbone model. While traditional models generate captions solely from images, instruction-tunable models can generate captions based on both images and textual instructions. Specifically, we harnessed InstructBLIP for its robust performance and modified it to accept non-textual instructions, i.e., ergonomics knowledge graphs.For training and testing, we collected 2,000 images from various real workplaces. For each image, we associated it with one of our knowledge graphs and annotated it with a caption describing an ergonomic problem and its corresponding solution according to a NIOSH ergonomic guideline. Our dataset consequently consists of 2,000 pairs, each comprising an image, a knowledge graph, and a caption. The bilingual evaluation understudy (BLEU) metric was utilized to assess the image captioning performance in ergonomic problem and solution identification. BLEU quantifies the similarity between artificial intelligence (AI)-generated captions and human-generated captions on a scale from 0 to 1. To demonstrate that the ergonomics knowledge graph enhances the performance of identifying ergonomic problems and solutions, we compared our model with our backbone model, which generates captions without ergonomics knowledge graphs. In terms of the BLEU-4 score, which compares sequences of four consecutive words, our model scored 0.834, while the baseline model scored 0.712. Our superior BLEU score indicates that the captions generated by our knowledge graph-enhanced model are more similar to the ergonomic problems and solutions specified in the ergonomic guideline than those generated by existing models.This result demonstrates the feasibility of image captioning with embedded ergonomics knowledge for automated ergonomic problem and solution identification from images. Our accessible automated approach is designed to assist in reducing potential WMSDs by intervening in hazardous workplaces where ergonomics knowledge or ergonomic experts are limited.

Gunwoo Yong, Quan Miao, Meiyin Liu, Sanghyun Lee

Conference Proceedings

Digital Transformation Readiness Level of Royal Thai Air Force

This research aims to develop a comprehensive toolkit to assess the readiness of the Royal Thai Air Force (RTAF) for organizational change as it transitions into the digital era, based on the framework provided by the United Nations Development Programme (UNDP).The primary objective of this study is to design a robust toolkit to evaluate the RTAF's preparedness for digital transformation. This toolkit is an adaptation of the UNDP's framework, tailored to address the specific context and requirements of the RTAF. To ensure the content validity of the toolkit, an expert evaluation was conducted involving three specialists. The reliability of the toolkit was confirmed with a Cronbach's alpha coefficient of 0.82.The study employed a quantitative approach to determine the overall readiness level of the RTAF for organizational change, which averaged 70.49%. The assessment covered various domains, with the following readiness levels: Innovation Ecosystem (46.67%), Basic Digital Utilities (Technological Infrastructure) (63.53%), Basic Data Utilities and Data Infrastructure, Strategy, and Management (66.67%), Cyber Security, Privacy, and Resilience (70.22%), Legal Basis (73.33%), Organizational Culture and Employee Skills (76.67%), Public Administration Reform (77.50%), Management (77.62%), and User-Oriented Design (82.22%).The findings reveal that the overall readiness level has not yet met the 80% standard threshold. The relatively low score in the Innovation Ecosystem domain indicates it may not be a core mission of the RTAF. Additionally, budget constraints likely contribute to the readiness level of basic digital infrastructure falling below 70%. Nevertheless, readiness levels in other areas range from 70.00% to 80.00%, suggesting a positive trend towards achieving higher readiness in the future.Despite existing challenges, the RTAF demonstrates a promising trajectory towards enhanced digital readiness, particularly in organizational culture, employee skills, public administration reform, and user-oriented design. Strategic investments and focused efforts in weaker areas such as the Innovation Ecosystem and basic digital infrastructure will be crucial for achieving comprehensive readiness for digital transformation.This study underscores the importance of a tailored approach to evaluating organizational readiness for digital transformation. The RTAF's strengths in several key domains provide a solid foundation for future improvements. Addressing the identified weaknesses through targeted investments and strategic initiatives will be essential for the RTAF to fully embrace the digital era.

Varit Intrama

Conference Proceedings

Organisational Change and Building Human-Tech Resilience in Industry 5.0

The advent of Industry 5.0 marks a transformative era, characterised by the seamless integration of human capabilities with advanced technologies. This shift, which places human-centric design and collaboration at the forefront, promises to revolutionise the workforce landscape. However, it also presents a series of opportunities and challenges for organisations aiming to maximise value creation. Central to Industry 5.0 is the optimisation of the value proposition, encompassing quality, service, and cost. Achieving this balance requires a nuanced approach that leverages technological advancements to enhance efficiency while maintaining the essential human elements that drive superior quality and customer service. One of the critical factors in the success of Industry 5.0 initiatives is the tension between individual upskilling measures and organisational acceptability rates. As technology evolves rapidly, individuals must proactively acquire new skills to stay relevant. Yet, the pace at which employees upskill often outpaces an organisation’s capacity to integrate and utilise these new competencies effectively. This discrepancy can hinder the full realization of value creation initiatives. On the other hand, organizations that do not create environments conducive to continuous learning and skill development risk falling behind in the competitive landscape of Industry 5.0. Resistance to change or insufficient investment in workforce development can lead to a significant gap between an organization’s capabilities and the demands of the new industrial paradigm. To navigate these challenges, a holistic approach is necessary—one that harmonizes individual growth with organizational priorities. Effective strategies include comprehensive workforce planning that aligns skill development with organizational needs, fostering a culture of lifelong learning, and providing accessible upskilling opportunities. Additionally, leveraging human-centric technologies that augment rather than replace human expertise is crucial. Encouraging cross-functional collaboration and knowledge sharing can also accelerate the adoption of innovative technologies, thereby enhancing organizational adaptability. Implementing metrics to measure the impact of upskilling initiatives on value creation is another essential strategy. These metrics can provide insights into the effectiveness of training programs and help organizations fine-tune their approaches to workforce development. By striking the right balance between individual upskilling measures and organizational acceptability rates, companies can unlock the full potential of Industry 5.0. This balance enables them to position themselves as leaders in value creation, optimizing quality, service, and cost considerations. In conclusion, the paradigm shift ushered in by Industry 5.0 requires a mindset that embraces continuous adaptation and fosters a symbiotic relationship between humans and technology. Organizations must prioritize strategies that harmonize the upskilling of individuals with organizational needs, ensuring that they can effectively navigate the complexities of this new industrial era. By doing so, they can achieve significant advancements in value creation, ultimately leading to sustained competitive advantage and growth in the Industry 5.0 landscape.

Daniel Rukare, Nikhil Soi, Asmita Singh Bisen

Conference Proceedings

Contemporary Innovative Application of Ancient Glaze Craft under the Perspective of Non-Heritage Revitalization

Ancient glaze is a material aesthetics with Chinese cultural characteristics, and the ancient glaze firing process combines art and culture as a national intangible cultural heritage. However, in the context of modernization and the impact of contemporary emerging art and high technology, the inheritance and development of the application of ancient glaze craft is limited. This paper takes the ancient glazing craft as a carrier, analyzes and summarizes the deficiencies in the existing specific design practice cases, and proposes a more systematic and structured design thinking framework, from material to spiritual to organizational levels of creation.Taking the large-scale glaze art installation of Fuyao University of Science and Technology "Heart Like Bodhi" designed by Prof. Luo Yan's team from the School of Design of Shanghai Jiaotong University as an example, this paper discusses how to utilize ancient glaze craft to carry out contemporary design innovation, and combine science and technology to realize the living inheritance of intangible cultural heritage.

Yuxi Yuan, Yan Luo

Conference Proceedings

Use of computational fluid dynamics in the design and analysis of heat exchange devices

A high-performance heat exchanging devices are gaining traction in many applications. This study aims to investigate heat transfer in a microchannel heat exchanger. A computational fluid dynamics (CFD) model is developed to examine performance under various flow conditions, assuming a steady-state operating condition. The effectiveness of the heat exchanger is studied by varying the inlet flow rate, with investigations conducted for different Reynolds numbers ranging from 200 to 2000. A single channel repeating unit from both the hot and cold sides of the heat exchanger is modeled. The effectiveness of the heat exchanger is determined using the inlet and outlet thermal condition of the heat transfer fluids. The thermal performance of the heat exchanger, including effectiveness and overall heat transfer coefficient, is examined for different flow rates. The effectiveness of the heat exchanger strongly depends on the channel size. It is found that increasing the Reynolds number decreases effectiveness while increasing the overall heat transfer coefficient. It is concluded that the use of microchannel can significantly improve the performance of heat exchangers in many applications. Using CFD can be substantial enhance understanding of fluid and heat transfer in heat exchanging devices.

Bobby Mathew, Fadi Alnaimat

Conference Proceedings

Computational Design of a Naval Unit For Rapid Intervention In Case of Marine Eco-system Disaster

The design and accomplishment of the systems used in the marine field (targets with direct sight, radar targets, floating units) require the analysis of the hydrometeorological conditions characteristic of the open areas of the marine shore areas of the coast, respectively: H wave = 6 - 8 m; L wave = 25 - 30 m with trochoidal waves (multi-directional and multi-component waves), V current = 1.5 m/s, as well as the nature of the substrate (sandy areas). For the digital design and loading of the patterns of the Naval Rapid Intervention Unit, the Optitex Pattern Making software was used. With the help of the modules included in the program, the changes made on the patterns were additionally transferred to the virtual model that provided: visualization of modules created as 2D patterns in virtual 3D mode; analysis of how changes made to 3D models affect 2D patterns; direct transition from concept to virtual 3D model with all aspects related to the fully defined product (material properties and their behavior). The equipment was tested and analyzed based on the physical-mechanical performance level, and the main statistical parameters were determined as essential elements for the optimization of the proposed technological solution.

Alexandra Gabriela Ene, Carmen Mihai

Conference Proceedings

Advanced Numerical Simulations For Seakeeping Performance Analysis Of A Floating Architecture Based On Textile Structure

The paper presents the results of the seakeeping performances on the regular wave through advanced numerical simulations of a floating unit intended for the capture, storage and transport of hydrocarbons. The behavior of the floating unit in a frontal regular wave with a height of 0.6 m and a length of 5.3 m was investigated, at speeds of 0 and 2 knots, considering the 3 drafts corresponding to the cases of loading with 75%. The numerical tests were based on solving the RANS equations. For the qualitative investigation of the hydrodynamic characteristics of the flow in a regular wave, the free surface and the analyzed architecture were represented at different time steps for the stationary ship and at the speed of 2 knots. Based on the results of the short-term seakeeping analysis, to avoid complete immersion of the floating unit, the most significant restrictions on navigation with 75% hydrocarbon loading were determined.

Alexandra Gabriela Ene, Carmen Mihai

Conference Proceedings

CatMapper: user interface support for large complex categories and semantic data exploration

Scientists and policymakers are increasingly leveraging complex, multi-scale data from diverse, worldwide sources to understand the causes and consequences of economic development, social stratification, climate change, cultural diversity, and violent conflict. This work frequently requires integrating data across diverse datasets by complex, dynamic categories (e.g., ethnicities, languages, religions, subdistricts). However, different datasets encode corresponding categories in disparate formats and at different resolutions (e.g., Guatemala Indigenous vs. Maya vs. K’iche’). These diverse encodings must be translated across datasets before bringing them together for analysis. At global scales across thousands of categories, the combinatorial complexity creates thorny challenges for manual reconciliation and for transparent documentation and sharing of researcher decisions. There is a need to investigate direct and uncomplicated ways to support search and explore the semantics for complex and diverse datasets.We design and deploy such a tool, CatMapper, to support semantic discovery through exploration and manipulation for large, complex and diverse datasets. CatMapper enables exploring contextual information about specific categories, translating new sets of categories from existing datasets and published studies, identify and integrating novel combinations of datasets for researchers’ custom needs, including automatically generated syntax to merge datasets of interest, and publishing and sharing merging templates for public re-use and open science. CatMapper does not store observational data. Rather, it is a dynamic, interactive dictionary of keys to help users integrate observational data from diverse external datasets in disparate formats, thereby complementing and leveraging a fast-growing ecology of datasets storing observational data. We have conducted heuristic evaluation on CatMapper usability. Results shed lights on enriching semantic data discovery.

Sharon Hsiao, Harsha Kasi, Daniel Hruschka, Robert Bischoff, Matthew Peeples

Conference Proceedings

Application of Architectural Appearance Design Process in Front Area of Fossil Fuel Power Plants Based on AIGC Collaboration

This paper examine the development, evolution, and application of AIGC (Artificial Intelligence Generated Content, AIGC), the research finds the applicable method of applying AIGC in the exterior design of the front area of fossil fuel power plants through practical cases, and verifies the feasibility of applying this technology to the above industrial projects at present. The collaborative design model of the architectural appearance of "AIGC+" fossil fuel power plants put forward. The conceptual scheme diverges through AIGC technology and then converges through the professional evaluation of human experts, which complements the advantages of human beings and AIGC. The feasibility of the design model is demonstrated by applying the model to the exterior design project of the front area of the actual fossil fuel power plants. Although there are still some shortcomings in the application of "AIGC+" in the architectural appearance design of the front area of the fossil fuel power plants, compared with the traditional architectural appearance design process, the design efficiency is greatly improved and the types and styles of schemes are more diverse. This design model can ensure the quality of the conceptual design scheme to a certain extent, effectively save design time and cost, improve design efficiency, and save money.

Mengying Tang, Jie Jiang, Xi Chen

Conference Proceedings

Innovative AI-Drive Product Design: Leveraging Language Models and AI Image Generators - A Case Study on Insole Design for High-Heeled Shoes

Artificial Intelligence (AI) technologies, is the crucial topic all fields of professionals are researching in, it’s one of the icon of this era and its influence on our daily lives is significant, and continuously growing. Incessantly, noticing by designers and making its way into the world of product design. Language Models are to generate ideas and concepts as inspirations, while AI Image Generators are to create graphics as an alternative rapid prototyping. These functional tools are assisting designers in all sorts of ways, as well as Product Design Process (PDP). However, AI’s ability related to Ergonomics is still exiled, owing to its trained in a big data of information but not really understanding the application of Human Factor Engineering. The insole of high-heeled shoes is chosen as the product to be designed, in view of their ergonomic needs and 3D modelling logic. With AI tools assisting among stages of PDP, this paper proposed a new process of Product Design, intended to compare the efficiency of and outcomes between Traditional 4D PDP and AI-Driven PDP. This paper underscores the transformative potential of AI in product design, highlighting its ability to merge creativity with analytical precision, thus fostering more efficient and effective design workflows.

Zun-hwa Chiang, Wei-wei Su, Ming-hsien Chuang

Conference Proceedings

Emerging threat of deepfakes: viability, risks, impacts and mitigations through a practical use case

Early 2024 an employee was tricked to transfer 25 million dollars in a cyber-attack where live deepfakes were used to convince the employee of the legitimacy of the request (Chen and Magramo, 2024). Deepfakes are media (image, audio, and video) edited by an algorithm. In the case of the malicious deepfake e.g. video input, it enabled real time interaction between a target and the deepfake. The availability of software and hardware enabling anyone to create their own high quality deepfakes has become such a threat that Europol in 2022 stated: “Many organisations have now begun to see deepfakes as an even bigger potential risk than identity theft (for which deepfakes can also be used), especially now that most interactions have moved online since the COVID-19 pandemic” (Europol, 2022). This paper presents experiences from creating live deepfakes based on typical online, openly accessible media, using free software and a gaming computer, following a free online guide. Without previous experience with deepfakes, we were able to select settings that yielded high quality deepfakes with less than one hour of exploring. The activity of labelling faces requires very little skill. Based on the use case, we provide examples of the achieved quality and discuss cyber and information security implications for organisations. Interviews were performed with a set of small and medium sized organisations regarding their awareness and preparedness for dealing with deepfakes. Industry start to become aware of potential threats of deepfakes, but lack procedures, processes and awareness to be able to sufficiently mitigate deepfake risks. Finally, we suggest a set of best practices and procedures for identifying, and mitigating such threats, focusing on technology, organisation, and the human element.Chen, H. and Magramo, K. (2024) Finance worker pays out $25 million after video call with deepfake ‘chief financial officer’ | CNN. Available at: https://edition.cnn.com/2024/02/04/asia/deepfake-cfo-scam-hong-kong-intl-hnk/index.html (Accessed: 11 June 2024).Europol (2022) ‘Facing reality? Law enforcement and the challenge of deepfakes, an observatory report from the Europol Innovation Lab’. Publications Office of the European Union, Luxembourg. Available at: https://www.europol.europa.eu/publications-events/publications/facing-reality-law-enforcement-and-challenge-of-deepfakes#downloads (Accessed: 11 June 2024).

Levente Nyusti, John Eidar Simensen

Conference Proceedings

Threat analysis for autonomous vehicle systems

Connected Automated Vehicles (CAVs) have significant role for enhancing logistics operations by providing improved efficiency, cost savings, traffic safety and to diminish environmental foot print. These are all major features of a competitive logistic operations of a modern company that seeks business advantage via its logistic operations. Already multiple types of CAVs are supporting logistic operations in warehouses, mines and generally in restricted areas in factory type environments. Reliability and safety of automated vehicle systems (AVS) can be realized in restricted environment for CAVs that operate on predetermined fixed routes relatively easy since these restricted environments have usually dedicated communication network that is not open to the Internet. This is not the case when CAVs start operating on public roads, in air space or at sea. There are already pilots in place that are using level 5 CAVs for delivering packages for a first/last mile logistic service on public roads and to provide taxi services for public with in a city. These CAVs require full support from AVS and they rely fully on public communication infrastructure to provide safe and secure services. Vehicles that require AVS services are in all practical means computers with full of multiple sensors and software that can and must utilize variable communication solutions in order to function as intended. Therefore, this paper’s research problem and focus is to analyse potential threats scenarios of a CAV and to find vulnerabilities of an AVS. The problem is analysed via general AVS use case and focus is on level 5 fully autonomous system when a vehicle can perform all driving tasks under all conditions without human intervention. Some of the very same vulnerabilities already exists today even for level 2 vehicles that have advanced driver assistance system (ADAS) since they regularly use public communication infrastructure to access service providers data platform. The vulnerability analysis mainly focuses on vehicle to everything communication cases, vehicle to vehicle communication cases and analyses potential risks for intra-vehicle operations if cyber security protection fails. This will provide better understanding for logistic operators how to prevent AVS’s complete, disastrous shut down by an external threat.

Markus Sihvonen, Reijo Savola

Conference Proceedings

Trust Us: A Simple Model for Understanding Appropriate Trust in AI

We address the dissonance in the formal study of trust in artificial intelligence (AI) by presenting a simple trust model that connects the two most-commonly cited definitions of trust. This dissonance can be largely attributed to the fact that expressions of trust are familiar to us, but the abstract concepts we formally study are not. To illustrate, consider what it means to trust your car navigation system. You might say that you trust your navigation system’s ability to recommend the best route during rush hour. However, when it comes down to it, you may opt to stay on your standard route. Your words express trust as an attitude, your actions express trust as an intention. While we can easily differentiate the expressions of trust in everyday life, overloading of the term ”trust” to mean both an attitude and an intention has led to a lack of precision and confusion in its formal study. We analyze the two papers most frequently cited by the community for their definitions of trust. One paper defines trust as an attitude (Lee and See, 2004), while the other defines trust as an intention (Mayer, Davis, & Schoorman, 1995). We develop a simple trust model that clearly articulates the relationship between these definitions. Simply put, trust as an attitude is weighed against perceived risk to determine trust as an intention. We also use the model to define appropriate trust in AI. A major goal of this work is to enable the design of trust experiments that manipulate and measure components of a shared model, allowing for comparison across research efforts and the building up of a consistent body of trust research. A practical implication of understanding trust is to strengthen the relationship between humans and technology.

Kyra Wisniewski, Christina Ting, Laura Matzen

Conference Proceedings

Examining the Role Memory Plays in Cyber Defence Evaluation: Risk and Uncertainty Demystified

Attackers’ decision-making processes can be influenced by their past hacking experiences, their knowledge of a target system, which is determined by the method/tool used to explore the system, and how important it is for them to remain undetected, among other factors. In this work, we utilized reinforcement learning (RL) agents equipped with/lack specific human-like capabilities to analyze how they interact with an environment characterized by (un)certain observation spaces. In particular, we investigated how agents with different memory systems and settings interact with reduced, masked, noisy, and baseline observations. First, to investigate whether the models are able to predict human-like tendencies, we analyzed the ability of non-linear models, calibrated to model different memory systems, and a linear model to predict actions taken by healthy humans and pathological gamblers (addicts) performing gambling tasks under incentive-compatible implicit and explicit learning schemes. Our findings show that a model’s ability to predict an individual’s tendency towards advantageous or disadvantageous actions is a function of the model’s characteristics, including the memory system(s) utilized in decision-making and its related attributes (e.g., impairments) and the condition(s) under which a decision is made (i.e., whether the decision is made under uncertainty or risk). Having examined the role memory systems and settings play in predicting real human behaviors using psychological datasets, we augmented RL agents with similar memory systems and settings to examine their influence on RL agents’ original behavior, that is of maximizing a net reward or satisficing a predefined condition. The analysis shows that equipping agents with different memory systems significantly and uniquely influences their approach to (un)certain observation spaces.Main findings:- In a simulated environment, knowledge of deception (or lack thereof) can be modeled in terms of the conditions (decision-under-uncertainty vs. decision-under-risk) under which the decision is made. We demonstrated that both conditions require further consideration when integrating cyber deception techniques into the environment and when evaluating agents using unique neural network architectures against defensive deception techniques. - Populations with distinct learning strategies require unique placement strategies since the thresholds of success may differ.- Strategies used to integrate deception into a network environment, which includes masking or reducing the observation space or adding noise to the observation space, vary in their effectiveness against the different types of agents.

Asmaa Aljohani, James Jones

Conference Proceedings

Human-centric Security Engineering: Towards a Research Agenda

While the importance of designing for user experience has long been acknowledged, there has been relatively little exploration of the actual processes involved in constructing usable and cybersecure systems. In many conventional projects, cybersecurity and usability are not considered primary goals, making them likely candidates for sacrifice in the rush to meet project deadlines. Unfortunately, designing systems with both cybersecurity and usability in mind is easier said than done and typically requires a change towards an organizational culture more conducive of human-centric designing. This position paper advocates for expanded research to explore the connection between culture and engineering practices, highlighting their impact on advancing a cyber-secure society. We explore ways in which the behavior of software development team members towards designing software and products that are both usable and cybersecure can be influenced through organizational culture. We conclude that initiating change within culture requires additional knowledge that future research must seek to provide. Three of these areas are discussed in the paper for immediate attention. The practical implication of this paper is that it encourages research in the field and provides some propositions to guide future empirical investigations.

Rick van der Kleij, Dianne Van Hemert, Bert Jan Te Paske, Thomas Rooijakkers

Conference Proceedings

Human-Centered approach in Design Curriculum Development

This paper details the inclusive efforts to revise a modern design curriculum, providing a comprehensive overview of the interdisciplinary and collaborative approach taken by design educators and administrators at a major university. The primary focus is on creating a curriculum that is accessible and relevant to students from diverse academic backgrounds, including those without prior design experience. The revision process was guided by an inclusive pedagogical framework that emphasizes three key design foundations: Intent and Opportunity, Ideation, and Implementation. Each foundation incorporates specific tools, methodologies, and design approaches aimed at fostering a holistic, user-centered, and interdisciplinary learning environment.The paper discusses the motivations behind the curriculum revision, highlighting the need to address the evolving demands of the design profession and the diverse interests of the student body. It outlines the steps taken to integrate non-design students into the design program, ensuring that the content is engaging and comprehensible to all participants, regardless of their previous exposure to design concepts. The paper also explores the challenges encountered during the revision process, such as balancing the needs of design and non-design students, aligning the curriculum with industry standards, and ensuring that the program remains flexible and adaptable to future changes in the field.

Scott Shim

Conference Proceedings

Using a model-based systems engineering framework for human-centric design

This research explores the integration of model-based systems engineering (MBSE) practices with human-centric design principles to enhance enterprise operations. The primary focus is on incorporating personnel data into digital SE environments to improve human resource management and project outcomes. Utilizing the Unified Architecture Framework (UAF), the study develops a model that captures the complex relationships between organizational structures, resources, and human factors. A production line system (PLS) serves as a case study to demonstrate how MBSE tools can simulate and optimize human interactions within the operational environment. Key findings include improved traceability of personnel competencies between individual persons and proper resource allocation based on capabilities. The research concludes with a recommendation further studies to include performance requirements, personnel and resource roadmaps, and the consideration of organizational and societal influences on employees.

Sarah Rudder

Conference Proceedings

Ming Dynasty Shipbuilding Technology from the Chronicle of Longjiang Shipyard

This study analyzes the shipbuilding techniques of gongjiang, the types of ships, and the materials, labor, and management systems used in their production, in order to clarify the institutional factors that influenced the development of shipbuilding technology in the Ming Dynasty in China. Research Perspective: This study examines the shipbuilding technology and management systems of the Ming Dynasty in China from the perspective of traditional Chinese design theory. Research Method: This study uses hermeneutics as the core method, combined with interdisciplinary research. Research Conclusion: "Longjiang Shipyard Records" provides a comprehensive perspective for studying the shipbuilding industry in the Ming Dynasty. Among them, the theoreticalization of shipbuilding technology and the systematization of the shipbuilding industry management system are the internal driving forces that promote the development of shipbuilding technology in the Ming Dynasty in China, and are the most intuitive manifestation of the technological development characteristics of gongjiang in the Ming Dynasty under the core ideas of Zhou Yi and Zhou Li .

Na Tian

Conference Proceedings

Interaction design of youth community in the context of service design

With the development of urbanization, more and more young people are pouring into first-tier cities, but the existing youth communities started late and are not perfect and cannot adapt well to the physical and mental demands of the current young groups. Therefore, starting from the Start with the concept transformation of youth apartments into youth communities, this paper studies the development and design of youth communities based on service design according to the needs and preferences of youth groups and combined with the challenges and opportunities of the development of the times, in order to improve the living conditions of urban youth groups. Through the investigation of the current working and living status of young people, the living needs of young residents are summarized by user interviews and questionnaires. Through the Kano model, the living, living, social, psychological and health needs of young people are prioritized, and the service blueprint is used to build a youth community service system. According to the living needs of urban youth, a community that meets the needs of urban youth is established. The Kano model can effectively analyze the functional demand priorities of community residents for the community. Combining offline and online scenarios, according to the service design concept, the design strategy analysis and design practice of the youth community system are completed, providing convenient, fast and comfortable community services for urban youth, and enhancing the happiness and sense of belonging of urban youth.

Li Jie Zeng, Xin Hu

Conference Proceedings

Inclusive Design of Smart Landscape in Community Parks for The Migrant Elderly

This study identifies the coexisting spaces of the migrant and local elderly in three community parks in Shanghai and achieves spatial inclusiveness grading based on the proportion of the migrant elderly in these spaces. By using the image recognition method in smart landscapes, landscape elements and spatial interfaces of the coexisting spaces were identified and analyzed, enabling more scientific and effective spatial characteristic analysis. Further analysis was conducted on the recreational behaviors of both types of elderly in spaces that exclude the migrant elderly and have relatively poor and poor inclusiveness levels, summarizing the inclusivity issues as: 1) landscape elements and spatial interfaces do not meet the recreational needs of the migrant elderly, 2) conflicts in recreational behavior between the migrant elderly and the local elderly, and 3) cultural inclusiveness issues. Targeted inclusive design approaches of the smart landscape were proposed, including the application of intelligent sensing technology, human-computer interaction technology, multidimensional experiences, and multimedia displays. This study provides new insights into spatial characteristic analysis through interdisciplinary methods. By analyzing the spatiotemporal distribution characteristics of both types of elderly, a new method for spatial inclusiveness grading is provided. By comparatively analyzing the recreational behaviors of both types of elderly and spatial characteristics, the inclusivity issues of spaces are examined. The research provides theoretical and practical references to meet the recreational needs of the migrant elderly, promote the construction of age-friendly community parks, and develop smart and inclusive designs.

Wenshu Sun, Yeshan Qiu, Bingqin Yu, Yun Wang

Conference Proceedings

Explainable AI Solutions for the U.S. Coast Guard Command Center: A Human-Centered Collaboration

With advances in artificial intelligence (AI) comes the responsibility to ensure that deployed AI solutions are ethical, useful, and safe. Explainable AI (XAI) has drawn increasing interest from the AI research community and seeks to provide understandable descriptions of how machine learning (ML) models generate their outputs. In short, XAI allows users to peek into the incredibly complex black boxes that most ML models have become. As successful adoption of new XAI tools necessitates designing “with,” and not just “for,” this paper explores the use of human-centered, participatory design in partnership with United States Coast Guard (USCG) command center watchstanders. Our process included traditional research methods such as interviews, observation, and contextual inquiry, as well as user experience (UX) workshop research methods such as experience mapping, post-ups, affinity diagramming, forced ranking prioritization exercises, and storyboarding. Our goals were to understand the unique problems and opportunities of the USCG’s Search and Rescue (SAR) mission, collaboratively generate desirable XAI solution ideas with command center watchstanders, elicit watchstander ideas and requirements for explainability features, and prototype our ideas to better meet real-world operational needs.

Audrey Haque, Anthony Lapadula, Jessamyn Liu, Sara Falkson, Karli Blanchard, Richard Coleman, Amna Greaves

Conference Proceedings

Hollywood Regency: American Design Under the Influence of Chinoiserie

Building on the historical development and design characteristics of Chinoiserie in America, this study examines history as a catalyst for design and investigates how design shapes society and culture. By constructing a historical narrative that links Europe with colonial and post-colonial America from both political and economic perspectives, the research elucidates the profound influence of Chinoiserie on the Hollywood Regency style. Europeans and Americans alike infused Chinoiserie with distinctive, dreamlike qualities, establishing it as a crucial source of inspiration for Hollywood Regency design.

Ellen Zhu

Conference Proceedings

Comparative Study of Signage Design in Inclusive Playgrounds and Public Parks Guidelines

With the opening of Japan’s first inclusive playground in 2020, playgrounds within Japanese parks are progressively moving towards inclusivity. Signage, serving as a vital link between parks and playgrounds, as well as within recreational facilities of the playgrounds, plays a crucial role in guiding people’s path-finding behavior. However, current research on signage design systems within inclusive playgrounds remains insufficient. This study aims to comprehensively understand the design points of signage in inclusive playgrounds by analyzing the instructions for signage design in the inclusive playground guidelines and park construction guidelines in Japan. The goal is to extract the key elements of signage design to facilitate ongoing improvement and enhancement of signage design within inclusive playgrounds, thereby promoting a more inclusive play environment.

Jia Wang, Yasuyuki Hirai, Melanie Sarantou, Yunkyu Lee

Conference Proceedings

Impact of Audience Presence on Pressure and Running Performance: The Potential of AR Presence

This study investigated the impact of audience presence on the experience of running on a treadmill by specifically examining perceived pressure, calorie expenditure, and heart rate. The primary objective was to understand how various types of audiences—live audience, video call, augmented reality (AR) characters, and no audience—affect runners' performance and psychological states. By exploring these scenarios, this study identified the role of audience presence in influencing exercise outcomes. The significance of this study lies in its potential to enhance exercise interventions and promote long-term commitment to physical activity. By leveraging AR technology, our results may contribute toward managing pressure and improving performance by offering innovative solutions to support both physical and mental well-being in the exercise context.

Ziting Gong, Hideaki Kanai

Conference Proceedings

Exploring the Path of City Image Communication through IP Image Design: A Comparative Study of China and Japan

In the traditional media era, city images were primarily constructed by government departments. However, in the new media era, city images are mainly built by the public through online channels, with IP images being an important carrier for promoting city images. This paper examines the cases of Kumamon in Kumamoto Prefecture, Japan, and the giant panda Hua Hua in Sichuan, China, to explore the experiences and shortcomings of using IP images to assist in city image communication in different countries. It aims to construct a design system for IP images suitable for Chinese cities from aspects such as establishing the image, endowing it with vitality, artistic construction, and long-term assurance. The study finds that integrating regional history and culture into IP image design can optimize city images, enhance cultural added value, and open new avenues for city cultural communication, thereby promoting sustainable economic development. This research provides new ideas and practical guidance for innovative urban cultural communication strategies.

Yuexi Qiao

Conference Proceedings

Design of a Smart Interactive System for Pet Dogs from the Context-Aware Perspective

With the constant advancement of technology and social development, the demands for pet dog care have been growing significantly, leading to a pressing need for intelligent and personalized solutions. This article aims to explore a smart proactive interaction system that integrates context-aware theory, designed specifically to meet the daily care needs of pet dogs.At the outset of the research, an exhaustive literature review was conducted to establish a clear understanding of the fundamental concepts and design principles of context-awareness. Subsequently, through in-depth social background research and user interviews, a user journey map was constructed, providing a comprehensive analysis of the daily routines and health requirements of pet dogs. These analyses offered valuable insights into the habits and preferences of both the pets and their owners.Based on these insights, an intelligent system grounded in context-aware principles was developed. This system possesses the capability to monitor the physiological state, behavior patterns, and location information of pet dogs in real-time, while actively offering interactive functional services tailored to the pet's specific needs. Additionally, a complementary application was designed for pet owners, providing precise health monitoring reports, behavioral analysis, and location tracking services. This comprehensive approach ensures that pet owners remain informed about their pet's well-being, while fostering deeper emotional bonds between the pet and its owner.The integration of various interactive features within the system facilitates seamless communication between pets and their owners, promoting not only the physical and mental health of the pets but also enhancing the emotional connection with their owners. This research provides a novel perspective for the design of smart service interaction systems for pet dogs, and serves as a practical reference for the application of context-aware technology in intelligent service systems. It opens up new horizons for future pet care solutions, paving the way for more intuitive and compassionate approaches to pet care.

Xuan Ding, Xin Hu

Conference Proceedings

Public Perception of Built Environment in Urban Street: A Text Emotion Analysis Approach

Liveability can be measured by various factors that matter for quality of life, but people’s perception and feelings toward the city, especially the built environment, is considered fundamental to the evaluation of urban liveability. Most previous studies described liveability-oriented urban built environments as spaciousness, bright and convenient with objective indicators, but attributes such as pleasant and comfortable are difficult to assess objectively. Traditional methods such as questionnaire surveys or interviews are likely to produce bias with small sample size or are time consuming if collecting large sample of data. Development of big data and machine learning approach makes it possible to evaluate people’s subjective perceptions toward the built environment. Exploring an urban street area in Shanghai, this research applies a Chinese natural language processing (NLP) tool to the text database and assesses the public perception toward built environment through a 0-1 score system. NLP is a machine learning technology that enables computers to interpret, manipulate and comprehend human language. The result indicates that the NLP emotion analysis is able to quantify people’s perceptions toward built environment and reveals the extent of the perceptions, which would significantly aid human-centred design of urban built environment.

Lingyue Li, Lie Wang, Yiwen Chen

Conference Proceedings

Meta-picture and Chindōgu: Design Explorations to Inspire the Visual Experience

This experimental artwork is divided into a physical installation part and a virtual part. The physical installation is a camera recording the way people use the Tap-Hat, while the virtual part is an invitation for more viewers to participate. The image of the work is created by nesting and superimposing the tap and the hat, and is expressed in the form of a chindōgu, paying homage to the classic meta-picture Duck-Rabbit (Fliegende Blätter 1892). The self-referentiality of the picture is an integral part of Duck-Rabbit, and in 2024 we found this perspective still compelling.In addition to exploring the relationship between the image and the physical object, we believe that this work is also relevant to human society. As Kenji Kawakami, the inventor of the Chindōgu described in his 101 unuseless Japanese Inventions, "Digital products are indeed very advanced, but they also alienate people while facilitate people’s daily life, and deprive them of the freedom. And freedom is the most important thing in life."We wish to explore a form of art where "creation" and "experience" work together in freedom. In the invitation to experience, we expect people to temporarily leave entrenched cognition and purpose behind, and to discuss values and meanings that go beyond monetary figures.

Jing Zhang, Qixin Chen, Liangliang Qiang

Conference Proceedings

My tool my rule:User-Participatory Design of an Angle Grinder

As a tool primarily designed for grinding, angle grinders are extensively used by workers in processing and maintenance tasks. However, using angle grinders for cutting purposes is not compliant with safety regulations, yet this practice is widespread. This misuse imposes significant wrist strain and safety hazards on workers. Existing tool designs often prioritize technology or market demands, frequently neglecting workers' needs and considerations for ergonomics and user experience.This study conducted multiple rounds of experiments and collaborated with users to advance a design plan for an angle grinder. We interviewed angle grinder users from various professions and observed their work processes, discovering numerous ergonomic issues in the actual use of angle grinders. Based on the forces exerted during operation, we proposed three new gripping methods to make the angle grinder suitable for both cutting and grinding. These methods were tested with users, leading to the creation of more detailed models to refine the mode-switching mechanism. This iterative process incorporated new user feedback into the design and resulted in the production of a prototype. The prototype was provided to 12 users for evaluation, and the scale results showed that the angle grinder designed with user participation significantly enhanced the user experience compared to traditional angle grinders.Based on this case, we developed a user-centric tool design methodology. This method begins with observing and interviewing users to extract their needs, followed by initial modifications to existing tools and seeking user feedback. The next steps involve integrating this feedback into design and structural development, conducting multiple rounds of discussions with users to adjust the design, and finally inviting users to evaluate the design outcome. Implementing this method requires detailed communication, extensive real-world experiments, and rigorous evaluation and collaborative decision-making. This approach finds a balance between practical conditions and users' ideal usage patterns, leading to more ergonomic design results. It enhances the user experience while providing new insights for designers and engineers.This user-centric design methodology emphasizes deep user involvement throughout the design process. By bridging the gap between actual working conditions and users' needs, it offers a new perspective on tool design that prioritizes ergonomics and user satisfaction. This method can lead to innovative solutions that improve the usability and safety of tools, ultimately benefiting both workers and the design community.

Yiwei Zhao, Mengshi Yang, Ruchen Hu

Conference Proceedings

Color Impressions in Images of Decorated Interiors and Furniture Are Influenced by Differences in Color Vision

The objective of this study is to investigate how impressions derived from multiple colors differ depending on the diversity of color vision. We have already conducted research on color impressions using abstract images as visual stimuli containing multiple colors. In this report, we will conduct a similar study using images of decorated interiors and furniture, which include more familiar subjects. Globally, 2% to 10% of men have color vision deficiencies (protan or deutan color vision), and many studies have been conducted to consider color　discrimination. However, there are few comprehensive survey results on how people with color vision deficiencies perceive various color impressions. In the study on color impressions perceived from single colors by Ichihara (2018, 2019), it was reported that people with protan or deutan color vision perceive colors like red and green as dark, sober, and dull, whereas colors like blue, purple, yellow, orange, and yellow-green are perceived as bright, flashy, and lively. Furthermore, in the study by Sakamoto et al. (2019) focusing on abstract images containing multiple colors, it was reported that the structure of color impression evaluation could be explained by three factors, including a factor related to "harmony." In this experiment, we targeted individuals with normal color vision (both male and female) and those with dichromatic color vision deficiency (both protanopia and deuteranopia). The experiment was conducted from January 10, 2024, to April 20, 2024. Images of decorated interiors and furniture with various color combinations were displayed on an LCD monitor (EIZO CG279X) connected to a MacBook Pro. We calibrated the color and brightness of the EIZO LCD monitor using color management software (EIZO ColorNavigator 7). We collected color impression data using the Semantic Differential (SD) method. Subsequently, we employed Principal component analysis to investigate which principal components significantly influenced judgments across different types of color vision. The results of the Principal component analysis extracted four principal components for each type of color vision. Specifically, these principal components are Activity (associated with liveliness and flashiness), Harmony (associated with beauty and elegance), Potency (associated with weight and strength), and Sharpness (associated with the sharpness of color combinations). It was suggested that color vision differences (normal color vision, protanopia, and deuteranopia) affect the evaluation of Harmony differently. Our results also suggest that when impressions of highly salient colors in interior design are similar across different types of color vision, the design tends to evoke the same impression. On the other hand, when impressions of highly salient colors differ across different types of color vision, the design tends to evoke different impressions.

Atsushi Kido, Toshikazu Kato, Takashi Sakamoto

Conference Proceedings

Circular materials for Eco-Craftsmanship - Development of a Wool-based Biocomposite for 3D printing of Abruzzo region craft products

The Abruzzo region, in Italy, has a strong artisan tradition. Among the many artisan sectors is also the textile artisan, present in many towns in the area, which uses sheep's wool as a raw material. However, artisan workshops (goldsmiths, ceramists, leather workers, embroiderers, etc.) tend to disappear due to insufficient generational turnover, as young people are interested in more innovative activities. This also results in the loss of cultural identity and the abandonment of internal territories, with serious damage to local socio-economic systems. Furthermore, some artisan productions are unsustainable from an environmental point of view, especially assuming an extension of production to optimize economies of scale. Wool mills, for example, in their textile production, produce large quantities of waste in terms of wool dust and threads, "waste" that cannot be easily recycled.Innovating in the artisan sectors, even the most traditional ones, through the use of digital technologies and 3D printing, could represent an excellent incentive to bring young people closer to ancient professions, thus encouraging a generational change and the creation of new job opportunities. The digitalization of some productions, moreover, associated with the recovery of some waste materials, would also positively interpret some of the UN 2030 objectives.This paper reports the results of a research aimed at reusing production waste from wool fabrics and filaments to generate a new, ecological and circular composite material. The new material involves the use of a bioplastic matrix, PLA (polylactic acid), loaded with wool filaments, to obtain a fiber-reinforced biocomposite printable with 3D digital printing technologies. This new material, based on the use of a typically local material, can be used to create artisanal products that recall some traditional Abruzzo productions, effectively complementing more conventional craftsmanship.

Stefania Camplone, Giuseppe Di Bucchianico, Gabriella Petrucci

Conference Proceedings

Adaptive fashion experience - A methodological approach for inclusive outerwear dressing

Today, the extended, hybrid, phygital reality builds new relationships between actors in the fashion industry supply chain and highlights the need to design products and services capable of interpreting the needs associated with physical and virtual interactions with the garment product. The paper proposes some outcomes of the ‘Moda 4.0’ project, mainly aimed at supporting fashion-clothing companies in the digital transition with a sustainable approach to products and processes. In this context, attention has been paid to the issue of the inclusiveness and adaptability of the outerwear, outlining here the opportunities offered by digital in the development of the adaptive design. The paper is structured in a first analytical part, which defines the scenario and identifies the general objectives of the project; a second experimental part, in which the results of the design experimentation of an adaptive outerwear and the wearing experience of a user with reduced mobility are presented.

Alessandra Scarcelli, Annalisa Di Roma

Conference Proceedings

Guidelines for the design of Digital Platforms for wellness and inclusion: Shaping future community of citizens

The primary objective of the presented research is to explore and outline the possibilities offered by digital platforms in the urban context of the future, enabling the the well-being and care of individuals and communities, asserting that in a fragmented social context, the development of aggregation services and reconfiguration of social networks is crucial to respond to pluralisation and changing needs (Kazepov & Barberis, 2013; Kazepov & Cefalo, 2009). The research is part of the project, funded under XX, which aims to design 'platforms of care' to improve the holistic well-being of citizens in their territorial and cultural context. The first phase of the research concerns the study of the city from a multidisciplinary point of view, integrating theoretical and practical methods from the technical disciplines of design and architecture with those provided by humanistic and social fields, such as socio-semiotics, cultural studies, and urban sociology. The research investigates the intrinsic correlation between digital transformation and progress in the broad context of citizen care and welfare, with a focus in the welfare sector, aimed at promoting economic, environmental and social sustainability while improving responsiveness to emerging social challenges and needs. Digital services can offer support for new services by encouraging and facilitating proximity interactions for better living in today's hybrid physical and digital space (Pais, 2021). In this regard, the paper presents the outcomes of the initial phase of the research, about the analysis of existing digital platforms for the organisation and provision of holistic care services in the Italian national context, promoted by public administrations (PA) and the third sector. In particular, the case studies considered concern the welfare platforms active in Italian cities, covering sectors such as social welfare, education, care, and physical well-being. Strengths and critical points are critically highlighted, particularly with respect to the relationship with citizens and the territorial and cultural context of reference. The robust interconnection between "care" practices and the structure of the city, typical of pre-modern urban contexts, has been gradually replaced by the evolution of increasingly functional and specialised proximity relations in contemporary cities as a result of digital evolution, pushing towards cities of distance, inherently devoid of care. Proximity, understood in the condition of being physically close in space, but also in the feeling arising from the awareness of sharing something with someone (Manzini, 2021) is here understood as a source of care; an ecosystem of people, organisations, places, products and services that collectively demonstrate a mutual capacity for care and wellbeing. The very concept of care emphasises the importance of contact and thus proximity, recognising how holistic care requires close interaction between the actors involved (Manzini, 2021). The physical-digital hybridisation of proximity is intertwined with the analogous hybridisation of care, making tangible the need to redesign care systems to support new communities and forms of proximity, inclusive and capillary over the territory, considering the city of proximity as a common good. The city of proximity becomes a social and material resource of all its citizens, who contribute to its production, and of which they must have the burden Moreover, today the outcomes of digitisation also involve welfare, requiring the transformation of services such as education, health, welfare and social protection services. The welfare of the future requires physical and non-physical places where people can overcome the barriers of sociability, creating the basis for a new community-type cohesion: the ability to establish proximity relations is closely linked to the long-range relations of community welfare. This gives rise to the phenomenon of welfare platforms, based on the principle of several people providing collaborative responses to needs, actively involving social actors and creating interactions, thus strengthening community resources (Arcidiacono et al., 2021; Fosti, 2013, 2016). The platform, in this context, acts as the main infrastructure linking the demand and supply of goods and services through their reorganisation. The methodological approach of the research considers human-centred design, declined with respect to the emerging phenomenon of digitization. The outcomes of the ongoing research presented consist in mapping the reference city context, the city of XX, its significant places, as well as the characteristics, habits and cultures of its citizens. The sociological analysis will support the technical analysis in the field by means of qualitative survey tools in order to outline realistic scenarios as a basis for the design of 'digital platforms of care and well-being'.

Annalisa Di Roma, Giulia Annalinda Neglia, Alessandra Scarcelli

Conference Proceedings

Artifacts as a means to investigate alternate and future realities

As design evolves and moves from the creation of physical objects to the creation of services, the methods and approach to prototyping have undergone a radical transformation, fundamentally altering the design process. Where once conceptual objects signaled the designer's view of the future, and sparked conversations about potential future realities; today, wireframes and frameworks are often used for targeted the refinement of specific interventions. As designers seek to shift the design process towards more participatory methods (Srikanth 2023), methods that involve all stakeholders in the design process, perhaps there is a new space for artifacts to be reintegrated into the design process, in a way that would facilitate new kinds of interactions, interventions, and discourse. From the use of actual and situated artifacts for critical inquiry, to speculative objects that allow for descriptions of, and interactions with, possible future worlds, physical objects can be a valuable tool in participatory design. Such artifacts can serve as boundary objects between communities and between disciplines as the design process becomes increasingly interdisciplinary. Furthermore, they can facilitate a deeper understanding of the value systems of different communities, as studying their interactions with objects allows us to decenter the human user in the design process and better understand how non-human objects fit into the larger systems they inhabit.This paper compares and contrasts speculative objects with material speculation. It examines the evolution of these two concepts, the key differences between them, and their potential applications in the context of participatory design. It also compares them to boundary objects and to the conceptual prototyping methods of the past, and examines how these types of objects and prototyping techniques have been used in different eras and their wide-ranging influence on different industries.

Nishanth Srikanth

Conference Proceedings

Design Maturity Frameworks and Enjoyable Design Processes

Maturity frameworks provide a structure for assessing key performance metrics of an organization and provide guidelines for assessment and growth in various areas of an organization.Design maturity frameworks focus more on a human-centered approach in assessing the human motivational factors that create enjoyable and sustainable workplace practices. Identifying factors that improve or inhibit the productivity of processes can help individuals and organizations design better workplace experiences. This presentation will introduce audience to the theoretical foundations of design maturity frameworks and suggest ways to build a human-centered model that is built around enjoyable and sustainable design processes, customized for individual and organizational growth. Participants will learn • Concepts of maturity frameworks and stages of design expertise • Identify issues with existing design processes at an individual and/or organizational level • Discuss practical solutions and develop a customized maturity framework for enjoyable and sustainable workplace experiencesThe session aims at identifying human factors that motivate individuals and organizations in developing design processes that generate enjoyable and sustainable workplace experiences. The content of the session will benefit novice to experienced professionals and managers to rethink their own professional practices in terms of design expertise development and motivational processes at workplace.Session Structure: • This session will include both presentations and practical work • The presentations introduce concepts of design maturity and expertise development in professional practices • Presentations will be followed by individual exercises and group discussions to identify motivational factors and productivity inhibiting factors at workplaceTarget Audience: The session is designed for novice to experienced professionals in the academic and professional fields who are interested in learning more about design maturity frameworks and guidelines to apply these structures in their professional practices. The presentation provides guidelines to adopt design practices and human-centered processes at individual and organizational levels. Target audience roles include: Designers, Managers, Developers, Researchers, Educators

Nandhini Giri, Erik Stolterman

Conference Proceedings

Emotion Regulation Strategies and the Innovative Design of AIGC Interactive Healing Images

The study explores a new approach to Artificial Intelligence Generated Content (AIGC) in interactive healing image design based on Gross's emotion regulation theory. By deeply analyzing the emotion regulation theory, this study proposes for the first time an innovative design framework that integrates emotion recognition, real-time adjustment and content generation. The framework focuses on the automated recognition and classification of emotions, the adjustment of real-time emotion regulation strategies, and the generation of personalized content, aiming to enhance the user's healing interactive experience.This paper provides new ideas and guidance for the application of AIGC technology in the field of interactive healing images, which has important theoretical and practical implications. Future research can further explore the practical application effects of these design principles and technical strategies.

Xingyi Wen, Jianmin Wang, Yu Shu, Xi Ji

Conference Proceedings

Interdisciplinary Application of Fractal Algorithm-Based Zodiac Symbol Graphic Design in Product Packaging

With the widespread dissemination of Western astrological culture among the younger generation, its unique popular cultural characteristics have deeply penetrated public life, leading to the formation of a design and production market themed around astrology. Against this backdrop, design works increasingly utilize fractal graphics and computer algorithms to optimize visual effects and aesthetic features, thereby showcasing the diversity of design and providing practical application value. This study aims to explore the application of fractal algorithms in astrological symbol graphic design and further apply it to the field of product packaging design. Through various research methods such as literature review, expert interviews, questionnaire surveys, and experimental analysis, this study conducts an in-depth analysis of visual aesthetic elements in design and combines them with fractal patterns to achieve innovative design effects. The study employs the fuzzy analytic hierarchy process to meticulously analyze primary evaluation factors such as visual aesthetic elements, graphic design aesthetic elements, textual design elements, and color design elements, as well as their secondary weight factors. Based on the analysis results of the importance of design elements, sample designs are created using existing fractal pattern materials. The outcomes of this study not only provide new design ideas for the product packaging of astrological symbol graphic design but also offer valuable references for interdisciplinary research in design studies and related disciplines, further promoting the market value and cultural dissemination of astrological symbol graphic design products among young people.

Shengdong Zhou, Eakachat Joneurairatana, Veerawat Sirvesmas, Yan Wang

Conference Proceedings

The Relationship Between Aesthetic Evaluation of Product Design and Purchase Intention in 100-Yen Shops– Focusing on Uniqueness, Humor, and Unexpected –

In recent years, various types of retail shops have appeared in Japan. The popularity of 100-yen shops can be attributed to the low price of 100 yen per item and the high quality of their products, which have won awards for design from Japanese organizations. The gap between "Low Price and High Quality" and "High Quality" is judged to be surprising to consumers. Thus, 100-yen shops are famous for their affordable prices and high functionality. On the other hand, there have been no cases where the relationship between the sensitivity evaluation of 100-yen shop products and willingness to purchase has been analyzed. Therefore, this study aims to visualize and investigate the relationship between consumers' assessment of the uniqueness, humor, and unexpectedness of 100-yen shop products and their willingness to purchase them. Seven participants visited three different 100-yen shops in Hakodate in evaluation experiment 1. The collaborators were asked to photograph each "Unique and Humorous" and "Unexpected" product and describe their reasons for choosing. Then, 281 participants in their 20s to 70s were asked to complete a questionnaire about the 100-yen shop. Then, as part of Evaluation Experiment 2, we investigated how they would evaluate the products using the pictures taken in evaluation experiment 1. The results showed that more than half of the consumers plan what they will buy before they go to a 100-yen shop, but they tend to make impulse purchases due to low prices or buy unexpected items to stock up on consumable items. Moreover, "Unique and Humorous" was strongly related to "Unexpected." On the other hand, "Unique and Humorous" did not lead to "Want to Buy".

Mikako Tsurugasaki, Namgyu Kang

Conference Proceedings

Harmonizing User-Centered Design and Operational Efficiency in Battery Electric Vehicles: Navigating the Electric Dilemma for Sustainable Mobility

As battery electric vehicles (BEVs) become more prevalent in the automotive industry, the interplay between user-centered design and usability takes center stage. This study addresses the complex dynamics of this paradigm and sheds light on the intricate trade-offs between user satisfaction and functional effectiveness to determine the optimal balance for a satisfying and sustainable user experience (UX). Therefore, an innovative approach is presented that enables optimized energy management, thereby increasing comfort and improving the UX. As technological innovations drive the capabilities of BEVs, the confluence of user expectations and operational efficiency presents a fundamental challenge. The pursuit of greater range combined with seamless usability underscores the need for a holistic human-centered design approach. In addition, the growing number of user-centric features (e.g., comfort features) introduces a new dimension to the equation, reinforcing the importance of human-centered design principles. Against this backdrop, external factors such as environmental conditions and user behavior exert a profound influence on the performance and usability of BEVs. The intricate interplay of these variables requires a nuanced understanding of user preferences and technological advances to strike a delicate balance. In response to these challenges, this research proposes an innovative framework to improve the UX of BEVs while maximizing energy efficiency in different operating scenarios and optimizing comfort features. By leveraging insights from user-centered design principles and advanced energy management strategies, this framework aims to optimize the driving experience while minimizing energy consumption. The electric dilemma highlighted in this study - increasing energy efficiency and driving range on the one hand and increasing comfort, optimized UX and human-center design on the other - which is particularly relevant for BEVs, illustrates the complicated interplay between user satisfaction and efficiency. Achieving a harmonious balance requires a multi-faceted approach that integrates user insights, technological advances and environmental considerations. The results emerging from the research offer actionable insights to guide the development of BEVs and provide manufacturers with a roadmap to tackle the electric dilemma and deliver UX that seamlessly combine comfort and efficiency. By embracing a human-centered design ethos, vehicle manufacturers can cultivate a symbiotic relationship between user satisfaction and efficiency, promoting a sustainable future for BEVs.

Alexander Kreis, Mario Hirz, Christoph Stocker

Conference Proceedings

Human-centred design in AI era: Inclusive AI assistance for visually impaired persons in recycling practice

More science and social researchers have advocated to use the high-tech to support the persons with special needs. Since the early 2010s, the design research team of the Public Design Lab has put effort to conduct in-depth qualitative studies on the needs of visually impaired persons (VIPs) in their daily lives. The team has worked with VIPs to propose some “creative” ideas to support their needs. Moreover, by exploring the recent front-end technological advancements, the team has advocated possibilities of AI technology to be included in the “design” of daily objectives for VIPs. By using persona method and case study, the team facilitate the VIPs to propose a model which is based on the current known AI technology to assist them to carry out the recycling practice independently. The model is expected to be possible to be applied in other daily needs of VIPs as well as other persons with special needs.

Kin Wai Michael Siu, Xinzhe Zhao, Jiayi Zou, Yijia Jiang, Maoen He, Keren Zhang, Qian Jiang, Jiaman Li

Conference Proceedings

A Lexical Analysis of online Reviews on Human-AI Interactions

The literature review delves into the complex dynamics of human-AI interaction, emphasizing its pivotal role in integrating artificial intelligence (AI) tools successfully. User perceptions of AI, highlighted by Neyazi (2023) and Cinalioglu et al. (2023), significantly influence acceptance and adoption. Trust formation, particularly crucial in domains like healthcare (Davenport & Kalakota, 2019; Wong et al., 2023), underpins widespread AI use. Ethical considerations, including bias and data privacy, demand careful attention (Mittelstadt, 2019; Huriye, 2023). Societal impacts, such as autonomy and collaboration, gain importance (Sankaran et al., 2021; Mirbabaie et al., 2021). In healthcare, addressing concerns is vital for positive outcomes (Esmaeilzadeh et al., 2021; Esmaeilzadeh, 2020), alongside factors like usability (Asan & Choudhury, 2021; Choudhury, 2022). Perceptions of AI risk and trust are influenced by human-likeness (Wong et al., 2023). Understanding user experiences improves outcomes (Rezwana & Maher, 2022; Rezwana, 2022). Despite advancements, understanding user challenges with AI remains incomplete. The review suggests analyzing AI software reviews to identify concerns, aiming to fill this gap and enhance understanding of human-AI interaction's challenges. Through this approach, the research seeks to contribute to the broader discourse on human-AI interaction.The research methodology involves several key steps. Firstly, a comprehensive dataset comprising 55,968 online reviews on AI usage is collected from three prominent websites: G2.com, producthunt.com, and trustpilot.com. These websites are well-established platforms for business software reviews, providing valuable insights into professional AI tool use through user reviews. The collected data is then subjected to rigorous data cleansing procedures using the NLTK library and WordNet Dictionary. This includes removing stop words, extracting adjectives and nouns, combining synonyms and antonyms, and lemmatization, to ensure the quality and consistency of the dataset. A matrix of nouns and adjectives in column and review text created. A weight assigned to each column based on its presence in the reviews (1 if it exists, 0 if not). Subsequently, Exploratory factor analysis is employed to analyze the collected adjectives and nouns and find correlations between words, aiming to identify underlying patterns and group similar traits together. This statistical technique provides valuable insights into the key factors influencing human-AI interaction dynamics, shedding light on the nuanced aspects of this complex relationship.The results obtained from the factor analysis will be further analyzed through content analysis to gain a deeper understanding of the identified factors and their implications for human-AI interaction. Currently, the study is focused on completing the factor analysis, with content analysis planned as the next step in the research process. The findings are expected to provide valuable insights into the critical factors shaping human-AI interaction, contributing to the advancement of our understanding in this domain. This research not only informs future developments in AI technology and user experience but also contributes to ongoing efforts aimed at enhancing human-AI interaction. By adopting the lexical approach and leveraging insights from online reviews, this study aims to bridge the gap between theory and practice in the field of human-AI interaction, paving the way for more user-centric AI systems in the future.

Parisa Arbab, Xiaowen Fang

Conference Proceedings

Multi-Dimensional Nature of Human-Centered Design: an Autoethnographic Analysis of the Seiko Bell-Matic Wristwatch Using Information-Theoretic Methodologies

Human-Centered Design (HCD) emphasizes empathy to understand users' needs, yet the complexity of these needs makes HCD an evolving and open-ended objective. This paper uses Seiko’s Bell-Matic wristwatch as an autoethnographic case study to explore discrepancies between the intended design and dynamic user needs. Applying the Networked Two-way Communication Channels (NTCC) model reveals new insights into the interaction dynamics of the Bell-Matic's unique mechanical alarm feature. This study proposes a novel approach to modeling UI interactions as multi-dimensional communication processes, enabling comparisons between system functionality and user needs. Ultimately, the paper reinterprets HCD by evaluating the alignment of functional entropies between systems and users.

Lance Chong

Conference Proceedings

On the practical utility and practical path of fashion model emotional memory method in performance

From the beginning of the 14th century, to the vigorous development of the 19th century, the form of costume performance art has become more and more perfect. With the progress of society and the improvement of aesthetic concepts, the audience's expectation of fashion shows is no longer limited to the external beauty of models, but more eager to see the emotional resonance and the true representation of life. From the viewpoint of psychology and the theory of fashion performance, this paper analyzes the basic composition of model performance, then introduces the concept of emotional memory into the field of fashion performance, and explores the advantages of empathy, authenticity and life as the three characteristics of real model performance. An in-depth analysis of the effect of models' emotional memory expression on fashion shows shows that models' plump perception will fill the performance details and work together with external body expression in the performance art of clothing to achieve the best artistic effect. To complete emotional memory performance, models also need to implement the concept of life aesthetics and experience aesthetics in daily training, attach importance to indirect experience, and pay close attention to technical assistance and technology empowerment.

Jianhong Wu, Xiaomei Chen

Conference Proceedings

Unconscious Design Method of Haipai Cultural Tourism Souvenirs Based on Extensional Narrative Theory

Haipai culture is unique to Shanghai and holds significant cultural value. Tourism souvenirs,as a key value-added industry in tourism, naturally serve as carriers for conveying local cultural essence and play a crucial role in promoting and disseminating Haipai culture. To address the current issues of severe homogenization, lack of depth, and insufficient emotional resonance in Shanghai tourism souvenirs, this paper explores an unconscious design approach for these souvenirs based on Extenics and narrative theory. Firstly, the KANO model is utilized to filter and categorize target user needs, obtaining their priority. Secondly, a cultural and creative product narrative design model constructed using Extenics innovation methods is employed to diagram the narrative framework of Haipai culture.Finally, through three unconscious design pathways, the narrative elements of Haipai culture and the user needs for tourism souvenirs are linked, resulting in the formulation of design strategies for Shanghai tourism souvenirs.The site of the First National Congress of the CPC, a landmark in Haipai culture, is used to validate the feasibility and rationality of these design strategies through the reproduction of its related elements in tourism souvenir design practice. This method provides a feasible path for both the internal excavation and external manifestation of Haipai cultural connotations and offers new ideas for showcasing Chinese cultural characteristics in the field of tourism souvenir design in the future.

Ye Junnan, Saiya Wang, Yue Wu, Haoyue Liang

Conference Proceedings

Creating emotionally resonant User Experiences in response to ever-evolving challenges in Open Distance e-Learning Institutions.

Advances in ever-present, social, mobile, and physical computing technologies have moved the field of Human Computer Interaction (HCI), particularly User Experience (UX), into practically all areas of human activity, including education. Higher education institutions (HEIs) face a growing need to enhance online learning opportunities that address an increasingly diverse learner community. This underscores the necessity of UX communities to propose that the development and evaluation of digital technology should not only include usability, but the broader range of user experiences, where users’ feelings, motivations, and values are given as much, if not more, attention than efficiency, effectiveness, and basic subjective satisfaction experiences which it offers. Emotion and the expression of emotion play a powerful role in the way human social interaction is shaped, and therefore can and must be exploited in HCI. An emotion lexicon is essential for describing emotions and emotion-aware experiences, facilitating the identification of emotions, and describing subsequent behavioural patterns which highlights the importance of a match between an emotion experienced, experience design and design principles. To explore the role of emotion and the possibilities it has for technology interaction, a non-formal learning initiative was implemented in an Open Distance e-Learning (ODeL) environment using a freely available social media app exploiting its capacity for inclusiveness and educational potential. Using phenomenology as a research philosophy and a methodology, emotions were identified and mapped to behavioural patterns resulting in design principles. This allowed for the creation of emotion-aware experiences and a more comprehensive understanding of mobile tutoring in a ODeL environment.

Petra Le Roux, Corne Van Staden

Conference Proceedings

Participant Experience Evaluation in Digital Rural Poetry Activities: A Sentiment Analysis Case Study of Mingyue Village in China

In the era of digital intelligence, integrating digital technologies and social media has revitalized cultural activities in rural communities, attracting the attention of many visitors. Utilizing Mingyue Village in China as a case study, this research explores how poetry creation and dissemination have become new pathways for preserving rural cultural heritage, allowing participants to share and experience poetry creation in both physical and virtual spaces. The study aims to assess the emotional expressions of residents in digital poetry activities. Based on anthropological fieldwork, it employs SVM (Support Vector Machine) with SMOTE (Synthetic Minority Oversampling Technique) to analyze poetry text data, delving into participants' emotional interests and inclinations. The results show that digital poetry activities not only enhance rural residents' sense of place and community cohesion but also promote the expression of positive emotions. The study concludes that digital poetry activities are an inevitable outcome of technological advancement while responding to human emotional and cultural needs. Future research will focus on optimizing sentiment analysis techniques, expanding sample sizes, and integrating tourism and cultural activities to promote rural community development and cultural heritage preservation.

Jiaman Li, Kin Wai Michael Siu

Conference Proceedings

Flexible and inclusive housing: adaptation to the changing needs of inhabitants

The ONU Convention on the Rights of Persons with Disabilities specifies that the built environment must adapt to human needs and not vice versa. This applies to everyone: the quality of life also depends on the quality of living, on the responsiveness of the living space to the needs of the person. The user—the inhabitant—is placed at the center of the project, and the house changes according to the changing needs of the users.Limiting the field to different residential forms, home environments must be designed and built flexibly so that they can be easily adapted to housing needs, which are never static but can also change substantially for a lifetime due to various factors, such as aging, illness, disability, or changes in family structure.Housing flexibility is based on two basic principles: adaptability and accessibility. Adaptability implies the ability to change interior spaces quickly and inexpensively, while accessibility refers to the possibility for all people, regardless of physical, perceptual, cognitive, cultural, etc. conditions, not only to use the dwelling without barriers but to live their home life under the best conditions.One of the issues related to changing housing needs over time is the aging of the population, which brings with it not only problems of mobility and fatigue but often also disability and loneliness. Older people require more accessible and safe home spaces and services to encourage socialization and maintain an active life. Elements such as handrails, ramps, stair elevators, and adapted bathrooms can make a big difference in the quality of life for older people. Flexible homes often incorporate these elements early in the design phase, enabling more comfortable aging in one's own home. Technology can be an indispensable support in facilitating home life for more than just older people: home automation systems, and smart home solutions make it possible to control the home environment and adapt it to different needs simply and inclusively, facilitating use by people with physical disabilities or motor limitations.Illnesses and disabilities can also affect housing needs. A flexible home might include spaces that can be easily modified to allow the installation of medical devices, such as hospital beds, lifts, or home therapy equipment. In addition, larger spaces may be needed to allow for wheelchairs or other mobility aids. The goal is to ensure that residents can receive care and assistance at home without moving to healthcare facilities. Special housing needs may also be generated by special conditions of a growing segment of the population affected by, for example, the autism spectrum. In this case, accessibility becomes more complex, requiring special attention and dedicated solutions, which are possible only from a thorough analysis of the users' needs.Another important aspect is the transformation of the family structure. Flexible homes can be designed to adapt to changes in family composition, such as the arrival of children, the inclusion of elderly family members, or family separation. In this case, flexibility could be read at the micro-urban level, with a system of "interchangeable" housing and services available.In conclusion, housing flexibility is essential to address the changing needs of inhabitants. Designing and building homes with this concept in mind improves people's quality of life and promotes a greater degree of autonomy and inclusiveness. As the population ages and housing needs become more diverse, flexible housing will become increasingly important in the contemporary housing landscape.

Daniela Bosia, Giulia Marchiano

Conference Proceedings

The Human-Centered Design approach for Operational Workflow Re-design: A Case Study in Safety for Agricultural Automotive Industry

Traditionally, Safe Design has been applied mainly to product and environmental aspects, including sectors such as control rooms, automotive engineering, and medical equipment. However, its principles have been less frequently considered in critical organizational workflows. This paper addresses this gap by proposing an innovative application of a user-centered methodology to redesign procedures within industrial settings, with a specific focus on enhancing safety protocols in the Safety & Compliance teams of the agricultural automotive sector.Safety procedures are vital throughout the product lifecycle in industrial design, serving as essential safeguards against potential hazards. However, their effectiveness can be hindered by complexity, lack of user-friendliness, and insufficient attention to human factors. This paper seeks to address these issues by integrating a Human-Centered Design (HCD) approach into the safety protocols redesign process, thereby improving usability, effectiveness, and overall user experience.Two key elements for the success of this project are the integration of the HCD approach, which prioritizes end-users' needs, preferences, and capabilities, and the adoption of a redesign perspective rather than traditional procedural design. In conclusion, this article highlights the importance of extending Safe Design principles to include critical organizational workflows, particularly safety protocols. By integrating the HCD approach and focusing on procedural redesign, organizations can enhance the usability and effectiveness of their safety procedures, reinforcing their commitment to safety throughout the product lifecycle while also improving workflow efficiency.

Marialaura Delvecchio, Francesco Tesauri, Roberto Montanari, Silvia Chiesa

Conference Proceedings

A Comparative Study of Visual Culture in Tourism Apps

With the rapid advancement of mobile internet technology, tourism applications have become a crucial means for tourists to explore and learn about tourist attractions. This paper focuses on the use of visual culture in tourism apps, aiming to explore the employment and categorization of visual culture in the design of excellent tourism applications. By comparing two applications—"Forbidden City 365" and "Great Wall 24 Hours"—this study analyzes how visual culture is presented on digital platforms and promoted based on the features of the respective tourist attractions.The Forbidden City and the Great Wall, as represented by the "Forbidden City 365" and "Great Wall 24 Hours" apps, are both World Cultural Heritage sites with rich cultural connotations and distinctive features. Their visual culture is highly representative, making these two tourism apps ideal subjects for comparative analysis in this research. By examining the design elements, images, color schemes, symbols, and cultural significances in both apps, this paper provides a comprehensive evaluation of the use of visual culture. Analysis of the main pages includes investigating the frequency of design elements, colors, images, and cultural symbols used, alongside collecting user feedback from app store reviews to understand user responses and experiences with the app designs.By comparing the design concepts, cultural conveyance, and user experiences of "Forbidden City 365" and "Great Wall 24 Hours," this study explores the differences in design elements, color schemes, cultural symbols, and user feedback dimensions. It reveals how visual culture influences user experience and perception in these apps.Results indicate that visual culture plays a significant role in user interaction with applications and their understanding of tourist attractions. These visual cultures are not merely decorative but serve as carriers of cultural meaning and identity, enriching the user experience by providing deeper cultural insights. This suggests that the effective use of visual culture can significantly enhance the informational and emotional appeal of tourism applications.Additionally, this study emphasizes the importance of selecting appropriate visual cultures corresponding to the tourist attractions when designing tourism apps. By reflecting the unique cultural characteristics of the sites, app designers can create more attractive and meaningful user experiences. The comparative analysis offers valuable insights into how different cultural narratives are visually presented, providing a framework for future research in this field.To summarize, this paper highlights the potential of visual culture in enhancing the communication and aesthetic quality of tourism applications. As mobile technology continues to advance, the integration of these symbols into app design will become increasingly important in promoting cultural tourism. This research offers practical recommendations for app designers and developers to create more immersive and culturally resonant tourism experiences. By focusing on the expression of the unique visual culture of tourist attractions, tourism apps can serve not only as informational tools but also as gateways to deeper cultural appreciation and understanding.

Zhiyuan Zheng, Xin Hu

Conference Proceedings

FULL PAPER IN BOOKS: How a human-centred design approach can speed up market acceptance of long-term ECG monitoring devices

Cardiovascular diseases constitute a significant portion of preventable fatalities, underscoring the necessity for early detection and diagnosis to enhance quality of life and mitigate healthcare expenses. While conventional monitoring tools are typically confined to hospital environments, limiting continuous monitoring of high-risk individuals, ambulatory monitoring devices improve the yield of detected pathologies. However, few solutions allow comfortable long-term monitoring systems and still fewer combine event monitoring and real-time access to data, limiting the potential to detect critical and sporadic events like atrial fibrillation or tachycardia, potentially resulting in sudden fatalities. This paper presents the design of an ambulatory ECG monitoring system based on wearable technology, guided by Human Factors, User Experience, and Lean methodologies for expediting market deployment and ensuring acceptance by clinicians, patients, and markets, thereby reducing time and costs. The work described covers the initial phase of the development process, including conceptual designs, dummy prototypes, detailed designs, and prototype validation with participants. In European and US body shape databases, anthropometric research was conducted to comprehend population variability and determine device shapes and dimensions for signal accuracy and comfort optimisation.An iterative design approach was employed to streamline design and development, aligning with regulatory standards required by regulatory bodies such as MDR and FDA to facilitate defining and validating functionalities, risks, ease of use, comfort, privacy, and satisfaction.

Jose Laparra Hernández, Mónica Redón, Jorge Valero, Ignacio Espíritu García-molina, Carlos Navarro, Paola Piqueras, José Navarro, María Jesús Solera, Carlos Atienza, Sara Enrique, Nicolás Palomares

Conference Proceedings

Human-centered Design Based on the Double Diamond Model for Optimizing Hybrid Game Design

This research suggests a hybrid game design framework that combines Double Diamond methodology with system thinking, user-centered design, agile method, and heuristic evaluation. The framework is proposed to address challenges in hybrid games that merge digital and physical gameplay elements, specifically focusing on balancing technology integration and user engagement and interaction in designing hybrid games with digital and physical parts of the game. The first step is to identify the challenges of designing a hybrid game, such as game mechanics and player dynamics, which are analyzed using system thinking. Subsequently, User-centered design principles are followed by defining and prioritizing game design objectives to be relevant and empathetic to the player’s needs and expectations. After the design and development phases, the agile method is used in the test process, and game components are developed and refined iteratively to make changes based on the feedback loops. The final solution phase for game design is the heuristic evaluation to ensure usability, satisfaction, and iteration. The research showcases how the integrated framework approach includes a model of flexibility, practicality, and comprehensiveness regarding the progress of hybrid game design practices in combining human-centered design with iterative development.

Risheng Liang, Sauman Chu, Debra Lawton, Guobin Pan

Conference Proceedings

The Elderly's Response for Choice Reaction and Movement Time

User interface plays important role in product safety and usability as an interactive part between user and product. In particular, in case of the elderly, bad user interface design causes some problems in aspect of usability and safety. In this aspect, this study was conducted to investigate the elderly’s characteristics of the elderly's choice reaction and movement time for elderly-centered universal design. In the elderly’s choice reaction time, the number of alternatives was three or more, the female's response times were greater than the male. And as the number of alternatives increased, the choice reaction time of the elderly was found to increase for both men and women, and was found to be appropriately expressed by a formula applying Hick's law. The choice reaction time tended to decrease as the experiment was repeated, but in repetitions of two or more times, the decrease appeared insignificant even if the number of repetitions increased. However, it was found that there was a significant decrease in reaction time for both men and women between the first and second experiments. In the elderly’s movement time, the movement time was affected by the index of difficulty (ID) that was calculated by moving distance and button size. In particular, the movement time was more steeply increased with the increment of ID in case of the elderly than the young. This study provides meaningful results in terms of identifying the general characteristics of elderly people regarding choice reaction and movement time, and these results can be used as basic data for future universal design.

Kwangtae Jung, Yejin Lee

Conference Proceedings

Evaluation of the Learning Effectiveness of a Smart TRX and Functional Fashion Workshop

This study evaluates the learning effectiveness of a TRX and smart clothing-based workshop delivered to 25 student participants. It assesses various dimensions of learning effectiveness, including TRX experience, design thinking, functionality, product evaluation, and market analysis. To achieve this, a combination of quantitative research methods were employed; i.e., questionnaires, in-class tests, and teaching evaluations. The results revealed the TRX experience significantly enhanced students' design capabilities with regard to the development of functional clothing. However, for students from non-textile related disciplines, explanations of clothing-related terms were necessary, suggesting future workshops should incorporate relevant explanations to facilitate learning. According to student feedback, affective (about 50%) and cognitive (about 49%) aspects were developed, while skills development was minimal (about 1%). Replacing traditional textbook theory with hands-on TRX exercises was a crucial benefit of the workshop, leading to high levels of student engagement and positive experiences, as was generating a deeper understanding of core muscle group training methods. This had a positive impact and inspired the product design process.

Hsin-rong Hsieh, Ying-Chia Huang, Yu-jen Chen, Peng-cheng Hsu, Ya-chun Chang, Jui-yun Hung

Conference Proceedings

Optimizing AI System Security: An Ecosystem Recommendation to Socio-Technical Risk Management

Given the sophistication of adversarial machine learning (ML) attacks on Artificial Intelligence (AI) systems, enhanced security frameworks that integrate human factors into risk assessments are critical. This paper presents a comprehensive methodology combining cybersecurity, cyberpsychology, and AI to address human-related aspects of these attacks. It introduces an AI system security optimization ecosystem to help security officers protect AI systems against various attacks, including poisoning, evasion, extraction, and inference. The risk management approach enhances NIST and ENISA frameworks by incorporating socio-technical aspects of adversarial ML threats. By creating digital clones and using explainable AI (XAI) techniques, the human elements of attackers are integrated into security risk management. An innovative conversational agent is proposed to include defenders’ perspectives, advancing the design and deployment of secure AI systems and guiding future certification schemes.

Kitty Kioskli, Antonios Ramfos, Steve Taylor, Leandros Maglaras, Ricardo Lugo

Conference Proceedings

Comparative Experiment of Context-Awareness-Based Visualization Schemes for Focused Information on Target Search Mission Posture

The reasonableness of the recommendation of the situational focus information visualization scheme has an important impact on the operator's performance of the target search task under the three conditions of high, medium, and low situational awareness. In particular, under the conditions of medium and low situational awareness, it is necessary to adopt different recommendations for the visualization of situationally focused information in order to ensure the operator's task performance and task correctness.Based on the visualization design requirements of situational display key information, this study proposes two-dimensional enhancement and three-dimensional enhancement scheme designs for the existing schemes, and examines the differences in the operational performance of different situational display key information visualization design schemes under the situations of high, medium, and low situational awareness by means of the target searching task so as to provide optimization suggestions for the visualization of situational display key information. objective data basis.

Qiuyu Liu, Li Bing, Bei Zhang, Shuang Liu, Yuqing Dang

Conference Proceedings

Strategic Enhancement of C-UAS through Advanced Human-Computer Collaborative Command and Control Mechanism

The command and control of unmanned aircraft systems (UASs) faces challenges such as multiple and heterogeneous sources of intelligence information, high operational agility requirements, complex and diverse threat patterns. The structures of traditional command information systems are difficult to effectively address these challenges, highlighting the urgency for innovative approaches. The efficacy of counter-UAS operations hinges upon the capability of combat systems to swiftly process intelligence, identify dynamic situational changes, and deploy operational resources in an accurate and efficient manner. However, traditional human-centric command paradigms fall short in meeting evolving demands, underscoring the necessity for new methodologies to address the escalating UAV threat.In response to these imperatives, this paper proposes an intelligent strategy model tailored for C-UAS command and control, emphasizing human-computer collaborative decision-making. Rooted in the OODA loop theory and informed by the characteristics of informatized, networked, and intelligent systems, this model aims to fulfill the imperatives of security, accuracy, and timeliness inherent in C-UAS. It designs a comprehensive framework structured around the counter operational process, dividing the task into four stages: multidimensional intelligence comprehensive situational awareness, spatiotemporal target locating, human-computer collaborative decision-making, and coordinated actions among equipment.This model provides a design framework based on the C-UAS application process, dividing the task into four stages. (1)Multidimensional intelligence comprehensive situation awareness. The fusion processing of multi-dimensional and multi-source information data forms a comprehensive and unified human-computer situational awareness capability. (2)Spatiotemporal target locating. Detection and identification of intelligence information to achieve accurate positioning and stable tracking of threat targets. (3)Human-computer collaborative decision-making. Division of labor and cooperation between humans and machines to improve decision-making efficiency, accuracy, and flexible adaptability. (4)Effectors coordinated actions. Rapid formation of a kill chain according to mission instructions, while possessing the ability to quickly switch kill chains.In order to verify the effectiveness of the proposed human-computer collaboration model, practical applications were conducted within an integrated C-UAS command and control system featuring diverse and heterogeneous equipment. The system was meticulously designed to address real-world operational exigencies through the implementation of cutting-edge methodologies, including multi-sensor autonomous collaboration, multi-target tracking optimization, and human-computer collaborative decision-making and evaluation. Field exercises were conducted in three typical operational scenarios: (1)Close-Range Surprise Raid of UAV assaults, (2)Drone Swarm Saturation Attacks from Multi-Direction, (3)Coordinated strikes by multiple UAVs. The system successfully detected and intercepted all incoming threats within the specified time, thereby demonstrating its autonomous operational capabilities in authentic battlefield environments.The outcomes of these experiments unequivocally affirm the capability of the human-computer collaborative system to detect suspicious targets, discern threat dynamics, assist commanders in decision-making, and orchestrate weapon systems for interception missions expediently and accurately. Moreover, the system demonstrates exceptional adaptability in swiftly responding to emergent threats and effectively engaging multiple targets from various directions.In conclusion, this research advocates an intelligent command and control strategy model underscored by human-computer collaboration, heralding a promising trajectory for enhancing the efficacy of C-UAS in modern warfare domains. By guiding the development and improvement of integrated C-UAS, this model is expected to strengthen defenses against the evolving UAV threat landscape while optimizing command efficiency in human-computer systems.

Yinan Zhao, Zhanxun Dong, Gang Liu, Xiaozhang Dong, Suiping Hu

Conference Proceedings

Autonomous Behavior of Bipedal Robot by Learning Time-series Camera Images

The author is conducting basic research on the autonomous behavior of a small biped robot. The system under study acquires behavioral data when a human controls the small biped robot. This system then learns from this behavioral data and image data obtained from the robot’s onboard camera. However, our previous method did not account for time-series behaviors, resulting in the repetition of certain behaviors. To address this issue, this paper utilizes Recurrent Neural Network (RNN), which are well-suited for learning time-series information. As a result, it was confirmed that the robot could behave autonomously without frequently repeating specific behavioral patterns.

Manabu Motegi

Conference Proceedings

Air conditioner operating system based on the concept of Benefit of Inconvenience (Bol)

Today, a growing body of research focuses on the "Benefit of Inconvenience (BoI)," a richness that can be enjoyed and, therefore, the physical and psychological labor it entails. There is also a movement to propose the "Benefit of Inconvenience Systems (BoI Systems)," things (Products and Services) that provide the BoI to users. The purpose of this study is to propose a new BoI System by analyzing conveniences in the living environment, the richness lost due to conveniences, and the adverse effects caused. In proposing a new BoI System, this study focuses on convenience and its adverse effects from two perspectives. First is the black box effect of adjusting the room temperature, resulting in the convenience of setting the room temperature at the touch of buttons by operating an air conditioner using a remote control. Second is the diminishment of the value of each photo, leading people to leave their photos without managing and reviewing them, a result of the convenience of the spread of smartphones, which allows anyone to take any number of photos quickly. By re-examining these conveniences and adverse effects, we propose "MemoCon (Memory Air Conditioner)," a BoI System that operates an air conditioner by estimating the temperature and air volume based on the visuals of photos taken in the past. The room temperature can be adjusted based on the user's intuition by operating the air conditioner through the visuals in the photos. In addition, selecting photos from a photo album on a smartphone creates an opportunity for the user to look back at the photos. After determining the specifications, we made a prototype for use as a smartphone application and a promotional video to show the actual environment in which "MemoCon" would be used so that the content of this proposal could be conveyed concretely.

Haruki Tanaka, Kodai Furumachi, Haruaki Kobayashi, Namgyu Kang

Conference Proceedings

How User-Platform Interactions Influence Continuance Intention in Augmented Reality Mobile Platforms

When we interact with mobile platforms in an augmented reality environment, it changes our cognitive and emotional engagements through different stimuli cues that respond to our behavioral intentions. The effects of those engagements through augmented reality, considering user-platform interactions, are unexplored. This study investigated a nuanced understanding of how stimuli cues in augmented reality affect sense of immersion and sense of presence, followed by an interaction-engagement-intention (I-E-I) model. A quantitative method was used to validate the proposed model. Based on our online survey with 886 responses, we assessed the influences of product fit, network quality, and artificial intelligence-driven recommendation in perceiving cognitive engagements. This study examined the importance of engaging satisfaction and trust as emotional engagements, influencing users’ continuance intention. Our findings confirm that sources of information, especially online reviews, positively affect in perceiving subjective norms. Also, trust has a more significant influence on the continuance intention to use AR mobile platforms. Also, the results explored that the generation of users has a significant impact on continuance intention. This could enhance the capabilities of information system designers, researchers, marketing professionals, and solution providers to attain sustainable user retention.

Zian Kabir, Kyeong Kang

Conference Proceedings

Body Positivity Perception and Fashion

One of the most important problems of our day is not liking our own bodies and being like someone else, which has become extremely important especially among young people and women. Due to this situation, many people try to make themselves look like people they want to see or like through surgical operations at a very young age. This situation brings with it very important problems and even causes irreversible mistakes, psychological problems and even deaths at a young age. For all these reasons, the body positivity movement, which sets out with the philosophy of trying to be happy with our own bodies no matter what kind of body type or shape we have, has emerged at this very moment by creating great awareness. With the body positivity movement, a more realistic ideal female body perception has begun to emerge. In this context, the body positivity movement is an important movement that encourages individuals to accept and love themselves as they are. The spread of this movement can change the ideal body perception of society and positively affect the psychological health of individuals. Therefore, awareness about body positivity needs to be increased and supported. In this context, a survey was conducted to determine the body positivity perception among young women between the ages of 18-24, to reveal the situation regarding their bodies and to reveal the attitude of society towards body standards and the findings were presented. According to the findings obtained as a result of the research conducted on a total of 296 university students, it was determined that the majority of the students have knowledge about body positivity and are aware of knowing, loving and accepting their own bodies in this direction.

Özlem Kaya

Conference Proceedings

How Multi-sensory Can Help the Visually Impaired Better Play the Instruments: An Inclusive Design Practice

For the visually impaired, it is harder to learn how to play an instrument. Taking playing the piano as the case, we conducted the research to explore how other senses work better to support this special group to learn how to play the piano. Using the methods of literature analysis and data collection by designed questionnaire, we tried to design a smart keyboard to solve the problems people with impaired sight may meet in three perspectives: 1) Finding the corresponding keys for notes. 2) Communication with instructors. 3) Variable changes in rhythm. We provide a new learning possibility for the visually impaired to play the piano. Based on the concept of inclusive design, we also considered the needs of the normal people with the expectation to achieve the inclusive goal of music communication between the abled and the disabled.

Qian Jiang, Kin Wai Michael Siu, Jiannong Cao

Conference Proceedings

Assembly Complexity Index (ACI): A Framework to Evaluate Assembly Process for Validating a Modular Robotic Design

The assembly of equipment necessitates varying degrees of expertise, with complexity often escalating alongside technological advancements. While automation has reduced the workload in manufacturing and assembly lines, repair and maintenance still require a significant user skillset. This research focused on developing a modular robotic system with straightforward assembly and disassembly, requiring minimal robotics expertise from end users. A modular robotic system offers benefits such as shorter repair times leading to reduced downtimes on a factory shop floor, options for task-agnostic reconfiguration and deployment, and potential reductions in initial investment costs.To validate this hypothesis, a study was conducted with twelve participants with differing expertise in tools, hardware, and construction. Direct evaluation of personal and workplace attributes such as workload, task complexity, prior expertise and learning is often indiscernible and non-comparable. Thus, it was essential to establish a tangible workflow to evaluate and monitor the design's effectiveness and any modifications' impact on assembly ease. The study employed the Task Complexity Index (TCI) and NASA Task Load Index (TLX) adapted to measure task complexity and user workload. Both TCI and TLX have been used independently in various studies and a correlation between the two was identified. Combining data on task complexity and workload provided a comprehensive evaluation of the assembly process.Results indicated a marked improvement in the Assembly Complexity Index (ACI) during the second phase of experiments due to participant learning and a lower time (p = 0.026) required for completion of a much more complicated task demanding a higher workload (p = 0.014). This research aims to establish a framework for identifying an Assembly Complexity Index (ACI) using these the subjective workload and complexity assessment tools. The study considered factors such as the number of components, operations, and tools required. In addition, it acknowledged that factors like the availability of resources, component size and weight, operation complexity, and tool availability also impact the overall assembly complexity.

Kartikeya Walia, Philip Breedon

Conference Proceedings

Designing a Human-Robot Collaboration System to reduce Work Fatigue in Redistributing Dockless Sharing Bikes

Dockless bike-sharing systems in China have enhanced user convenience but face challenges like vandalism and improper parking. Despite advancements in bike collection technologies, manual labor remains essential in the redistribution process, often leading to worker fatigue and safety concerns. This study explores solutions to reduce work-related fatigue for bike collectors using a human-robot collaboration (HRC) system. In our proposed system, workers assess bike conditions and position them for a robotic arm to handle lifting and placement. The system aims to minimize physical strain and improve worker experience. We conducted simulations with healthy adults to test the system's effectiveness. Physical fatigue was measured through heart rate monitoring, and mental fatigue was assessed using the Multidimensional Fatigue Inventory. Participants were divided into two groups: one with nominal technological assistance and one without. Professional bike distributors evaluated the system's performance by observing task recordings and completing structured surveys. Our findings show that the HRC system significantly reduces physical and mental fatigue among participants. The system's potential to enhance bike redistribution efficiency and improve worker safety is promising. Future work will focus on integrating advanced robotics, intelligent software, and smart scheduling for real-world deployment and broader logistics applications.

Yueru Chen, Yun Lam Daniel Lo, Xinghan Xiao, Weinan Li, Luolin Zhang, Fang Le, Fang Cong, Stephen Jia Wang

Conference Proceedings

Evaluation of Feedback in Manual Assembly Assistance Systems

Despite the technological advancements of Industry 4.0 and automation in many industries, the variability and complexity of products to meet market demands require a level of flexibility that is not yet achieved with machinery. Consequently, manual assembly processes have become the core of manufacturing in organizations that aim to keep up with the accelerated pace of market growth. However, increased flexibility and manual assembly have the disadvantage of increased manufacturing errors, which are more likely due to the complexity of processes, operator fatigue, etc. This paper highlights the crucial role of feedback in the assembly process, presenting an evaluation of human operator performance using a simulation of two types of intelligent assembly assistance systems, one that only provides task instructions and another that, in addition to instructions, displays errors in task execution. A 3D-printed toy truck model was used to simulate assembly. As a result, a total of 12 participants participated in the experiment. The research primarily evaluates the metrics of assembly completion time and the number of errors. Data analysis suggests a difference in the two groups' assembly performance. The group of participants whose assistance system provided feedback on errors appears to have been more efficient, taking less time to recover from errors.

Mariannys Rodriguez Gasca, Diego Queiroz, Isabel Giannecchini, Sanderson Cesar Macedo Barbalho, Antonia Markus

Conference Proceedings

Enhancing Emergency Response: A Reliability Analysis of Human-Robot Collaboration

The adoption of robots in daily life, such as service robots, is progressing and necessitates that humans make informed decisions when interacting with them. However, the relationships between humans and robots, particularly in emergencies, are not as developed as human-to-human relationships. A lack of understanding about robots often leads to significant accidents. To facilitate effective and appropriate collaboration, the analysis of human-robot interaction (HRI) is essential. This study focuses on analyzing "reliability," which is particularly crucial in the healthcare and training fields. We specifically examined the interactions between humans and robots during emergencies and analyzed the reliability of these interactions. Our verification method combines case studies and empirical experiments, beginning with a case analysis and followed by an experimental design based on these findings. Empirical experiments confirmed that combining visual and tactile feedback significantly affects interface reliability in HRIs. Designing empirical experiments based on case study results is a crucial analytical approach for enhancing the utility of services and healthcare robots for users.

Daigo Misaki, Kazuma Shirakawa

Conference Proceedings

Comparative user feedback on the efficacy of a back-support exoskeleton in industrial settings

Work-related musculoskeletal disorders (WMSDs) are prevalent in industrial settings, particularly affecting the lower back, shoulders, and knees. Exoskeletons show promise in reducing WMSDs, though their effectiveness varies by user demographics. This study investigates the impact of a passive back-support exoskeleton on perceived physical exertion (PPE) during lifting and carrying tasks, with a focus on gender-specific responses. Twenty-two participants rated their PPE under two conditions: with and without the exoskeleton. Results indicate that exoskeleton use significantly reduces perceived exertion, especially for female participants. These findings highlight the importance of gender-specific considerations in the design and optimization of exoskeletons for improving ergonomic outcomes across diverse user groups.

Fatemeh Davoudi Kakhki, Armin Moghadam

Conference Proceedings

Testing a Motion Matching Algorithm for Gaze-based HMI

This study explores gaze-based interaction, focusing on object selection, particularly in dynamic environments. Traditional methods like dwell-time selection have limitations, prompting investigation into novel approaches such as motion matching. A pilot study was conducted to compare a motion matching algorithm with dwell-time selection, indicating a tendency towards faster selection times with motion matching. Workload metrics showed very similar results between selection mechanisms, but a small bias towards reduced user frustration and enhanced satisfaction using motion matching. Challenges remain, including the Midas touch problem and technical constraints of eye tracking technology, highlighting the need for further research to refine algorithms and address limitations. Despite challenges, motion matching represents progress towards making gaze-based interaction more accessible for widespread use.

Cosima Uechtritz, Thomas E F Witte, Verena Rist, Torsten Gfesser

Conference Proceedings

Human Interaction with Autonomous Delivery Robots: Navigating the Intersection of Psychological Acceptance and Societal Integration

The rapid advancement of autonomous delivery robots has led to their increasing presence in our daily lives, prompting the need for a deeper understanding of the factors influencing their psychological acceptance and societal integration. This research paper presents a comprehensive survey-based study that investigates the complex interplay between human perceptions, attitudes, and behaviors towards delivery robots. The study employs a mixed-methods approach, combining quantitative and qualitative data collection techniques to gather rich insights from a diverse sample of participants.The survey design incorporates a range of questions addressing key aspects of human-robot interaction, including perceived usefulness, ease of use, trust, safety concerns, social presence, and future expectations. The data collection process involves online questionnaires and semi-structured interviews, ensuring a robust and representative dataset. The analysis employs statistical techniques and thematic coding to identify significant patterns, trends, and relationships within the data.Through a critical synthesis of the existing literature and the study's findings, this paper contributes novel insights into the psychological and societal factors shaping the acceptance of delivery robots. The results highlight the importance of trust, transparency, and user-centered design in fostering positive attitudes and willingness to engage with these technologies. The paper also identifies key challenges and opportunities for the successful integration of delivery robots into various domains, such as last-mile delivery, healthcare, and retail.By providing a comprehensive understanding of the human dimensions of delivery robot acceptance, this research advances the field of human-robot interaction and offers valuable implications for the design, development, and deployment of these technologies. The findings emphasize the need for collaborative efforts among researchers, industry stakeholders, and policymakers to create delivery robot solutions that align with user needs, societal values, and ethical considerations. Overall, this paper contributes to the ongoing discourse on the future of autonomous delivery systems and their transformative potential for enhancing efficiency, accessibility, and sustainability in our rapidly evolving world.

Saumil Patel

Conference Proceedings

Optimizing UX design to enhance user confidence in digital products

As digital products grow in prominence, the significance of user experience (UX) design becomes increasingly evident. A crucial outcome of strong UX design is user confidence, defined as a user’s trust in their ability to effectively interact with a product. Designs that foster user confidence reduce interface uncertainty and enhance user self-belief, leading to increased engagement and repeated interactions. Conversely, a lack of user confidence can drive users to seek alternative products. This study aims to uncover the underlying principles that enable users to navigate products with confidence, thereby providing design guidance for fostering long-term product loyalty. This study identifies five key design principles that enhance user confidence: 1) Creating familiarity with UI elements and interactions, 2) Balancing information accessibility and overload, 3) Providing clarity in action descriptions, 4) Offering feedback after decisive user actions, and 5) Enabling the reversibility of actions. To explore user confidence, the study employed three methods. In-depth user interviews were conducted to gather insights on user experiences with both digital and physical products. Afterward, a three-day immersion study (“UX diary”) was conducted to document users’ emotional interactions with everyday products. Finally, a series of generative workshops were hosted to validate the principles and explore their applicability in different product contexts, such as posting content on Reddit and placing an order on Amazon. Participants reported that these principles provided reassurance and facilitated ease of use. User confidence is a prerequisite for other UX design considerations. By focusing on these principles, designers can create products that foster confidence and satisfaction, ultimately leading to improved user engagement and retention.

Vivian Li, Peiyi Sun, Yihyun Lim

Conference Proceedings

Human Language-Instructed Robotic Excavation based on Behavior Trees

Collaborative construction robots have emerged as a promising alternative to relieve construction workers from both physically and cognitively demanding tasks, contributing to a safer and more productive construction industry. However, communicating with robots is not a trivial task as human workers and robots speak different languages. From the human-centered perspective, allowing human workers to communicate with robots using natural language is desirable because it minimizes additional cognitive load to human workers. Existing studies, however, have been focusing on converting language instructions into sequential actions, leading to a rigid task plan and inability to handle complex situations and unstructured working environments. To address this critical limitation, this paper explores the use of behavior tree (BT), an alternative architecture for describing and controlling complex tasks like excavation. A behavior tree is a hierarchical tree structure that specifies the switching between the agent’s actions (i.e., execution nodes) via control flow nodes. Its modular nature allows the BT of excavation to be generated through linking reusable actions based on the human task descriptions. The resulting BT structure enables the robot to alter its behavior by selecting different tree branches in response to changing working conditions, thus improving its adaptability to dynamic construction environment and its capability of error-handling. In addition, the BT eases the human understanding of robot behavior for debugging and correcting robot behavior. A corresponding framework is proposed for enabling humans to guide a robotic excavator using goal-oriented language instructions. The framework consists of four modules: interpretation and reasoning, knowledge management, structural analysis and parsing, and BT generation. The interpretation and reasoning module decomposes instructions into structured executable intents. The knowledge management module organizes the knowledge for instruction reasoning, including the robot capable skills and its current working environment. Structure analysis and parsing module further grounds the intents and extracts associated parameters, while BT generation module maps the extracted elements with predefined BT nodes, building and refining the BTs of desired tasks. A case illustration is performed to demonstrate the viability of the proposed framework with executable demos. The findings are expected to facilitate efficient and transparent human-robot cooperation in earthmoving construction from a human friendly perspective.

Zirui Hong, Hubo Cai

Conference Proceedings

Applying UX principles to innovate citizen Science platform development: an integrative approach

The development of digital platforms is critical for the success of Citizen Science initiatives, as it facilitates the effective engagement of diverse participant profiles. To ensure these platforms are effective, efficient, and satisfactory for users, a strategic development approach is necessary. This research proposes a design and development model for a Citizen Science platform at the European level, grounded in User Experience (UX) principles. The methodology involved benchmarking existing platforms, developing user stories to identify necessary functionalities, and assessing user engagement and satisfaction through focus groups, UX research using Hotjar, and web analytics via Matomo. The findings reveal a set of principles—such as the STP model, user-centered design, content marketing, and digital analytics—that are instrumental in optimizing the development of Citizen Science platforms.

Manuel Gertrudix Barrio, Alejandro Carbonell-alcocer, Juan Romero-luis, Alberto Sanchez-acedo, Begoña Rivas-rebaque

Conference Proceedings

Mobile Phone Accessibility Solution for People with Upper Limb Dysfunction

With the rapid development of smartphones and digital technology, it has become the norm for people with upper limb dysfunction to use smartphones to access the Internet. This study applies the methodology of qualitative research, combining semi-structured in-depth interviews and observation strategies, to examine the daily lives of people with upper limb dysfunction in detail, and to compare and analyze existing solutions, aiming at exploring better solutions for smartphone accessibility, and proposing rationalized suggestions for future development, in order to promote the development of cell phone use experience for people with upper limb dysfunction. In this study, the upper limb dysfunction population is firstly divided into six categories according to the cause of the injury, and the research object does not include the people who have no arm or complete loss of upper limb function due to various reasons. The study first focused on existing smartphone accessibility solutions, focusing on a number of features including voice recognition technology, screen reader technology, "accessibility menu" buttons, magnification, high contrast and color adjustment, etc. The results show that although existing accessibility solutions provide a certain level of support for people with upper limb dysfunction, they do not provide the same level of support for people with upper limb dysfunction, but they do not provide the same level of support for people with upper limb dysfunction. The results show that although existing accessibility solutions provide a certain degree of support for people with upper limb dysfunction, there are still a number of limitations, including, but not limited to, shortcomings in technical applicability, user satisfaction and personalized design. Future accessibility technologies should focus more on personalization and ease-of-use design, and could incorporate mechanisms such as eye-tracking technology and head movement control to meet the needs and abilities of different users. The findings of this study provide a useful solution to the digital connectivity problem for people with upper limb dysfunction, and also provide important references and insights for the continued development of accessible technology and social progress.

Chen Jinghong, Xin Hu

Conference Proceedings

DMGR: Divisible Multi-complex Gesture Recognition Based on Word Segmentation Processing

In the realm of gesture recognition and computer algorithm optimization, traditional approaches have predominantly focused on recognizing isolated gestures. However, this paradigm proves inadequate when confronted with complex gestural sequences, resulting in cumbersome recognition processes and diminished accuracy. Contemporary human-computer interaction (HCI) applications often necessitate users to perform intricate series of gestures, rather than isolated movements. Consequently, there is a pressing need for systems capable of not only recognizing individual gestures but also accurately segmenting and interpreting sequences of complex gestures to infer user intent and provide natural, intuitive responses.Drawing parallels with natural language processing (NLP), where understanding complex sentences requires word segmentation, structural analysis, and contextual comprehension, the field of HCI faces similar challenges in multi-complex dynamic gesture interaction. The cornerstone of effective gesture-based interaction lies in precise gesture segmentation, recognition, and intention understanding. The crux of the matter is developing methods to accurately delineate individual gestures within a continuous sequence and establish contextual relationships between them to discern the user's overarching intent. To address these challenges and facilitate more natural and user-friendly multi-complex dynamic gesture interaction, this paper introduces a novel recognition model and segmentation algorithm. The proposed framework draws inspiration from word processing techniques in NLP, applying a list model to the multi-complex gesture task machine. This approach decomposes complex gestural sequences into constituent operations, which are further subdivided into consecutive actions corresponding to individual gestures. By recognizing each gesture independently and then synthesizing this information, the system can interpret the entire complex gesture task. The algorithm incorporates the concept of action elements to reduce gesture dimension and employs a probability density distribution-based segmentation and optimization technique to accurately partition gestures within multi-complex tasks. This innovative approach not only enhances recognition accuracy but also significantly reduces computational complexity, as demonstrated by experimental results on a multi-complex gesture task database.The paper is structured as follows: First, it elucidates the algorithm framework for divisible multi-complex dynamic gesture task recognition and the underlying model based on word processing techniques. Subsequently, it provides a detailed exposition of the algorithm's implementation, encompassing feature extraction, gesture classification, segmentation, and optimization methodologies. Finally, the paper presents the experimental design and results, offering empirical validation of the proposed approach's efficacy.This research represents a significant advancement in the field of gesture recognition, particularly in handling complex, multi-gesture sequences. By addressing the limitations of traditional single-gesture recognition systems, this work paves the way for more sophisticated and intuitive human-computer interaction paradigms. The proposed model's ability to accurately segment and interpret complex gesture sequences opens up new possibilities for applications in various domains, from virtual reality interfaces to robotic control systems. The integration of concepts from NLP into gesture recognition underscores the interdisciplinary nature of this research, highlighting the potential for cross-pollination of ideas between different fields of computer science. Furthermore, the emphasis on reducing computational complexity while maintaining high accuracy addresses a crucial concern in real-time interactive systems. In conclusion, this study makes substantial contributions to the field of gesture recognition and HCI, offering a robust framework for handling multi-complex dynamic gesture tasks. The proposed algorithms and models not only advance the state of the art in gesture recognition but also lay the groundwork for more natural and efficient human-computer interaction modalities in future applications.

Yuncheng Ge, Yewei Huang, Ye Julei, Huazixi Zeng, Hechong Su, Zengyao Yang

Conference Proceedings

Development of A Single Usability Metric that Accounts for Accessibility (SUMA)

Various technology tools have been designed to aid person(s) with disabilities (PWD). However, no wholistic, standardized method exists that evaluates usability with a focus on accessibility of apps. The objective of this study was to develop a model to assess app usability with a single usability metric that accounts for accessibility (SUMA). The model includes both subjective and objective usability measures to create a comprehensive view of usability and considers accessibility metrics to ensure interfaces are inclusive for PWD. SUMA combines all measures into a singular score, so it is easily interpretable and comparable to other interfaces since previous studies tended to prefer singular score questionnaires. Seven metrics are selected based on their relevance to website and app design as well as inclusivity considerations for PWD including efficiency, effectiveness, satisfaction, accessibility, learnability, flexibility, and memorability. This paper focuses on the development of SUMA and explains the next steps to finalize the model. This includes reducing model dimensionality through a principal component analysis (PCA) of user testing data from an indoor navigation app designed for PWD. Examples of the final model and Excel package are shown based on the pilot data. The results of PCA yielded a model with reduced dimensionality while maintaining a desirable amount of dataset variability.

Vanessa Nasr, Maryam Zahabi

Conference Proceedings

The Impact of Resolution and Material Selection on a Prototype Assessment

Prototypes are a well-established artefacts that are used to express and validate ideas and concepts in the product design and development process, enabling team members, stakeholders, or final users to provide feedback (Gero, 1990). Despite the usefulness of prototypes in facilitating the development process, challenges associated with their usage have emerged over time. Prototypes can be developed in a variety of ways, ranging from low-fidelity paper prototypes, commonly used in software development, to high-fidelity pre- production prototypes that closely resemble the final product (Pei et al., 2010, 2011). Nevertheless, a consensus regarding the classification of these artifacts remains uncertain due to divergent perspectives presented by various authors, e.g. Coughlan et al. (2007), Jensen et al. (2016) and Pei et al. (2011). Regardless, there are an agreement that the differences in complexity among those are referred to as fidelity or resolution, and the major issue is to determinate timing, methodology and context to apply them in the design process. The resolution of prototypes pertains to the level of information conveyed by each artifact and its clarity in communicating its intended function. Scholars such as Jensen et al. (2016) and Lim et al. (2008) emphasize the importance of aligning prototype resolution with its intended purpose. Conversely, Pei et al. (2011) offer a detailed taxonomy categorizing prototypes based on predefined characteristics. Several researchers, including Catani & Biers (1998), Sauer et al. (2008), and Wiklund et al. (1992), have compared prototypes of varying fidelity and concluded that lower fidelity prototypes can yield comparable results to high-fidelity ones. However, recent studies by Deininger et al. (2017) and Jensen et al. (2018) have focused on how resolution influences user satisfaction, finding a preference for higher-fidelity prototypes that are easier to understand. Nevertheless, none of these studies have directly examined the relationship between prototype resolution and user performance. This study aims to investigate the impact of prototype resolution on performance assessment using six prototypes. Thirty-three participants were involved, divided into six groups, with ages ranging from 18 to 58 years (mean = 23.7 years; SD = 7.4). The prototypes, denoted as V1 to V6, were developed to simulate design iterations of a Citroen Xsara steering wheel, with two prototypes classified as low fidelity, two as medium fidelity, and two as high fidelity, each iteration increasing in resolution, information density, and detail. All prototypes were tested on a driving simulator utilizing a SuperDrive SV250® kit with steering wheel and pedals, connected to the Assetto Corsa® video game software. The findings indicate that while higher resolutions tend to exhibit gradual improvement in performance, with better results corresponding to increased resolution, lower resolutions do not demonstrate this linear behaviour. Notably, V1 performed similarly to V3, while V2 exhibited the poorest performance. This phenomenon may be attributed to the design of the prototypes, particularly V2 and V3, which feature a blended interface, leading participants to interact directly with labels, the most contrasting details on the prototypes. In contrast, V1, despite having a complete 2D layout, offers a more coherent design, facilitating interpretation for participants.

Vitor Pais, Álvaro M. Sampaio, Nelson Costa, António J. Pontes

Conference Proceedings

Interface Design of Vehicle AR-HUD Based on User Needs

Focused on user needs, it aims to explore the design strategies for in-vehicle AR-HUD interfaces that effectively reduce cognitive load, improve driving safety, and elevate user experience and satisfaction across safety, experiential, and visual dimensions. Firstly, user needs were obtained through semi structured interviews, in-depth observations, etc., and classified using the KANO model. Secondly, the Analytic Hierarchy Process (AHP) is employed to calculate and prioritize the weights of user demands, thereby identifying core requirements. Lastly, the Quality Function Deployment (QFD) was employed to map ambiguous user needs into specific design elements, with weights calculated and ranked to provide execution strategies and practical guidance for implementing in-vehicle AR-HUD interfaces. Following the KANO-AHP-QFD research process, 11 user needs were objectively identified and extracted, leading to the identification of 15 design elements across safety, experience, and visual dimensions, culminating in innovative design proposals for the in-vehicle AR-HUD interface. Through the comprehensive application of the KANO-AHP-QFD model, both surface-level and latent user needs can be met, effectively guiding interface design, enhancing user satisfaction, and providing reference and insights for similar designs.

Yi Fan Chen, Jiejun Dai

Conference Proceedings

HPCMod: Agent-Based Modeling Framework for Modeling Users on High-Performance Computing Resources

High-performance computing (HPC) resources are used for compute-demanding calculations in various fields of science and engineering. They are large computational facilities utilized by many users simultaneously. High utilization often leads to high waiting times. Simulating users' behavior on such a system can help with future system design, develop user interventions, and ultimately improve the user’s experience and resource utilization. Here, we present HPCMod, an Agent-Based Modeling Framework for Modeling Users on HPC Resources. The key concept of the framework is the representation of the user's computational needs: the user project is represented as a collection of possibly dependent compute tasks. Each task can be executed as a single compute job or a series of jobs, depending on the task size. Some tasks can be too big to be executed in one chunk; such a situation often occurs during molecular dynamics simulation. There are multiple ways in which tasks can be split into jobs, and users will make their decisions based on previous experience, application parallel scalability, and available resources. For example, a user's compute task requires 32 node hours; it can be executed in multiple ways: a single 32-hour job on one node, two sequential 16-hour jobs on one node, one 16-hour job on two nodes, and so on. In the HPCMod, we implemented three models: 1) historical replay of compute jobs, 2) simulation of reconstituted compute tasks using historical job sizes, and 3) adaptive compute tasks splitting where users can modify jobs parameters given available resources till the execution of the next job in line. The framework was tested on a ten-node test system and a larger 1,736-node system modeled after a portion of TACC Stampede-2. The HPC resource model implements a first in first out (FIFO) scheduler with backfill scheduling. The initial results showed that on a tiny system, adaptive task-splitting is beneficial for the user but leads to a larger number of jobs. On a large system, the adaptive task-splitting was also very beneficial, decreasing waiting times for users using this strategy almost two times; however, other users got a 5% increase in their wait time. Further investigation is needed as the current task reconstitution algorithm is deterministic and does not allow quantification of job recombination uncertainties. The Julia-based implementation is fast: five years of historic workflow consisting of a million jobs and a one-hour stepping took around three minutes.

Nikolay A Simakov

Conference Proceedings

Development of a Dynamic Visual Acuity Training Software Based on Baseball Situations to Improve Users' Dynamic Visual Ability

Dynamic visual acuity (DVA) is crucial for successful baseball batting, as it enables players to quickly assess the ball’s trajectory and adjust their swing timing in a short period of time. This study involved interviews with 19 baseball coaches and players from four collegiate teams, as well as questionnaire distribution and a literature review, revealed that visual training is underutilized in baseball from youth to professional levels. Existing training products often lack customization to individual abilities and struggle to translate training effect to on-field performance. Recent advances in virtual reality (VR) have been applied to baseball training, but issues such as motion sickness remain. To address these gaps, this study developed a dynamic vision training software with three modes: (1) Simulation Mode, (2) Track Blocking Mode, and (3) Texture Contrast Mode. The software adjusts difficulty based on an 80% accuracy threshold and focuses on training players to recognize fine details, such as the seams on a fast-moving ball. To evaluate the software's effectiveness, 18 non-athletic participants were recruited and divided among the three training modes. Each group underwent a pre-test, completed eight training sessions, and finished with a post-test. Results showed an overall improvement in personal ability rating, with statistical significance in the Simulation and Track Blocking Modes, but not in the Texture Contrast Mode, possibly due to eye fatigue in one participant. The study demonstrates that this software allows teams to flexibly schedule training and enhances real-world performance more effectively than other visual training tools.

Yu-Hsiu Hung, Bo-Wei Chen

Conference Proceedings

An Approach to System Architecture Design Through Usability Heuristics

This research explores the application of usability heuristics in the design of system architectures, addressing the current lack of clear guidelines in systems engineering. Systems engineering has evolved into a distinct scientific field, emphasizing the importance of robust and user-friendly system designs. The integration of human factors and usability principles is crucial for developing effective system architectures that can meet both technical and user needs. This study investigates how usability heuristics can be applied to enhance system architecture design.The methodology involved two primary usability testing approaches: timed performance assessments and A/B testing. The timed performance assessments evaluated two differently designed architectures of an autonomous vehicle's active safety features. Sixteen participants, selected based on their STEM background and basic design knowledge, were timed on their ability to locate and interpret information from the system architectures. The architectures were analyzed for node identification, data flow paths, and nested node structures. Additionally, qualitative feedback was gathered to understand user satisfaction and perceived usability.A/B testing was conducted on an aircraft avionics system architecture, comparing a patented design with a newly designed configuration. Participants provided qualitative feedback on their understanding, satisfaction, and perceived complexity of each architecture. The aim was to identify specific design elements that contribute to better usability and to develop a set of heuristics tailored for system architecture design.The analysis revealed significant differences in usability between the two architectures tested in the timed performance assessments. Participants identified elements faster in the redesigned architecture with fewer line intersections and clearer node organization. The results highlighted the importance of minimizing line intersections, using straight lines instead of diagonal ones, and providing clear labels for all elements. In A/B testing, the newly designed architecture received higher satisfaction ratings and was easier for participants to understand, emphasizing the value of organized node grouping and clear flow of information.Based on the findings, a refined set of usability heuristics for system architecture design was developed. These heuristics include minimizing the intersection of arrows, creating straight lines, labeling and identifying all elements, ensuring a clear information flow, designing with enough space to reduce noise and promote flexibility, and attaching a key for all abbreviations and symbols. These guidelines aim to help system architects create more intuitive and efficient designs.The study concludes that applying usability heuristics can significantly improve the design of system architectures, leading to better performance, user satisfaction, and overall business success. The research underscores the need for further studies involving a larger and more diverse participant pool to validate and expand the proposed heuristics. By integrating human factors research into systems engineering, businesses can develop more robust and user-friendly products that meet the demands of both technical and non-technical stakeholders.

Preston Myers, Duha Ali

Conference Proceedings

Revisiting the Brief Nuclear Usability Measure: A Preliminary Evaluation of its Validity and Reliability using Licensed Operators

Global energy consumption is expected to increase through 2050 (EIA, 2023). Global population grown, increased manufacturing, and higher living standards are cited as key drivers to pushing energy consumption beyond energy efficiency advances. In order to circumvent such grim projections, the role of nuclear electricity generation has a pivotal role in providing carbon-free electricity generation across the world. Within the United States, there have been thrusts in extending the operational lifespan of the existing light water reactor fleet through significantly modernizing these existing plants with digital technologies that reduce their operations and maintenance cost. Additionally, despite some setbacks, development and deployment of advanced reactor technologies are continuing to move forward from both developer and regulatory standpoints. Across both pathways, the role of human factors engineering is crucial to ensuring timely completion of major modernization efforts or advanced reactor deployment by addressing human and technology integration challenges. Such challenges range from effective allocation of function with digital technologies and automation to the design of novel human-system interfaces that support effective monitoring and control of advanced reactors. Two important human factors constructs that are relevant for human factors tests and evaluation of these advanced technologies entails situation awareness and workload. For instance, these constructs are referenced in existing regulatory review guidance (e.g., NUREG-0711) as vital to assess during integrated system validation and other testing and evaluation activities. Indeed, a multimethod approach is generally most appropriate for assessing situation awareness and workload as these constructs are not directly observable. A suite of objective and subjective measures is typically a “gold standard” in evaluating situation awareness and workload. Though, the use of self-report through standardized survey instruments offers a practical way of collecting such data, particularly in the “real world.” For instance, when testing licensed operators, availability and time for data collection can be significantly limited (Kovesdi and Joe, 2019). Therefore, approaches to streamline survey instruments that can adequately assess situation awareness and workload have been explored. Kovesdi and Joe (2019) developed an abbreviated survey instrument, the Brief Nuclear Usability Measure, derived from reviewing the National Aeronautics and Space Administration Raw Task Load Index (NASA-TLX; Hart and Staveland, 1988) Single Ease Question (SEQ; Sauro and Lewis, 2016), and Situation Awareness Rating Technique (SART; Taylor, 1990). This work presents an exploratory evaluation of the validity and reliability of the Brief Nuclear Usability Measure using real-world data collected from four separate and independent human factors studies that utilized licensed operators during operator-in-the-loop studies. The intent of this work is to provide an assessment of the utility of this measure as a practical tool to evaluating situation awareness and workload for prospective human factors tests and evaluations for both modernization efforts and advanced reactor development.ReferencesKovesdi, C., & Joe, J. (2019, February). Exploring the Psychometrics of Common Post‑Scenario Human Factors Questionnaires of Workload, Situation Awareness, and Perceived Difficulty. In 11th Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies, NPIC and HMIT 2019 (pp. 1631-1643). American Nuclear Society.Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. In Advances in Psychology (Vol. 52, pp. 139-183). North-Holland.https://www.eia.gov/pressroom/releases/press542.phpSauro, J., & Lewis, J. R. (2016). Quantifying the user experience: Practical statistics for user research. Morgan Kaufmann.Taylor, R.M. (1990). Situational Awareness Rating Technique (SART): The development of a toll for aircrew systems design. In: AGARD Conference Proceedings No 478, Situational Awareness in Aerospace Operations. Aerospace Medical Panel Symposium, Copenhagen, 2nd -6th October 1989.U.S. Nuclear Regulatory Commission. (2012). Human Factors Engineering Program Review Model, NUREG-0711, Rev. 3. Washington, DC: U.S. Nuclear Regulatory Commission.

Casey Kovesdi

Conference Proceedings

Enhancing the Onboarding Experience with Wearable Technology for Research Applications

Recent advancements in wearable technologies like the Apple Watch, Samsung Galaxy Watch, and Empatica EmbracePlus have revolutionized the real-time monitoring of physiological parameters. However, integrating such technologies into research settings hinges on the seamless onboarding of participants that are unfamiliar with these devices. Our project, conducted at a large R1 university, investigated how procedural steps and participant instructions in the onboarding and setup processes affect user interaction with these sophisticated technologies.Our methodology consisted of a multi-phase study starting with a front-end analysis that established fundamental user interactions with the devices and identified potential onboarding challenges. Subsequent phases involved cognitive task analysis and iterative testing with engineering students, focusing on user registration, app installation, device pairing, and data synchronization. Key interventions included simplifying login procedures and enhancing the instructional clarity of device setup. User feedback was integral, collected through surveys and direct observation, ensuring a user-centered design approach.Initial findings indicated several user-technology interaction challenges, particularly with complex login credentials and device pairing. Suggestions for improving these tasks have been explored and discussed. The study emphasizes the importance of human-centered design in the deployment of wearable technologies in research settings. Our findings indicate that even minor, focused alterations in the onboarding process can notably enhance the efficiency of technology adoptions within research environments. This research highlights the transformative potential of wearable technologies in academic data collection, emphasizing the crucial role of user-friendly design. Our findings demonstrate strategic design modifications that can significantly improve the efficiency and effectiveness of wearable technology usage in research settings.

Sara Amani, Noor Obeidat, Thomas Ferris, Kristi Shryock

Conference Proceedings

When hearing protection makes you worse at your job: objective measurement of decrements in sensorimotor tracking

Occupational hearing loss (HL) is a significant problem worldwide, even though it can be mitigated by the wearing of hearing protection devices (HPDs). When surveyed, workers report that worsened work performance while wearing HPDs is one reason why they choose not to wear them. However, there have been few studies to supplement these subjective reports with objective measures. In this study, listeners heard commands from the Coordinate Response Measure (CRM) corpus (i.e., sentences of the form "Ready <call sign> go to <color> <number> now). CRM sentences informed listeners of which of nine moving on-screen objects to track with a computer mouse (e.g., "blue four" refers the listener to a blue square). The commands were presented in background street noise and were heard under No HPD or HPD wearing conditions. HPD wearing was simulated with a digital filter meant to mimic the attenuation profile of an HPD. Continuous recording of tracking error allowed the simultaneous examination of how HPD wearing impacted speech comprehension, the accuracy of tracking, and how tracking accuracy varied as a function of time on task. Listeners spent less time tracking the correct object in the HPD wearing condition. Tracking error, after trimming data to those time points in which the target object was known, showed worse performance for the HPD condition than the No HPD condition. Workers' complaints of poorer performance while wearing HPDs are justified and extend beyond just auditory situational awareness. Considering these aspects of performance will be an important part of addressing HPD non-use in occupational settings.

Matthew Wisniewski

Conference Proceedings

Bridging the Gap: Enhancing Mobility and Usability in Industrial Devices for Operational Efficiency

A shift from traditional pen and paper to advanced industrial devices can pose significant ergonomic challenges that impede efficiency and adoption, especially among refinery workers on the front lines. Due to usability and mobility issues, frontline workers in these industries resist adopting new technology which get in the way of their daily work. Consequently, duplication of work, manual data entry and human errors become common occurrences in this safety critical environment, where accuracy and timely data collection is key. In this paper, we present a mixed-methods case study to highlight the effectiveness of a user-centric approach to enhancing technology adoption, by prioritising human factors and ergonomic design principles. A design research exercise was conducted with 15 refinery operators leading to an iterative development process with continuous feedback sessions. This systematic approach allowed us to address user pain points, optimise their daily work, and improve their acceptance and adoption of mobility devices. Post-intervention data showed a significant increase in user satisfaction from 2/10 to 8/10 and a significant surge in device usage.

Bahar Khayamian Esfahani, Souleymane Boundaouda Camara, Rita Bourma

Conference Proceedings

The Impact of Digital Device Configuration on Elementary Students' Experience of Writing Traditional Chinese Characters: A Preliminary Study

The rapid development of digital devices and online learning platforms has increased the flexibility of education. However, younger elementary school students still struggle to learn Traditional Chinese in the digital environment. The purpose of this study was to investigate the effects of various digital equipment configurations on Chinese traditional writing on screens. Because of the numerous differences in device settings and setups, preliminary studies are necessary to eliminate ineffective parameters, thereby reducing experimental costs and minimizing the strain on children.In this study, 32 adult participants were recruited through experimental, observational, and interview methods. The variables were eight equipment configurations, visual line smoothness, smoothness of forearm movements, overall comfort, and the number of visual switches. The results revealed that the “horizontal dual-screen configuration” provided the most comfort overall, while the “vertical dual-screen configuration” had the least visual switches. These quantitative findings are further supported by the interview data, indicating that orienting the devices in the same direction may create a smoother viewing experience. However, left-right layouts with irregular screen angles can cause issues such as discontinuous vision and insufficient viewing distances.

Tzu-hsin Kao, Johan Chang

Conference Proceedings

Understanding Stress Responses: Exploring Facial Expressions in the Context of Individual Performance and Automated Agents

Understanding and effectively detecting stress is paramount across various domains, including healthcare and business, where individuals often operate under pressure. This paper proposes a novel approach that employs facial expression analysis to discern stress levels during both stressful and non-stressful phases. Our study aims to understand the impact of automated agents on individual performance and how performance, in turn, influences facial expression dynamics. Utilizing facial video data, we scrutinize the facial expressions exhibited by individuals under induced stress conditions, comparing them with relaxed states. Building upon prior research in stress detection, we conduct in-person experiments to study facial expressions indicative of stress responses, examining features such as facial muscle movements, microexpressions, and overall expression dynamics. Machine learning techniques are leveraged to classify stress levels based on facial expressions extracted from video data. Preliminary findings reveal distinct patterns of facial expressions associated with stress, encompassing heightened muscle tension, altered facial symmetry, and changes in expression intensity. By contrasting these patterns between stressful and non-stressful phases, our objective is to formulate a robust model for real-time stress detection using facial analysis. This research contributes to the advancement of stress detection methodologies, offering potential applications in healthcare, psychology, and human-computer interaction. Future directions include refining the classification model and exploring additional contextual factors that influence facial expressions during stress.

Lokesh Singh, Sarvapali Ramchurn, Yi Dong

Conference Proceedings

Mapping the Evolution of Tangible User Interface: A Bibliometric Analysis and Future Trends

In today's digital era, user-computer interface experiences are increasingly intuitive and immersive. Tangible User Interface (TUI) enables users to interact with digital content through physical manipulation. This design paradigm, emphasizing interaction with physical objects, garners significant attention from academia and industry. Literature review helps to strengthen the knowledge framework of research topics by reviewing relevant literature, and it aids in summarizing the current research status. Although this field has achieved certain research results and practical applications after years of development, the extensive and interdisciplinary nature of the literature makes it difficult to systematically analyze the research hotspots and trends through traditional literature review methods alone. Therefore, this study utilizes relevant literature collected from the Web of Science database as the data source. Through bibliometric analysis, it systematically reviews and visually analyzes the field of TUI to identify the progress and future trends over the past two decades.Method: This paper employs bibliometrics, content analysis, and information visualization. Bibliometrics, first proposed by Pritchard in 1969, quantitatively analyzes diverse literature data to uncover patterns and insights. To obtain more rigorous and comprehensive data indicators, this study integrates the use of CiteSpace and VOSviewer. CiteSpace and VOSviewer are bibliometric analysis tools that run on JAVA programs and can effectively establish mapping relationships between literature knowledge units. Visual analysis and research lineage sorting are conducted across the distribution of literature outputs by year, country, research organization, keyword clustering, and co-citation of literature entries in this study. This study selects the Web of Science core database for retrieval. The search strategy is set as TS=((tangible user interface design OR TUI design OR physical user interface design)). The five major citation indexes in the WOS database, including SSCI, SCI-Expanded, A&HCI, CPCI-S, and CPCI-SSH, are selected as retrieval sources. To avoid the loss of interdisciplinary literature, no reduction is made to the literature sources. The retrieved literature is exported to a txt file in the format of "full records and cited references". Irrelevant articles, such as those deviating from the research topic or containing duplicate data, are removed. In the end, a total of 3994 articles were obtained (from 2004 to 2023).Conclusion： The output of literature related to TUI peaked in 2019 and has since exhibited a declining trend. Few institutions are highly productive in this field, with Massachusetts Institute of Technology, Carnegie Mellon University, University of Washington, Tsinghua University, University of Tokyo being core institutions in academia. Through keyword clustering analysis, TUI research content can be classified into four categories: #1 Physical Interaction Technology, #2 Sensory Simulation, #3 Intelligent IoT, #4 User Behavior Study. Analysis of the evolution of TUI hotspots reveals that the current focus of most scholars is on enhancing TUI's application in virtual reality and augmented reality environments, as well as innovative applications in education and entertainment. Future research may concentrate on the integration of TUI with artificial intelligence technology, human-centered computing, and human-robot interaction.

Zhitao Yu

Conference Proceedings

Information availability and accessibility regarding ecological products offered in online stores – a case of retail chains

The global impact of increasing environmental pollution and the impending climate crisis are now becoming central concerns of modern-day societies at large. More than ever before, enterprises that introduce products to the market find themselves under pressure to take ecological actions and provide eco-friendly solutions. A large role is also played by consumers, whose everyday decision-making when selecting or buying products strongly affects the processes occurring on the market. However, for members of society to be able to make informed choices of products, they must be able to gain sufficient knowledge and information about them.The aim of the study was to assess the availability of information concerning organic products on the websites of the largest retailers in Poland. The research method used was an elaborated questionnaire to assess the availability and accessibility of environmental information on store websites. In total, 10 selected e-shops were evaluated. The study was limited to examining only the offer of food products, so that the results could be comparable.The obtained results suggest that there is a very large difference in the approach to providing consumers with knowledge about the impact of sold products on the environment. What is more, the assessed e-shops lacked direct links to subpages with eco-friendly or organic products. Only in a few cases did retailers decide to use additional, larger eco-labels, such as the EU organic logo. In most cases, the only way to recognize an ecological product was to observe photos of the offered products, which were often characterized by low resolution and small size.The development of e-commerce means that an increasing number of products are sold through this channel. In the case of traditional trade, many solutions have already been developed that can substantially bridge the information gap, thus allowing consumers to make more informed decisions.The obtained research results refer to the situation on the Polish market. However, the overall conclusions are rather disturbing. The analysis of the conducted research prompts to take actions and measures to achieve significant improvement in the availability, accessibility, and ease of identifying eco-friendly and organic products in e-commerce.

Natalia Kozik, Bartłomiej Kabaja, Dainora Gedvilaitė

Conference Proceedings

Investigating effectiveness of distraction rate: augmented reality-based eye-tracking feature to predict student formative and summative performance

Augmented reality (AR) is gaining attraction as a valuable aid in training and educational settings. However, the cognitive overload due to the new learning environment may hamper effective learning during the AR sessions. For this reason, monitoring students learning status with an effective metric is required. Distraction rate (DR) is a feature extracted from a student’s eye-tracking coordinates data developed to measure the distracted proportion of a student in an AR learning session (Deay, 2023). In this study, we investigate DR with students’ formative and summative assessment outcomes to validate its effectiveness as a predictor for student performance.Methods: To do this, students learned a topic of biomechanics through several AR modules. The results of quizzes taken after each AR module and their class exam outcomes taken at the end of semesters provide formative and summative evaluation performances, respectively. The data were collected in two years in the same setup. To compute DR, the standard eye-tracking coordinates, called baseline, and those of an observed student are compared. In order to reduce false alarms, two sources of noise are accounted for. First, temporal noise caused by quick deviations from the baseline that only lasts for a short period of time is removed by computing the moving average of eye-tracking curves. Second, spatial noise caused by slight deviations in a student’s sight from the virtual instructor is reduced by applying a threshold to determine whether the deviation is large enough. Finally, the proportion of moving average signals exceeding the threshold is computed.Using mixed effects logistic regression models, this study shows how DR and students' performance are related while considering the year and student variations. To extract DR from eye-tracking data, two parameters should be determined, the window size and threshold. In this study, we carried out a comparison study with several parameter values with respect to the model’s prediction performance to find the best parameter tuning.Key Findings:For the formative performance, the results indicate that DR is a significant predictor for the probability of correct answers. For the summative performance, DR does not show a significant relationship with students’ exam scores, yet the negative regression coefficient of DR can be still found, indicating that the high DR value results in low performance in the exam. It can be interpreted that, due to the time interval between AR learning and exams, even if some students may have not paid much attention during the AR learning sessions, they could catch up on the material later by themselves. Overall, it is found that the exam performance is less sensitive, compared to the quiz performance, to students’ attention paid to AR learning sessions. Accordingly, the relationship between DR and summative performance is likely to be weaker than the case of formative assessment.

Sara Mostowfi, Kangwon Seo, Jung Hyup Kim, Danielle Oprean, Fang Wang, Yi Wang

Conference Proceedings

Comparing the Efficacy of Virtual Reality Training, Augmented Reality Instruction and Traditional Paper-Based Instruction Methods for Assembly Tasks

The landscape of instructional methods is continually evolving, driven by advancements in technology. Virtual Reality (VR) and Augmented reality (AR) are emerging technologies offering innovative approaches to training and providing real-time assistance. In order to compare the efficacy of these methods in assembly tasks, in this study, 24 participants were randomly assigned to three groups: one group used paper-based instructions, while another used instruction displayed through the HoloLens 2.0 (AR), and the remaining group was trained in a fully immersive VR environment and were asked to perform the same assembly task afterward. The participants were tasked with assembling a monster truck Lego set, and their performance was measured using objective metrics such as completion time and the number of errors made. Subjective measures were obtained through the NASA Task Load Index (TLX) questionnaire, which assessed the perceived workload of each instructional method. Participants using paper-based instructions completed the task in an average of 5.92 minutes, which was significantly faster than those using AR (average completion time of 8.21 minutes), and those using VR training (average completion time of 7.23 minutes). The number of errors was highest with the VR training, averaging 2 errors per participant, compared to the paper-based instructions (0.625 errors) and AR (1.25 errors). Subjectively, participants rated the AR experience slightly higher, with an average NASA TLX score of 23.26, compared to 26.25 for VR training. Paper-based instructions had the lowest workload value, with a mean NASA TLX score of 17.60. The findings suggest that while VR and AR offer advanced learning experiences, they may not always outperform traditional paper-based instructions in terms of task completion time and error rates. These results emphasize the need to consider task complexity and user experience when evaluating instructional methods. Further research is needed to explore the benefits of VR and AR in different contexts.

Md Abdullah, Vibhav Nirmal, Mahmudur Rahman

Conference Proceedings

Simulator Sickness and Performance in AR vs VR: A Comparative Analysis Applied to Additive Manufacturing

Augmented Reality (AR) and Virtual Reality (VR) technologies are increasingly becoming integral to educational and training contexts, yet comparative analyses of their effects on simulator sickness and user experience remain limited. Recent advancements in AR/VR headsets, such as the Meta Quest 3, now allow virtual and augmented reality experiences to be delivered through a single device. However, previous research comparing user experiences between virtual and augmented reality did not account for the use of a unified headset in their investigation. This study aims to investigate the differential effects of AR and VR on users’ simulator sickness, engagement, mental workload, and performance, and usability of the training environment. A training module was developed in Unity 3D for both AR and VR focusing on 3D printing using a powder bed fusion (PBF) printer. A within-subject assignment of factors explored the comparison of ten participants’ experiences regarding simulation sickness and printing experiences and performances. Each participant went through the same tasks under simulated environments to explore the implications of AR and VR on user experience. The study found that there was no statistically significant difference in motivation and user experiences between AR and VR using Meta Quest 3. Moreover, the users experienced comparatively higher simulator sickness in VR than in AR. These findings will not only help to fill the gaps in comparative studies of AR and VR but will also help to inform future technological deployments in educational and professional training scenarios.

Tazim Ahmed, Jose Lopez, Soptorshi Rai, Yiran Yang, Mahmudur Rahman

Conference Proceedings

Light-Tracing: A Novel Approach for Mixed-Reality (MR) Content Creation

Mixed reality (MR) technology combines digital elements with the real world, offering immersive experiences in various fields. However, content creation in MR remains challenging for average users due to complex 3D modelling techniques. This paper introduces Light-Tracing, a novel system integrating light painting with MR environments using a robotic arm. Light-Tracing allows users to intuitively create 3D models through path light painting, which AI tools convert into digital assets. The system simplifies spatial content input, making MR content creation more accessible and enhancing user experience. Evaluations demonstrate its positive impact on usability and immersion. Importantly, Light-Tracing lowers the barrier for MR content creation and opens new possibilities for participatory design in urban planning and vehicle customization, highlighting its potential to revolutionize MR content creation.

Ruilin Huang, Yining Ge, Lu Chen, Chi Ma, Cong Fang, Le Fang, Xingtong Chen, Yangfan Cong, Stephen Jia Wang

Conference Proceedings

Enhancing Construction Industry Training Through Augmented Reality: A Study of Student Inspectors

In the construction industry, ensuring timely and precise material installations is paramount. However, reliance on two-dimensional representations of three-dimensional structures in paper documents often leads to errors and inefficiencies, particularly among inexperienced installers. With seasoned professionals leaving the workforce, there is a growing expertise gap, undermining the industry's ability to deliver high-quality products. Augmented Reality (AR) emerges as a promising solution to these challenges, offering enhanced training and comprehension opportunities. This study evaluates the reliability of AR devices for construction inspections, focusing on their potential to bridge the aforementioned skills gap and improve quality control procedures. The research replicates a typical construction scenario involving the positioning of underground utilities before concrete placement, emphasizing the importance of accuracy in layout and placement. Results indicate significant differences in accuracy and precision among AR devices, with the HoloLens demonstrating superior performance. Despite not meeting stringent industry requirements in this study, AR tools show promise as educational resources, fostering active engagement and improving student comprehension. Future research should address environmental factors, sample size limitations, and disparities in device operation to further refine AR effectiveness in construction inspections. Leveraging AR's immersive features can lead to a transformative shift in educational paradigms within the industry, revitalizing productivity, and quality control practices for future success.

Jeffrey Kim, Darren Olsen

Conference Proceedings

CreteAR: Enhancing Learning Experiences through Tangible Transformable Artifacts and Extended Reality

This paper discusses the design and development of CreteAR, a system that integrates Extended Reality (XR) with a transformable physical model of the island of Crete to enhance learning experiences. CreteAR features an XR application for handheld devices that overlays information on a scale model, which is equipped with mechatronics to elevate or conceal showcases containing culturally significant items. Users can interact with both the digital content and the physical model, activating the showcases and accessing information through a companion display. The paper explores relevant literature, analyzes similar systems, and details the design process, including user requirements and expert feedback. CreteAR was initially conceived as a prototype, but it holds the potential to contribute to the development of broader applications across various domains beyond the scope of Crete's geography and heritage. It was designed to deliver an immersive and hands-on learning experience, emphasizing social interaction and cooperative exploration, engaging users in dynamic and meaningful interactions.

Antonios Tosios, Asterios Leonidis, Maria Korozi, Nikolaos Menelaos Stivaktakis, Emannouil Apostolakis, Michalis Roulios, Spiros Paparoulis, Emmanouil Stamatakis, Constantine Stephanidis

Conference Proceedings

Enhancing Motorcycle Safety through Augmented Reality: Design and Development of a Smart Helmet Prototype

Motorcyclists, often regarded as some of the most vulnerable road users, encounter many hazards on the road, ranging from swiftly altering weather conditions to vehicles hiding in their blind spots. Traditional helmets provide physical protection but they lack the capability to enhance situational awareness. Recent advancements in motorcycle safety include the development of Advanced Rider Assistance Systems (ARAS), connected motorcycle technologies, and wearable technology such as smart helmets with embedded sensors. Augmented Reality (AR) Head-up Displays (HUDs) offer real-time information overlays for riders, while artificial intelligence is utilized to analyze rider behavior. This paper introduces a prototype helmet incorporating a pair of AR smart glasses in order to provide enhanced situational awareness and safety, as well as an improved overall riding experience through its comprehensive suite of features. The Smart Helmet aims to provide an immersive and intuitive interface for riders to access critical information without distractions, whereas by consolidating multiple functions into a single device, it offers convenience and efficiency, eliminating the need for riders to juggle multiple gadgets or systems while riding. Through its immersive interface, it overlays real-time information directly onto the rider's frontal visual field, including GPS navigation prompts, weather condition notifications, and visual alerts for vehicles in blind spots. In addition to visual information, the Smart Helmet employs voice commands to enable hands-free control of various functions, such as turning on the rear camera for enhanced rearward visibility, activating Advanced Driver Support System (ADAS) features, or transmitting important information in case of an emergency. Finally, through artificial intelligent the helmet can recognize obstacles ahead and issue timely visual and auditory warnings to prevent accidents. The incorporation of multiple modalities was considered an absolute necessity considering the application domain, which in turn offers a more natural and intuitive interaction paradigm.The design process of the Smart Helmet followed an iterative User-Centered Design (UCD) approach, beginning with an extensive literature review on smart helmets, AR technologies, and road safety applications. This review identified gaps and defined key system features. Interviews with motorcycle users and brainstorming sessions with interaction designers were conducted to gather insights and generate ideas. Subsequently, a prototype was created, featuring a common helmet in which various sensors were embedded and AR glasses were properly mounted, so as to evaluate and test the design concepts. Finally, a heuristic evaluation was performed to assess the prototype's interaction usability and identify areas for improvement, before proceeding with user testing.This paper presents a thorough analysis of related systems and a comprehensive literature review, laying the foundation for the design and development of the Smart Helmet. It elaborates on the iterative design process undertaken, detailing the conceptualization, user requirements gathering, and incorporation of feedback from experts. The functionality of the prototype is described in depth, highlighting its innovative features and how they address identified user needs and safety concerns. Finally, the findings of the heuristic evaluation conducted on the Smart Helmet prototype are discussed, providing insights into its usability, safety, and user experience.

Georgios Gerentes, Asterios Leonidis, Nikolaos Menelaos Stivaktakis, Maria Korozi, Constantine Stephanidis

Conference Proceedings

Design of Human-Machine Interface for Truck Platooning Using Driving Simulator

Environmental and energy problems as well as countermeasures of the driving burden of truck drivers are critical issues in the logistics industry in Japan. As a solution to these problems, concerns regarding autonomous truck platooning of heavy-duty trucks are heightened globally. The actual operation of truck platoon systems in which trucks are unmanned is considered in limited traffic environments, such as expressways. The lead truck driver should confirm the safety of not only his/her truck but also those of the trailing truck(s). This study designs and evaluates a Human-Machine Interface (HMI) for the driver of the leading truck in an unmanned truck platoon using a driving simulator (DS). The HMI was assessed through a combination of objective evaluation of driving behavior, biometric data, and subjective feedback gathered via a questionnaire. The results demonstrated that the driver of the leading truck could effectively change lanes using the proposed HMI, and the inclusion of a bird’s-eye view significantly improved driver acceptance.This study proposes an HMI that incorporates mirror image displays and a bird’s-eye view as in-vehicle HMI components.1.Mirrorless Image Display:When the driver of the leading truck in a platoon checks the safety of the surroundings, it is crucial to visually confirm the side mirrors and rear monitor. The position to be displayed by the camera in the platooning is considered, and the image display is adapted to the safety confirmation of the drivers in the platoon.2.Bird’s-Eye View Display:In addition to the selected mirror images, this study proposes a bird’s-eye view that facilitates understanding the positional relationship with other trucks when confirming safety. In this study, the DS is used to measure the driving behavior of the participants. Biometric measurements are also taken to assess psychological burden. Furthermore, a questionnaire is conducted as a subjective evaluation, and a comprehensive assessment is made by integrating these results with the objective evaluation of driving behavior. The effectiveness of the proposed HMI was demonstrated through the DS experiment results.

Toshiyuki Sugimachi

Conference Proceedings

Technology relationship, algorithmic thinking and task performance with UxV

There is evidence that subjectively assessed technology relationship, sense of self-efficacy, algorithmic thinking and operation with unmanned vehicles are in correlation. The complex skillset required for both operators and UxV operators requires understanding on nature of information, algorithmic, computational, and epistemic thinking. Based on framework of algorithmic thinking this paper connection between algorithmic thinking, technology relationship, and task performance in operation supported with fleet of unmanned land vehicles. The paper is based on extensive quasi-experiment (n=500) in simulation environment. Key results presented are related to connections between different personal attributes, digital literacy and tasks performance with autonomous systems in the battlefield.

Jussi Okkonen, Mia Laine, Christian Andersson

Conference Proceedings

Enhancing User Satisfaction and Accessibility in VR: A Comparative Analysis of Different User Interfaces

In recent years, virtual reality (VR) technologies have improved and become more affordable, leading to an increased adoption of VR in healthcare, manufacturing, education, and other industries. To facilitate further growth, human factors engineers and software developers must work hand in hand to ensure that virtual reality technologies are easy to use by as many populations as possible. This research investigates how different user interfaces can improve a VR user’s experience, with accessibility incorporated into the design. Three interaction modes were tested: traditional VR headset controllers, hand tracking, and gaze interaction. All three interaction modes were tested in a CNC Hybrid Machine training simulation similar to those used in industry. The simulation was created using the Unity game development engine for the Meta Quest 3 VR headset. The satisfaction of the participant with each interaction mode was indicated using presence, usability, and mental workload surveys given after each interaction mode experience. The results of the participants’ surveys indicate that participants liked using controller mode the best. Gaze tracking was the second favorite because of its simplicity, ease of learning, and seamless multitasking with it. Hand tracking was the least favorite due to difficulties interacting with objects. Future development to improve hand tracking technology in the Meta Quest 3 could improve users’ interaction experiences.

Faith Sowell, Daniel Rodarte, Yiran Yang, Shuchisnigdha Deb

Conference Proceedings

Reflections and Insights on Haptics’ Influence on Human Factors Within Virtual Environments

The present work discusses the influence of different haptic feedbacks and devices on two selected Human Factors (Motion Sickness and Technology Acceptance) that are strongly relevant for User Experience analysis in Virtual Environments. With this work, we aim to stimulate: (i) practitioners to consider human factors in the selection of the right type of haptic feedback and device; (ii) researchers for future in-depth studies by highlighting some grey areas of current literature about haptics and their influence on Human Factors.

Sara Buonocore, Francesca Massa, Lisa Guadagno, Giuseppe Di Gironimo

Conference Proceedings

Design of fire escape system for children based on VR technology

Fire is one of the disasters that threaten people's lives and property safety, and mastering correct fire escape skills can greatly reduce the casualties caused by fire. Most of the traditional fire escape education is carried out in the form of fire escape drills, lectures, etc. Although it has played an educational effect to a certain extent, it can't build a safe and experiential interactive platform for people. In view of this, the design scheme of fire escape system based on VR technology is proposed, and the process and framework of the system are given at the same time; the key technologies in the platform are discussed and researched; and the logical idea and realization method of the interactive function using C# language in Unity 3D are elaborated in detail.

Aijun Wang

Conference Proceedings

User Experience of Virtual Reality in Healthcare Clinical Training

Background: The field of healthcare education is constantly in search of new and creative solutions to various problems. One such solution that has gained significant popularity is the use of virtual reality (VR) technology to enhance healthcare clinical education and training. Despite its widespread use, there is a dearth of research on how to optimize the learning and immersive experience offered by VR in the context of healthcare clinical training.Objective: This integrative review aims to thoroughly examine the user experience of virtual reality in healthcare education, utilizing existing research cases as a basis. The purpose of this paper is to offer insights into the following research inquiries: What dominant factor can be used to evaluate the user experience of virtual reality in healthcare education? In medical training, What are the special precautions for VR user experience?Data sources: An extensive search was conducted using virtual reality in healthcare clinical training for scientific research data between 2018 and 2024. The search encompassed databases such as PubMed, IEEE Xplore, and Google Scholar. The search retrieved 10 original articles, which were quality-checked and included for review based on the search criteria.Results: After extensive research of case studies in existing literature, we have developed a deeper understanding of the user experiences of medical students and faculty in virtual reality. Our analysis has revealed dominant factors that influence the virtual reality user experience. These insights will ultimately enhance the effectiveness of virtual reality training for medical learning, providing trainees with a more efficient and rewarding experience.

Lizhu Zhang, Cecilia Xi Wang

Conference Proceedings

Virtual Experiential Design in the Context of Intangible Cultural Heritage: A Case Study of filigree VR design

This paper delves into the application of virtual reality (VR) technology as a solution to the challenges encountered in the preservation and advancement of intangible cultural heritage. Taking the Beijing Filigree VR design as a focal point, this study maximizes the immersive, interactive, and multisensory attributes of VR technology to conceptualize and produce virtual experiential products tailored to Filigree. The investigation examines the merits and distinctive features of virtual reality technology in the dissemination of intangible cultural heritage, including its ability to faithfully recreate authentic scenes and cultural significance, broaden the modes of intangible cultural transmission, and augment audience interaction to fortify the overall user experience. Throughout the design research process, the ICE design model (Insight-Create-Experience, Model) is formulated, providing a lucid research framework for VR design. In the creation phase, the interface design is fine-tuned employing a user experience hierarchy model, thereby facilitating virtual teaching and simulation exercises related to Filigree. This study introduces a novel perspective and methodology for the dissemination and conservation of intangible cultural heritage, establishing a theoretical basis in design for the advocacy and perpetuation of such heritage, exemplified by Filigree.

Yue Gu, Jintao Liu, Yuxuan Li, Yulu Hu

Conference Proceedings

Performance of Fire Fighters in a Multiple-Sensory VR Pump Panel Training Simulation

Virtual reality (VR) simulations have emerged as valuable tools for training and education, allowing learners to engage with realistic virtual environments. This study investigates a novel VR training simulation that integrates visual, audio, haptic, and olfactory cues. Participants (N=54) learned a specific sequence of interactions for operating the Super Soaker 5000 pump panel and were subsequently tested on their ability to replicate these steps. Demographic data and sense of presence questionnaires were collected. The research reveals intriguing findings. While the combined sensory conditions enhanced participants’ sense of presence, they did not significantly impact final pump panel test performance. However, an essential factor emerged: the amount of time spent during the learning phases significantly affected final test outcomes. These results prompt further exploration into optimizing training duration and refining the integration of sensory modalities in VR simulations. This paper discusses the study’s results, the implications for training effectiveness, and the need for future research. By understanding how sensory cues influence learning outcomes, educators and practitioners can enhance VR training experiences and better prepare learners for real-world scenarios.

Scott Ledgerwood, Erika Gallegos

Conference Proceedings

Effects of Daylight Intensity on Emotion Regulation in a Virtual Healing Space

With increasing social pressure, the youth population in colleges and universities generally faces increasingly severe negative emotional problems, which not only affect academic performance but also significantly reduce the quality of daily life. In response to this challenge, numerous educational institutions have established psychological healing rooms to provide emotional support and stress management services. However, existing psychological healing spaces often fail to achieve the expected healing effects and affect student engagement due to a lack of sufficient privacy and interactivity. To address this issue, this study proposes a virtual psychological healing space design based on the audiovisual fusion effect, aiming to improve students' emotional regulation and mental health management by enhancing privacy and interactivity. The design prototype incorporates four natural environments: water and sky, woodland and sky, grassland and sky, and elemental uniform distribution environments. Each environment is paired with customized Lofi music to enhance the healing effect through a multi-sensory experience. Additionally, by utilizing Unreal Engine's dynamic sky and weather simulation system for natural light, real-time transitions between four lighting environments (early morning, midday, dusk, and night) were achieved in virtual reality to explore the specific effects of light intensity on emotion regulation. This study surveyed 30 college student participants to collect the subjective effects of environmental lighting on emotions in a virtual healing space through semi-structured interviews. This study demonstrates that varying lighting conditions have a significant impact on participants' emotional states. It underscores the critical necessity of customizing lighting to accommodate the specific needs of users in the design of virtual healing spaces, thereby minimizing the influence of inter-individual differences on therapeutic outcomes. The results of this study provide an empirical basis for designing virtual healing spaces and are expected to offer a theoretical reference and practical basis for implementing personalized healing strategies in virtual environments.

Han Zhang, Diyu Zhou

Conference Proceedings

FULL PAPER ONLY: Virtual Reality and Extended Reality for training of operators

Training on field for operators of confined or suspected polluted environments is very challenging for guaranteeing safety of attendees and adapting the scenarios to many different environments and risks. In this context Inail realized in collaboration with universities, through a call for bid “SIDE - Development of an exoskeleton for simulated dynamics and haptic interface”, a bi-articular robotic system for the upper limb that can be interfaced with virtual or augmented reality systems. This robotic system can physically reproduce "virtual" stresses of force/contact interaction of the upper limb in a controlled virtual environment, simulating human/environment interactions. In this way, the simulation provides real-life experience: the use of tactile sensation offers the perception of physical effort in a confined space under normal operating conditions and in emergency situations. This simulation helps workers to experiment, facilitating accurate learning of relevant knowledge, skills, and emotions. The solution allows operator to wear visors, the wearable robot (think of a backpack to which a haptic robotic limb is connected) and find yourself in a confined space in virtual reality. Patent application no. 102023000023538 has been filed for this system. The scenario reproduced in virtual reality is a hostile environment - for example, a confined and/or suspected pollution environment - in which the worker had to perform a task in a place very hard to reach and/or with a quantity of oxygen - available limited or with a bad air quality. Thanks to the pre-acquired skills in the motor task carried out in VR, it is possible to obtain a fundamental difference in terms of safety. In this paper we will describe the solution focusing on the characteristics of interaction between the reality and the VR scenario.

Alessandra Ferraro, Daniela Freda, Marco Pirozzi, Eduardo Palermo, Luciano Di Donato

Conference Proceedings

Patient Gender Treatment Gaps in Tactical Combat Casualty Care of Gunshot Wounds Mitigated by Training Experience

Optimizing Tactical Combat Casualty Care (TCCC) in the golden hour of care is critical to improve patient outcomes. Previous research demonstrates performance gaps in treating female soldiers compared to their male counterparts. This study examines TCCC performance of N = 29 combat lifesavers and Reserve Officers’ Training Corps cadets presented with two high-fidelity simulators, male and female, experiencing polytrauma. Participants were less likely to locate the female’s gunshot wound (GSW) to the chest and more likely to commit sealing errors. There was a significant patient gender x order interaction with more sealing errors and longer times to expose the female patient when the female was presented first. More training experience with female human patients was significantly associated with greater success in locating GSWs and fewer sealing application errors. A follow-up analysis found the beneficial effect of practice with female humans remained when controlling for practice with male humans.

Nichole Morris, Curtis Craig, Bradley Drahos, Katelyn Schwieters, Eugene Floersch, Mark Mazzeo, Jack Norfleet

Conference Proceedings

Integrating Machine Learning With Resilience Models To Assist Hospital Resilience improvement

Healthcare systems have become increasingly fragile due to growing rates of burnout, depression, distress, and subsequent workforce shortages since the COVID-19 pandemic. Although researchers and institutions urgently called for hospitals and healthcare staff to build resilience to withstand, adapt, recover, rebound, or even grow from adversity, stress, or trauma, the ambiguous relationships between individual and organizational resilience are one of the major obstacles to the development of resilience in hospitals. The COVID-19 pandemic amplified the intersection of individual resilience and system resilience. It provided a good opportunity to discover the weak signals of cognitive behavior of healthcare staff that were ignored before the pandemic. The Patient Safety Culture Survey (PSCS) and the Employee Satisfaction Survey(ESS) are mandatory requirements for hospitals by the hospital accreditation. The PSCS has 46 questions in 8 dimensions. It aims to examine the dimensional strengths and weaknesses of hospitals’ patient safety culture. The ESS (39 questions, 7 dimensions) aims to understand how healthcare workers are satisfied with policy, management, team, job, etc. Both survey data include employees' feelings and attitudes about the work system and workload but have been used only for their designed purposes. Thus, the study aims to identify individual and collective weak signals from routine hospital survey data to proactively support employee retention programs and strengthen hospital resilience promotion activities.The study setting is a medical center. It collected 2020 – 2022 PSCS data including the emotional exhaustion questions adopted from the Maslach Burnout Inventory, and ESS data. First, we applied machine learning(ML) to determine which questions in the PSCS and ESS were associated strongly with workers’ resignation or retention. Next, based on the concepts of the multilevel organizational resilience model and the interplay model of individual and organizational resilience, we accordingly marked each determined question corresponding to individual or organizational resilience elements as a signal map for further improvement activities. Finally, by departments, we screened out the riskiest units to make suggestions for employee care and system resilience improvement. 3076 records of PSCS and 4521 in ESS were analyzed. The XGBoost method combined with 10-fold cross-validation was adopted in ML. By using SHapley Additive exPlanations(SHAP), the SHAP value of PSCS and ESS questions greater than 0.05 were selected as the most meaningful signals to resignation and retention accordingly. PSCS: questions S12 (education & training courses organized by our hospital) and S30, and ESS: questions Q14 (I like my job very much), Q16, Q27, and Q35 were identified for the retention signals. PSCS: question 27 (communication channels and methods of the hospital) and S30, and ESS: question 13 (has a culture that fosters colleagues to learn from others’ mistakes) and Q24, Q37 of ESS were identified for resignation signals. The determined questions were accordingly linked with the elements of individual resilience and organizational resilience by departments for future resilience improvement.The study provides a valuable framework that integrates with ML analysis to utilize the dynamic relationships between individual and organizational resilience and assist in future hospital resilience development.

Sheuwen Chuang, Kuei-miao Kuo, Jyun-wei Jhang, Jui-chi Lin

Conference Proceedings

Orange-Sweet Scent Reduces Stress Associated with Numerical Tasks: A Physiological and Psychological Evaluation

This paper evaluates the stress reduction effects of orange-sweet aroma at the perception threshold. The number of patients suffering from stress-related disorders is increasing, making it a significant social issue as stress can prevent individuals from working and interfere with their daily lives. However, completely eliminating stress from daily life is not feasible. Therefore, this research aims to identify a method for reducing stress within this social context, even when stress is present. Given the varying influence of scents on individuals, this study examines the stress-reducing effects of orange sweet essential oil aroma at the perception threshold. A sample of 20 university students (10 males and 10 females; average age 22 years) participates in the study. The experiment is conducted under two conditions: with and without the scent. The stress task, designed to eliminate the influence of computational ability, involves simple numerical computations performed under both conditions. To evaluate the effects of the aroma on stress reduction, multiple physiological and psychological indices are utilized. Physiological indices include electrodermal activity (EDA) and salivary amylase levels. Psychological indices include the short version of the Profile of Mood States 2 (POMS2), a Japanese questionnaire for work-related fatigue feelings called Jikakusho-shirabe, and a Likert scale questionnaire assessing scent preference and intensity. Electrodermal activity (EDA) significantly increased during the stress task compared to the rest condition. Additionally, the discomfort factor in the Jikakusho-shirabe increased after the task compared to before the task, but only in the absence of aroma. These results indicate that the stress task created in this study effectively induces arousal. Furthermore, the findings suggest that discomfort can potentially be reduced by the presence of orange-sweet scent at the perception threshold. However, the presence of aroma resulted in a significant difference only in the discomfort factor. In future experiments, we will focus on behavioral indices, such as poor performance, which cannot be determined solely by physiological or psychological indices.

Ayaka Yamada, Asako Noma, Takashi Sakamoto, Toshikazu Kato

Conference Proceedings

Improving Quality of Care through Tailored Medical Education in a Pathology Residency Program

Improvements in quality and safety in healthcare and reducing medical errors are imperative. Quality health care is defined as “the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge”. Postgraduate residency training programs are designed for residents to acquire competence through workplace-based clinical care provision and academic learning. Academic teaching helps consolidate basic and applied knowledge for quality patient care. Residency programs in Pathology, one of which is “Diagnostic and Clinical Pathology” aimed at general competence in clinical and laboratory medicine is heavily influenced by the changing landscape of practice and emerging technologies. Within the Diagnostic and Clinical Pathology residency program specifically, the best pedagogical approach to delivering academic (classroom-based) teaching to promote quality care, reduce medical errors, prepare for digital literacy and promote resource stewardship remains unclear. This study measured residents' perceptions of course satisfaction, ability to meet learning objectives and future clinical application across courses offered in three different pedagogical approaches (an introductory "Boot Camp" course utilizing traditional didactic lectures, interactive case-based sessions, and asynchronous learning based on pre-developed Modules). Specific topics related to quality care- among other topics – included, utilization, role as a laboratory professional, medical error, quality and safety, and self-efficacy of practicing required behaviors. Clinical scenarios, such as acetaminophen poisoning, provided a scaffolding for learning these aspects. Kirkpatrick level 1 “Reaction” was evaluated across satisfaction, engagement, perceived relevance and usefulness, emotional response and immediate feedback through a survey (10 questions for satisfaction, 7 for achievement of learning objectives, 1 for usefulness for clinical application and open-ended comments). Descriptive statistics were used for reporting quantitative data and key quotes/themes were extracted from the narrative comments. For all three teaching methods, most residents agreed that sessions were satisfactory (>80%), had met learning objectives (>75%), and were comfortable applying material for clinical applications (80%) The interactive case-based sessions scored highest, averaging 91%, 86% and 100% respectively in these three categories. Didactic teaching sessions and pre-developed modules had a wider range of disagreement amongst the residents, specifically related to time, opportunities for discussion and achievement of learning objectives. Open-ended responses highlighted case-based teaching as “bridging the gap between theoretical knowledge and clinical application” and articulated the need for more case-based teaching. While all three methods were well-received and met expectations, our study suggests that a difference may exist between pedagogical approaches to improve quality care. The boot camp provided foundational knowledge; the interactive cases consolidated learning, and the modules highlighted clinical relevance and applicability. Recognizing that most medical errors result from system and process issues and the centrality of high quality medical education to safe care, utilizing different modalities for academic teaching (across the system and emphasizing current and emerging topics) to complement workplace-based learning for deep and practical knowledge is essential for teaching Pathology residents. Future studies with a larger sample size and additional measures of engagement are needed to assess if an interactive case-based approach is a superior educational strategy.

Avani Saxena, Bryan Johnston, Jay Kalra

Conference Proceedings

Exploring Hand Dexterity in Spoon Handling : Impact of Handle Cross-Section on Dynamic Tripod Grip

Spoons are among the fine tools frequently used by toddlers who transition from early power grips to refined dynamic tripod grips. Research on fine finger manipulations reveals that such operations are more stable when performed with relatively small finger flexion and pressure changes. Existing literature on pencil and chopstick handling shows that the cross-section of the handle affects fine manipulation, but there is limited research specifically evaluating such effects with regard to spoons. To design a spoon suitable for dynamic tripod grips and facilitate learning for toddlers with less mature manipulative skills, experiments were conducted with adults who exhibit stable dynamic tripod operations. This study synthesized spoon operation literature and movement processes to identify three specific tasks: Scooping, Cutting, Gathering. Following an analysis of commercially available products, six common cross-sectional shapes were selected. Thirty adults with normal hand function participated in the experiment, wearing flexion and pressure sensors to assess the impact of handle cross-section shapes on operational efficiency, finger stability, and finger pressure. Results indicate that hexagonal and pentagonal shapes offer the best operational efficiency. No significant differences in finger stability were observed among the six shapes, and circular shapes allowed for better performances in finger pressure. Overall, the combined evaluation suggests that circular, pentagonal, and hexagonal shapes are preferable, providing a foundation for product development in this field. The applicability of these findings to toddlers can be further validated through future experiments.

Yu-chen Huang, Johan Chang

Conference Proceedings

Investigating the Impact of Vertical Floor Vibration on Cognitive Performance

As construction materials and techniques improve, yielding stronger but lighter building floor structures, and architectural drive continues towards open plan, slender, and transparent designs, modern building floor structures – although strong and robust – increasingly feature considerably reduced mass, stiffness, and damping. This means that the so-called floor vibration serviceability design considerations replace structural strength considerations when determining the size and shape of modern floors in buildings.Every vibration serviceability problem can be rationalized into vibration source, path, and receiver. In the case of building floors, the vibration receiver is most frequently human occupants of the floor. Of the three parts of the vibration serviceability problem, the human receiver of vertical floor vibrations is by far the least researched and understood. Strong evidence is emerging that the current set of building design standards proposing limits for vertical floor vibration are unreliable and not fit for purpose.This paper describes the first-ever attempt to determine the effects of vertical floor vibration on the cognitive performance of the office floor users. A brand new and worldwide unique research facility VSimulator (based at the University of Exeter, UK) was used for the first time in the context of floor vibration serviceability.The paper describes the testing protocol employed for and the pilot data gathered from the Visual Search and Stroop cognitive tests carried out in a US$7m+ research facility. The pilot data gathered from the first group of 12 test subjects indicate that increasing the VSimulator floor vibration has a considerable effect on the scores from the two cognitive tests. The affected scores indicate a potential reduction in the cognitive performance of the test subjects with the increasing level of floor vibration.More test subjects are scheduled to take part in these tests during 2024 and the results could form the basis of the new generation of floor vibration serviceability standards. These will be based on objectively measured cognitive performance rather than subjectively assessed levels of floor vibration with ambiguous descriptors such as "annoying" or "low probability of adverse comment".

Aleksandar Pavic, Ahmed Mohammed, Ian Walker, Alessandro Margnelli, Iason Pelekis

Conference Proceedings

Analysis of Pre-Flight and Monitoring Tasks Using Cognitive Performance Modeling

Pilot cognitive workload and errors significantly contribute to aviation incidents. Evaluations of piloting tasks in both simulators and real-world settings, along with computational models of cognitive task performance can help to identify cognitively challenging tasks early in the system design process and enhance user interface designs. This study applied cognitive performance modeling (CPM) to assess pilot task demands in pre-flight and monitoring using a UH-60V Black Hawk helicopter flight simulator. The objective was to propose potential flight checklist and subtask interface redesigns to reduce pilot working memory load and improve operational effectiveness. Initial analysis involved reviewing pilot instructions and logs for pre-flight checks, monitoring activities, and emergency responses. Actions, such as button presses, task errors and the duration between tasks were recorded. A Hierarchical Task Analysis (HTA) was applied to identify sub-task interdependencies. CPMs were developed using Cogulator and a variation on the GOMS language detailing cognitive, perceptual, and motor processes. Models focused on task sequences and cognitive process durations, revealing task time estimates, working memory load, and cognitive workload. Demanding subtasks were identified based on longer durations and/or higher workloads. Cogulator model outcomes for workload assessment were compared with pilot opinions on task difficulty for model validation. Recommendations for cockpit interface enhancements were formulated with the aim of streamlining sub-task operation sequences, reducing cognitive load, and improving pre-flight and monitoring efficiency. Key suggestions included redesigning checklists, providing auto-text completion options for data entry tasks, and implementing temporary shutdowns of displays (irrelevant to the primary flight task) under emergency conditions. The study methodology was validated through expert interviews and findings inform the design of current and future piloting procedures, potentially contributing to improved aviation safety and efficiency.

Chihab Nadri, Yunmei Liu, Maryam Zahabi, David Kaber, Jaime Ruiz, Michael Middleton, Ryan McKendrick

Conference Proceedings

Optimizing speech elicitation tasks for machine learning-based depression assessment

THEORETICAL BACKGROUND: The field of machine learning-based speech analysis may provide unobtrusive, time-efficient and cost-effective ways of automated depression assessment. Systematically optimizing speech elicitation tasks may further improve the accuracy of this approach. We hypothesized that machine learning-based depression classification would perform better if trained on recordings of individuals reading anti-depressive statements with the instruction to intone them as convincingly as possible compared to readings of anti-depressive statements without instructions regarding intonation.METHODS: To test this hypothesis, we recruited a sample of 48 clinically depressed individuals, 48 sub-clinically depressed individuals, and 48 non-depressed individuals. Participants from each group were randomly allocated to either the experimental or the control condition. In both conditions, participants read aloud scripted anti-depressive self-statements. Participants in the experimental condition received instructions to heighten the prosodic expression of conviction in their voice, whereas participants in the control condition received no such instructions. Separate classification models aimed at detecting current depression were trained for each condition and with a selection of different machine learning methods. RESULTS: We found that models trained on data from the experimental condition were more accurate and reliable than those trained on data from the control condition. While the former models reached balanced accuracies between 65–76%, the latter only reached balanced accuracies between 36–61%.DISCUSSION: Our results suggest that features of speech elicitation tasks have substantial influence on model performance for automated depression classification. The present findings highlight that speech elicitation tasks including voice modulation instructions can improve the validity and reliability of machine learning-based depression classification.

Jonathan Bauer, Maurice Gerczuk, Bjoern Schuller, Matthias Berking

Conference Proceedings

Basic psychological needs related to information ergonomics and loneliness

Remote working, particularly online teaching, in academia has significantly increased during and after COVID-19 pandemic. Simultaneously, loneliness at work has risen. Working in remote environments therefore requires employees to develop new types of working habits and psychological resilience. This study examines how basic psychological needs satisfaction related to online teaching has affected academics experiences of perceived usefulness of technology in their work, technostress and their sense of loneliness. The study is based on a survey dataset (n=201) collected of two Ghanaian universities during October 2023 to January 2024. The distributions of the item means were compared across the quantiles of autonomy, competence and relatedness. The results enhance the understanding to what level academics experience loneliness in collectivistic country like Ghana, and how basic psychological needs satisfaction in online teaching, perceived usefulness of technology and technostress interact in that relationship also from academic role perspective. The results provide useful information for academic working and curriculum planning as well as points for wellbeing at work considerations.

Reetta Oksa, Mia Laine, Edward White, Jussi Okkonen

Conference Proceedings

Cognitive Cost Assessment in Aeronautical Tasks: New Objective and Sensitive Method

The future fighter aircraft (e.g., Next Generation Fighter, central element of the Futur Combat Air System) are being developed in response to evolving conflicts in the Multi-Domain context. AI-based onboard systems will be limited in their tasks for technical and/or ethical reasons, thus leaving some tasks to be managed by the aircrew. Alongside these tasks is the overall management of the onboard system, further increasing an already high cognitive cost. Assessing this cognitive cost would help identify particularly costly tasks and develop training and human-system interfaces accordingly.This study aims to validate a method for evaluating cognitive cost using the complex span task protocol (Barrouillet & Camos, 2007) on basic aeronautical tasks performed by novices early in their training. The complex span task protocol involves alternating between memorization and processing. In this experiment, processing tasks correspond to two flight phases: a low difficulty phase (i.e., flight legs) and a high difficulty phase (i.e., turns at waypoints). The cost is measured by asking participants to perform a letter memorization task in a flight simulator during these flight phases. The number of letters recalled in the correct order determines the participants' complex span in each experimental condition (i.e., the higher the number of letters, the better the complex span, the lower the cognitive cost), interpreted as an indicator of the current task's cognitive cost.In addition to the test group (N=16), which performs both aeronautical and memorization tasks, a control group (N=14) is subjected only to the memorization task. Results show that the control group's complex span is better than that of the test group, indicating a lower cognitive cost. Within the test group, the complex span is better during the low difficulty phase than during the complex phase. These results indicate that the phase identified as high difficulty is more cognitively costly than the phase identified as low difficulty, with both phases indicating a higher cognitive cost than the memorization task performed alone. Taken together, the results suggest that evaluating performance on a complex span task during a simulated flight could provide an objective and sensitive indicator distinguishing variation in the cognitive cost of aeronautical tasks.Thus, this method has the advantage of being time-efficient and non-invasive, surpassing current limitations of measuring cognitive cost through physiological sensors (e.g., eye-trackers, electromyograms, or electrocardiograms).Consequently, such a method of cognitive cost evaluation could be extended to a wider range of more complex aeronautical tasks (e.g., spatial orientation changes, onboard system management). This task identification could lead to proposed methods for reducing what is identified as costly.

Marianne Jarry, Jean-christophe Hurault, Gregory Froger, Anne-lise Marchand, Colin Blättler

Conference Proceedings

A Digital Human Model for Symptom Progression of Vestibular Motion Sickness based on Subjective Vertical Conflict Theory

Digital human models of motion sickness have been actively developed, among which models based on subjective vertical conflict (SVC) theory are the most actively studied. These models facilitate the prediction of motion sickness in various scenarios such as riding in a car. Most SVC theory models predict the motion sickness incidence (MSI), which is defined as the percentage of people who would vomit with the given specific motion stimulus. However, no model has been developed to describe milder forms of discomfort or specific symptoms of motion sickness, even though predicting milder symptoms is important for applications in automobiles and daily use vehicles. Therefore, the purpose of this study was to build a computational model of symptom progression of vestibular motion sickness based on SVC theory. We focused on a model of vestibular motion sickness with six degrees-of-freedom (6DoF) head motions. The model was developed by updating the output part of the state-of-the-art SVC model, termed the 6DoF-SVC (IN1) model, from MSI to the MIsery SCale (MISC), which is a subjective rating scale for symptom progression. We conducted an experiment to measure the progression of motion sickness during a straight fore-aft motion. It was demonstrated that our proposed method, with the parameters of the output parts optimized by the experimental results, fits well with the observed MISC.

Shota Inoue, Hailong Liu, Takahiro Wada

Conference Proceedings

Supporting inclusive approach for Autism Spectrum Disorder (ASD) social environment

This article presents some of the results of the ongoing research SensAbility Design based on Design for Well-being and Medical Devices carried out by the authors at the Politecnico di Bari in the areas of product design and interaction design. The research which investigated the field of inclusive design for the design of devices capable of managing emotions in children with Level I Autism Spectrum Disorder. Level 1 autism, also known as mild autism, represents the least severe form within the autism spectrum and is generally characterized by normal or above-normal intelligence and developed language, but may manifest difficulties in several areas, including social communication, social interaction, and repetitive behavior (Cortina, 2015).In the area of social communication, without adequate support, communication deficits cause significant impairments, these individuals may have difficulty understanding and responding to non-verbal social cues, such as facial expressions, tone of voice and body language, have problems initiating and maintaining conversations, especially with unfamiliar people, often speaking in a monotone or overly literal manner. An important aspect relates to theory of mind, i.e., the ability to infer the other person's state of mind and use this information to interpret and predict the behavior of others, which leads to difficulties in recognizing and understanding emotions (Bird et al., 2013), especially complex ones, and interpreting the mind of others, resulting in unsuccessful attempts to make friends and maintain relationships (Howlin et al, 2004).Given this premise, the research in the desk phase has constructed the state of the art with reference to existing devices in the field of inclusivity and autism disorders; in the field phase it conducted a user research based on the co-presence and of 3 designers during the rehabilitation activities carried out within the PerL.A. cooperative and the department of Child Neuropsychiatry of the ASL of Ruvo di Puglia. This aspect, together with the qualitative and quantitative investigation carried out in the user research, contributed to identifying the objectives for the elaboration of the CLEA device and app.The involvement not only of the main users (children with ASD, parents, doctors and therapists) but also the of social welfare associations in order to compare the topic with the challenges of social inclusion (Tosi et al., 2020) has been the specific inclusive approach carried out.The first fase of the design research defined the following objectives: - to support children with autism to manage their emotions; - to enable parents and caregivers to manage and monitor the children's state of mind in real time, through suggestions according to specific needs; - to enable the social welfare network of the ASD children to be aware of issues related to managing emotions. - to promote a new paradigm and social awareness: care by designing and understanding the emotional complexity of ASD in depth. Understanding and supporting the unique needs of people with autism are important to create inclusive and supportive environments where they can thrive; this approach not only improves their quality of life, but also promotes their full participation in society.

Annalisa Di Roma, Alessandra Scarcelli

Conference Proceedings

Minimizing Chat-Bot Risks in Telemedical Applications: A Semi-Rule-Based System Approach for Large Language Model (LLM) Interactions in an Outpatient Setting

We present a patient-centric system integrating Large Language Models (LLMs) into medical applications, focusing on a diverse set of use cases. An initial use case for symptom reporting was explored using natural language, addressing the limitations of traditional questionnaires. This collected data can be analysed by healthcare professionals during visits. Designed within the EU's Medical Device Regulation (MDR), our system incorporates a semi-rule-based approach to guide conversations, ensuring control over the LLM's outputs. With modular architecture and open standards like FHIR, our system supports personalized medicine and future advancements in AI-driven healthcare tools.

Simon Stock, Marius Gerdes, Florian Mazura, Markus Schinle, Jonathan Helmond, Wilhelm Stork

Conference Proceedings

A Social Support-Enabled Mobile Health (mHealth) Application for Adolescent Depressive Symptomatology: Is it Usable and Feasible?

Over the last decade, there has been a remarkable expansion in designing and developing mobile health (mHealth) applications for prevention and/or intervention of a wide range of mental health problems, which have negative consequences on the physical health and everyday routine of individuals. With the onset of these mental illnesses during adolescence, mental health apps (MHapps) are especially a promising approach for depression, which is one of the most common and leading causes of mortality and morbidity in this vulnerable age, and is yet underrecognised, underdiagnosed and undertreated. However, the majority of MHapps available for download in commercial marketplaces do not adhere to evidence-based treatment guidelines, nor are supported by evidence-based research. Despite the potential advantages of mHealth apps in promoting mental health and well-being, particularly in adolescents with depression, extensive multidisciplinary systematic literature searches across various databases reveal a scarcity of research-based MHapps focusing on this population. Furthermore, most existing mHealth apps rely on self-reported symptom-based screening of depressive symptoms and provide low-intensity psychological interventions with minimal or no therapist involvement. Although numerous studies validate these approaches, researchers note insignificant or very small effect sizes for self-management-oriented mHealth interventions due to the persistent presence of loneliness, a core symptom of depression, resulting from limited human interaction. To alleviate depressive symptomatology and elevate psychological well-being in adolescents, a rule-based and evidence-based professional and peer social support framework to be integrated and incorporated in MHapps was investigated, proposed, implemented, refined, and tested based on comprehensive multidisciplinary literature reviews in mHealth and mental health domains, and usability testing with technical experts. This paper presents a step-by-step usability and feasibility assessment of the iteratively and incrementally refined theory-driven social support-enabled mHealth application in the real-world with school-going adolescents, licensed mental health counsellors and a moderator over a 4-week period. The critical analysis of both quantitative and qualitative results indicated a positive reception with participants expressing appreciation for the app's usability and potential impact on their well-being. The average SUS scores of 70.8 and 93.8 from adolescents and counsellors, respectively, underscored the acceptability of the social support-enabled mHealth app with 13 themes emerging from analyses of both participants’ responses to the five open-ended questions. These contributions serve to highlight the significance of integrating social support into mHealth interventions for adolescent depressive symptomatology, thereby expanding access to mental healthcare as well as saving time and resources. Fundamentally, these user-centric findings and their implications can be vital for mobile mental health research and community in making targeted improvements and facilitating optimal mental health and well-being in adolescents.

Sayyida Masoom Gilani, Muhammad Fermi Pasha, Vanlal Thanzami, Pari Delir Haghighi

Conference Proceedings

Improvements in stress-detection technology to improve the quality-of-life of people with challenging behaviour

In this paper we present two improvements to the ongoing development of a sock garment with integrated sensors for the monitoring of physiological signals. These signals are used for stress detection in people with intellectual disabilities and dementia in a long-term care (LTC) setting. The improvements discussed in this paper are both aimed at improving the quality of the measurements and improving the quality of care, especially in the context of challenging behaviour. In this paper we briefly present the following two improvements:1.A new electrode configuration that allows for predictive maintenance of the garment-part of the system.2.A new user interface, particularly an online dashboard, providing a tool set aligned with the needs of behavioural scientists.

Tim Hulshof, Mila Chorbadzhieva, Reon Smits, Erwin Meinders

Conference Proceedings

Development of Intelligent Nighttime Brace with Smart Padding to Treat Adolescent Idiopathic Scoliosis

Adolescent idiopathic scoliosis (AIS) is a three-dimensional spinal deformity affecting children aged 10 to 16, with up to 4 in 100 adolescents potentially having this condition. AIS is characterized by asymmetrical shoulders, bulging ribs, or a tilted torso, though patients typically do not experience pain or neurological issues. Treatment varies based on the severity of the spinal curvature and bone maturity, ranging from observation and bracing to surgery and Schroth exercises. Full-day brace wear (18 hours/day) is often recommended but challenging for adolescents, leading to low compliance rates and associated psychological stress for both patients and parents (Vicente., et al, 2021).To address these issues, nighttime braces have been developed to reduce wear time to a minimum of 8 hours per night by overcorrecting the major scoliotic curve during sleep. However, existing nighttime braces, such as the Charleston brace, can cause compensatory curves and permanent overcorrected spinal curvatures, as well as skin issues like rashes and redness (Yrjönen., et al, 2006).This study aims to improve nighttime brace design and material selection to enhance patient compliance and treatment outcomes. The design process will integrate clinical studies, material science, garment design and wearable technologies. The primary function of the proposed brace is to control spinal deformity during sleep.Key features of the new brace include the careful selection of sweat-wicking and breathable textiles to ensure comfort. The brace will incorporate a smart padding system that automatically adjusts corrective forces and positions. Preliminary clinical trials will be conducted with a diverse group of subjects to refine and optimize the intelligent brace. These trials aim to ensure the brace's effectiveness across various cases. The intelligent brace is designed to enhance patient compliance and treatment efficiency while reducing the risk of skin problems through automatic adjustments and a comfortable wearing experience, ultimately improving overall patient outcomes.ReferencesVicente, L. G., Barrios, M. J., González-Santos, J., Santamaría-Peláez, M., Soto-Cámara, R., Mielgo-Ayuso, J., Fernández-Lázaro D. & González-Bernal, J. J. (2021). The ISJ 3D brace, a providence brace evolution, as a surgery prevention method in idiopathic scoliosis. Journal of Clinical Medicine, 10(17), 3915. Yrjönen, T., Ylikoski, M., Schlenzka, D., Kinnunen, R., & Poussa, M. (2006). Effectiveness of the Providence nighttime bracing in adolescent idiopathic scoliosis: a comparative study of 36 female patients. European Spine Journal, 15(7), 1139-1143.

Qiwen Emma Lei, Zhaolong Chen, Man Chee Kenneth Cheung, Kai-yu Tong, Mei-chun Cheung, Kit Lun Yick, Chi Yung Tse, Joanne Yip

Conference Proceedings

Design for multiverse healthcare: The innovation spaces and transformation paths of the medical and health industry in the Digital Era

With the popularization of intelligent technology and digital survival methods, the medical and health industry faces numerous opportunities, challenges and changes. This study aims to explore the innovation space and transformation path of the medical and health industry in the era of digital survival. First of all, this study starts with the concepts of big health and big health industry, and summarizes the whole life cycle of individual health and the multiple innovation spaces of health design. In the exploration of multiverse healthy design, the study starts with the analysis of human identity, and defines the way of human existence in the future society as conscious human, physical human, social human, and digital human; thus, different types of health are derived, namely mental health, physical health, social health, and digital health; and the multiple innovation spaces of the medical and health industry are analyzed, namely, consciousverse (conscious space), physicalverse (physical space), socialverse (social space), and digitalverse (digital space). Each innovation space has its own unique characteristics and functions, and they can influence, intersect and interact with each other, providing new possibilities for improving people's health level and quality of life. Secondly, the study analyzes the five major transformation paths of the health industry, namely"Digitalization&Intelligence","Inclusion&Accessibility","Personalization&Customization","Systematicness&Intersectionality", and "Globalization&Localization". The content of this study will expand new innovation space, provide new innovation inspiration and transformation ideas for designers, technicians, researchers engaged in the development of health products, services and experiences, as well as institutions, organizations, enterprises and practitioners related to the health industry.

Yuqi Liu, Liang Xiao, Ye Zhang

Conference Proceedings

Comparison of Race Walking and Power Walking at Varying Paces by Expressing Movement in the Frequency Domain

Many people use walking as a form of exercise to maintain or improve their health. Main gait types of walking are normal walking, power Walking and race walking. Although race walking has a potential to contribute significantly to healthcare due to its high exercise load, it is difficult for athletes to judge gait themselves due to the nature of the competition, in which the gait is judged visually by a judge. Therefore, this study focuses on race walking and elucidates mechanism of race walking in order to examine whether race walking can be used for healthcare. Previously, this research group has considered walking as a periodic motion and proposed a method to quantitatively represent normal walking by analyzing the frequency components of vertical acceleration that occur in body parts during walking. By applying this method to race walking, it is considered that frequency components can be used as a quantitative indicator of characteristics in race walking, and can help to evaluate and improve their own movement. On the other hand, power Walking, which is a walking movement with a stronger exercise load than normal walking, is more similar to race walking than normal walking. So, we believe that the characteristics of race walking can be further clarified by comparing the characteristics of power Walking with those of race walking. Therefore, the purpose of this report is to clarify the characteristics of walking movement in race walking based on the frequency components of vertical accelerations occurring at body parts in race walking and power Walking. In this report, pace is used as one of parameters to represent the movement, and changes in the characteristics of movement when pace is varied are focused on.

Tomoki Inoue, Kyoko Shibata

Conference Proceedings

Timbre estimation of compound tones from an auditory cortex by deep learning using fMRI: Sound pressure levels detection of specific frequency

Brain decoding have been widely treated in the neuroscience. However, compared to research in the visual cortex, progress in the field of auditory cortex has not been made. Therefore, the purpose of this study is to establish a technique to estimate sounds heard by human using deep learning from brain images captured by fMRI. The sounds we hear in usual have a unique timbre. Timbre is determined by the combination of sound pressure levels at the overtone, which is the natural multiple of the fundamental frequency, in a compound tone. Before, this research group decoded the pitch of pure tones, which are waves of a single frequency. As a result, the discrimination of two tones in increasing degrees and the detection of a specific pitch in triad were realized. Next phase of this research is to decode a sound pressure level at a specific frequency. By combining these methods, we believe it is possible to decode timbre by detecting a sound pressure level of specific overtone. In a previous report, we examined whether the brain activity of listening to pure tones at two different sound pressure levels at specific frequency can be discriminated by deep learning binary classification. The result was a discrimination rate of 70.84% with relative levels of 0 [dB] and -20 [dB] when 90 [dB] was used as a reference. This result indicates that the difference in brain activation intensity by sound pressure level could be handled as classification problem by deep learning. Therefore, the purpose of this paper is to detect the sound pressure level of pure tones using deep learning for application to timbre decoding. Specifically, we attempt to detect specific sound pressure level among the three tones of 0 [dB], -10 [dB], and -20 [dB] when 90 [dB] based on an absolute level of 90[dB]

Junnosuke Kusumoto, Kyoko Shibata, Hironobu Satoh

Conference Proceedings

A user-centered design approach in the development of a modular AI-system for detection of cerebral palsy in infants

One in 500 newborns is born with cerebral palsy (CP), a malformation of the brain that results in restricted movement and muscle spasticity. The earlier CP is diagnosed and targeted therapy is initiated, the more potential there is to reduce the physical impairments of the affected children and the resulting consequential damage and costs. However, the diagnosis depends largely on the qualifications of the clinicians. In the CP-Diadem project, a modular sensor AI-system is being developed to objectively support paediatricians in the diagnosis. The aim is to develop a support system that automatically detects conspicuous movement patterns, which can then be examined more closely by experts. In this paper, we address the following research questions (1) How should an AI-diagnostic tool for clinicians to detect CP be developed that is accepted by all those involved (clinicians, parents and infants) in the treatment? (2) How can the diagnostic system be integrated into the clinical routine (treatment pathway)? Based on the human-centered approach according to DIN EN ISO 62366 the following formative studies were conducted iteratively. Initially, the prototype of the modular sensor system was tested in a field study with 50 infants, their parents and clinicians during regular treatment. It consists of a sensor mat with eight piezo sensors, on which the infant is placed, and seven inertial measurement units (IMUs), which are attached to the child's limbs. Two cameras record the infant's movements. Parents and clinicians evaluated the system in terms of their user experience and assessed the challenges of integrating it into standard pediatric care for the early detection of neurological movement impairments. Based on the results, a click prototype was developed. The AI-system was evaluated with clinicians as part of a workshop. The aim was to achieve a high level of usability and user experience and to identify challenges in the use of AI in the diagnosis of CP in infants. All UCD methods used in the project involve clinicians, parents and children with their requirements, needs and ideas for active co-decision and participation.

Natalie Jankowski, Vivian Waldheim, Katharina Lorenz, Christina Mittag

Conference Proceedings

Smart Packaging: overcoming barriers to medication adherence for older adults

Medication adherence is essential for managing ageing illnesses due to the growing population of older adults who are increasingly multi-medicated. This paper explores the current challenges and future opportunities in enhancing medication adherence for older adults. It highlights the importance of leveraging home-based healthcare technologies for older adults based on their needs. There are various types of healthcare technologies and smart packaging options available in the market today. Some examples include smart pill and medication dispensers with smart packaging features, Mobile applications with reminders, manual pill boxes and organisers. These devices use features such as alarms, reminders, and tracking systems to help older adults with their routine. However, older adults' medication management can be affected by changing needs associated with ageing. As a result of ageing, their cognitive and physical abilities are rapidly changing due to various conditions including dementia, reduced vision, and decreased dexterity. Exploratory interviews were conducted with five older adults age 65 and over. The interviews focused on the participants' experiences with managing their medications, including challenges associated with rapidly changing medical conditions and capabilities. The major concern identified by participants was the complexity of managing multiple medications due to rapidly changing health conditions including forgetfulness, sensory impairments, neurological conditions, and reduced dexterity. The results have opened new avenues for future research in 1) smart packaging and design features that prioritises accessibility and ease of use, 2) leveraging Artificial Intelligence (AI) in smart packaging towards more personalised products to improve medication adherence in older adults.

Bahar Khayamian Esfahani, Jelena Milisavljevic-syed, Kalok C Lee

Conference Proceedings

User trust in a depression screening app when outcomes are labelled as either AI-generated or doctor-generated: a pilot study.

This study aimed to quantify and compare user trust when interacting with a web-based depression screening app, where outcomes were labeled as either AI-generated or doctor-generated. The app calculated a depression score based on user input and presented two screening outcomes, one labeled as “doctor-generated” and the other as “AI-generated.” Participants were then asked to select the outcome they trusted the most. Seventeen individuals participated in the study. Despite identical outcomes, 11 participants chose the AI-generated outcome (group-AI), while 6 selected the doctor-generated outcome (group-DR). To assess user trust (also attention), electroencephalogram (EEG) signals were recorded during the task, focusing on Alpha (Pz) and Beta (Fc1, Fc2) channels. Attention was measured through Alpha activity at Pz, while trust was assessed through Beta activity at Fc1 and Fc2. Post-intervention, participants’ perceived trust in the outcomes was measured using a survey. The mean normalized power spectral density (PSD) values were calculated and correlated with the survey-based trust scores. Comparisons of PSDs and trust scores were made both between and within the AI and DR groups. Results showed that the mean PSD value for attention (Pz) was 0.116 µV²/Hz, while the values for trust (Fc1 and Fc2) were 0.648 µV²/Hz and 0.646 µV²/Hz, respectively. The mean trust score for the AI-based outcome was 3.118, compared to 3.235 for the doctor-based outcome. A weak to moderate correlation was observed between survey trust scores and PSD values in Fc1 and Fc2. Group-AI exhibited lower Alpha power at Pz (0.108 µV²/Hz) and higher Beta power at Fc1 (0.660 µV²/Hz) and Fc2 (0.659 µV²/Hz) compared to group-DR, which showed higher Alpha power at Pz (0.131 µV²/Hz) and lower Beta power at Fc1 (0.626 µV²/Hz) and Fc2 (0.621 µV²/Hz). In conclusion, our findings suggest that while participants may express marginal preference for doctor-generated outcomes in self-reported trust, their EEG data reveals a nuanced picture where those choosing AI-based outcomes may exhibit higher levels of trust on a cognitive level.

Yeganeh Shahsavar, Avishek Choudhury

Conference Proceedings

Social Empathetic Cognitive Robotics for Autism (SECRA): a preliminary study

In the last two decades, Socially Assistive Robotics (SAR) has emerged as a promising approach in treating Autism Spectrum Disorders (ASD). SAR involves using social robots to provide assistance in social interaction settings. Although much research in this field is still preliminary, SAR has shown significant potential for achieving effective outcomes in ASD treatment. Despite these promising results, there are still unanswered questions about the effectiveness of SAR for ASD, especially regarding how social robots should be designed to optimize the complex interactions among therapists, children, and robots. The primary aim of the present project is to address these limitations through a large-scale, randomized controlled trial that can provide clear answers to the above questions. The project has two main objectives: (a) to develop robust psychosocial protocols for robot-assisted therapy tailored for children with ASD, and (b) to evaluate whether the QTrobot (LuxAI), along with eye-tracking technology, can improve cognitive and socio-emotional skills in these children in various environments. The project will be implemented in two phases. In the first phase, psychosocial protocols will be developed and tested preliminarily to refine their effectiveness. Based on the results of Phase 1, a rigorous randomized controlled study will conduct in the second phase. Currently, the project is at first phase. We are conducting the preliminary study to develop the psychosocial protocol and to understand what factors can facilitate the interaction human-robot. In this case, children with ASD and the QTrobot. This project is funded by the European Union-Next Generation EU.

Tindara Caprì, Giulia Picciotto

Conference Proceedings

Preferences of Elderly People in Western Taiwan towards Smart Sportswear

This study was designed to determine the preferences of 300 elderly people in western Taiwan, aged 55 to 85, with regard to smart sportswear. It employed non-random sampling, in the form of a structured questionnaire, and an independent sample t-test, a single factor variance analysis, a post hoc test, and a chi-square test of statistical analysis to analyze the responses to the 16 questions. The research datasets were categorized based on gender, age, and exercise duration. The findings revealed that half sleeve and three-quarter sleeve tops were more commonly chosen by women than men, while shorter tops and trousers were more commonly chosen by men than women. In terms of color, men and women preferred blue and red, respectively. The majority of the participants reported the knees and ankles to be the most commonly injured body parts. They preferred to wear loose-fitting garments, crew neck tops, ankle-length trousers, hip-length garments, and short sleeve tops. However, only 8.7% of participants had experience wearing smart clothing. Fifty-six percent of participants expected to pay between 33USD and 166USD for smart sportswear.

Ying-Chia Huang

Conference Proceedings

Segmentation of Augmented Reality 3D Meshes to Discover In Home Safe Walking Spaces for Older Adults

Falling continues to be a significant risk factor for older adults and other mobility limited individuals. Around 16% of all US adults 65 and over fell at least once in a 3 month window, and falling affects 50% of adults over the age of 80. These falls account for 0.1% of all US healthcare costs, or about $4 billion per year. Falls are the number one reason older adults move from independent living to long term care, so any reduction in their frequency has significant benefits to our communities. Around 55% of all fall related injuries occur within the home, and 35% to 40% of those from environmental conditions such as clutter, slippery floors, narrow walkways, and poor lighting. Monitoring and maintaining clear, tripping hazard free pathways in living spaces is invaluable in helping people live independently and safely in their home. This paper proposes and demonstrates a space segmentation approach to discovering which areas of the home are classified as ‘walkable’ in a safe manner. The goal is to then provide residents and caregivers guidance about reducing in-home environmental risk factors for falls. The system leverages 3D mesh-based maps of the home gathered by the Microsoft HoloLens v1's sensors. The algorithm was designed to work with many different kinds of sensor platforms that provide mesh-style maps of spaces, such as LiDAR, vision-based solutions, and other Augmented Reality platforms. The collection of algorithms needed for the system were collected into the Walking Spaces Algorithm (WSA) package. These algorithms first used a denoising floor detection algorithm and a waterfall-based furniture and clutter detection to handle the noisy raw mesh data to help identify uncluttered floor spaces. The resulting reduced noise 3D model of the home was then processed using a segmentation algorithm to find pathways that would be considered safe under the United States Occupational Safety and Health Administration (OSHA) guidelines. The home's safe and unsafe spaces were then visualized for users to see and understand where the home is safe and accessible or not. To test the WSA algorithm, data was collected from both lab and apartment spaces for testing. All data collected was stored on a database backend with a web frontend to see real time updates of the home as the resident carried the AR headset through the space, with final images being generated on a daily basis for long term analysis as the home's space changed due to clutter or furniture movements. The long term goals of these technologies are to monitor the living space’s clutter and clear walkways over time. The information it generates shall then be provided to the residents and their caregivers during environmental home assessments. It informs them about how well the home is being maintained so proactive interventions may be taken before a fall occurs. Overall, the results from the WSA algorithm in the testing spaces were successful at identifying open vs. cluttered spaces and allowed the algorithm to demonstrate where residents had OSHA-rated clear walking spaces in their home.

Aaron Crandall

Conference Proceedings

Development of a Training Simulator and Testing Environment for Electric Wheelchair Controls

A training simulator is being designed as part of the interdisciplinary research project “Development of alternative control systems for wheelchairs”. This simulator serves as a platform for testing and evaluating innovative control concepts that are created in an iterative process involving users with electric wheelchairs, medical and technical specialists. The development focuses on integrating the physical properties of a real, electric wheelchair into a simulation. This wheelchair is typically controlled with the hand, chin or tongue joystick and has characteristics such as inertia and acceleration behaviour. The goal is to create a driving experience that is as realistic as possible. These adjustments are continually developed in close cooperation with the groups mentioned. This project aims to clarify how the transfer of the real wheelchair into the virtual simulation affects the learning behaviour, motivation, and satisfaction of patients who complete training with electric wheelchairs.Interviews with occupational therapists at the Center for Paraplegics in Hamburg have revealed an increased need for such a training simulator. Currently, training with electric wheelchairs is limited to real-world environments, which poses certain risks. The home environment is simulated in the clinic with markings on the floor. A safer and more efficient training method would be to use a variable, virtual environment in which patients can be familiarized with the new method of locomotion without risk. For this purpose, realistic training scenarios from everyday clinical practice are integrated into the virtual environment of the training software. A virtual reality headset allows patients to adapt to using the electric wheelchair without risk and at their own pace. In cooperation with a leading manufacturer of electric wheelchairs, the plan is to use the physical hardware of the wheelchair as an interactive input device for the simulator. It will also be possible to configure the specific comfort settings (including backrest, headrest, largest, armrests) within the training simulation. In particular, the adjustability of the backrest is an important element of driving training for mastering slopes and slides.The next phase of research is concerned with the development of an eye-controlled digital joystick for the Magic Leap 2 augmented reality glasses, which will eventually also be implemented in real wheelchairs. The joystick is initially used as a control element for a virtual wheelchair in a simulated test environment. A key development goal is to visualize the wheelchair's user-specific user interface (UI) on the AR display. It is also planned to enable control of the UI via eye control and voice commands to ensure intuitive and barrier-free interaction. Thanks to flexible setting options, the UI can be personalized to the requirements of the respective user.After a comprehensive evaluation of the control by the test subjects and medical staff regarding user-friendliness and safety, the innovative control is integrated into a physical wheelchair. In a further iterative process, the control is continuously optimized in close collaboration with the end users in a protected setting.

Jendrik Bulk, Benjamin Tannert

Conference Proceedings

Preventive Medicine: The most prestigious profession of the near future

The title of this scientific essay implicitly emphasizes the application goal. Hypothesis: the differences in most indicators of somatic, mental and social health are small (or non-existent) between countries with the formally largest number of weekly physical education lessons in primary schools and those with the smallest number (apart from countries where PE is marginalized). The empirical argumentation of the authors of the 'physiotherapist in every school' project, although sufficient at this stage, is merely a kind of encouragement for researchers and teams from around the world. The implications concern at least two elementary methodological issues. First, the most valuable knowledge about phenomena indicating the counter-effective PE paradigm in many respects can already be published in many natural languages, unavailable in the global scientific space. Second, the idea of replacing PE teachers in schools with preventive medicine experts requires systemic implementations that will most likely cause resistance from many interest groups. As humanity, we are probably at the peak of ‘the turning point’, not only in the sense described by Fritjof Capra (1982). Since the dynamics of depletion of natural resources is still one of the key indicators of identifying this peak, there is no visible turn in the direction that Capra so simply and accurately appealed for: ‘we should invest more in people, our only wealth, which we have in abundance’. Anyone who identifies with the hypothesis on the supreme value criteria of the global civilization should rather not question the validity of preventive medicine as a subject of school education and INNOAGON as science and its mission. However, one may ask a basic question about the way or ways of investing these innovations in people. The answer is only seemingly trivial: effectively, healthily (this term includes ‘safely’), in deeply humanized and attractive forms.

Roman Maciej Kalina

Conference Proceedings

Methodological and mental distance to the dissemination of vertical test fight between girls and boys

The aim of this work is empirical evidence of the need to respect specific methodological standards in the study of the phenomenon of diagnosing mental and motor predispositions to counter physical aggression. The key criterion for ‘situational actionability’ is testing fights in a vertical posture (TFVP) efficiency. Of the 59 TFVP participants aged 7 to 13 years, there were 37 boys and 22 girls. The innovative comparison of motor potentials according to the same criteria, i.e. age- and gender-adjusted for the winner of the GPC (groups of people combats), provides important empirical evidence that the chances of girls' effective self-defence against physical aggression by their peers, boys, dominating them with motor potential and/or body weight, are real.

Michal Kruszewski, Wojciech Niedomagala, Jaroslaw Klimczak, Artur Litwiniuk

Conference Proceedings

Measurement of motivation and qualitative effects of physical effort during two motor learning sessions with multifaceted variation of goals, methods, measures and tools – example of violin playing and safe fall

The purpose of this case study is to argue empirically about the similarities and differences of the indicators used to evaluate the motor learning effects of new motor competencies with distinct goals and in radically different educational settings. During 14 sessions of remote teaching and improvement of violin playing during the COVID-19 pandemic, a less than 13-year-old boy in the last semester of a six-year first-level music school was observed. Two 22-year-old female students (Girl1 and Girl2) and a 21-year-old male student (Boy) were observed during 8 sessions of a safe fall course (a mandatory subject in a physiotherapy degree program). The effects of the adolescent violinist's effort were evaluated three times during the session (in the beginning, middle, and end parts). The music teacher arbitrarily adopted five kinesiological criteria for evaluating movement characteristics: accuracy, rhythm, range, force, tempo. He combined each individually with artistic effects according to a 25-point scale. The highest arithmetic means of the evaluation scores of the violinist's joint motor and artistic activities were found during the 5th session, when he declared a self-motivation of 5 points. The most positive health effects of exercise of Girl1 and Girl2 are furthermore documented by the highest number of sessions (8 and 7 respectively, representing 87.5% and 75% of the observations) during which exercise was qualified to the high intensity zone. Elements of measuring physical exertion and motor effects with a component of either artistic or prevention component during motor learning in the areas of instrumental music and motor skills related to human personal safety (safe falling, avoiding collisions, self-defence, skiing, etc.) can be mutually implemented to the benefit of public health in particular.

Elizabeth Waszkiewicz, Artur Kruszewski

Conference Proceedings

The relationship between the cognitive and behavioral potential of young adults resistant to motor modifications and the effects of learning safe falling techniques

The discovery of the phenomenon of resistance to motor modifications targeted at increasing personal safety during an unintentional fall raises questions about the relationship between the cognitive-behavioral potential of adults with such properties and the effects of learning how to safely collide with the ground due to loss of balance. The aim of these pilot studies is to resolve the question whether multi-month safe falling courses are a sufficient incentive for adults who are resistant to this type of modifications not only to eliminate the errors of colliding with the ground with distal parts of the body (it is about diagnosing the phenomenon of susceptibility to the body injuries during the fall - symbolic abbreviation: SFI) ), but also fully professionally mastered safe falling techniques.Among the 14 students of physiotherapy and physical education who had suffered at least one body injury in the past and at the same time committed the errors of colliding with the ground with four parts of the body during three tasks of the susceptibility test to the body injuries during the fall (SFIindex from 100% to 78.57%). still 9 of the physiotherapy students made mistakes, even though they participated in two safe fall courses - first for people with visual impairments, then for people with limb amputations. Two of them (22.22%) eliminated 100% of errors compared to the results preceding the training (SFIindex 0 points). The rest reduced errors by 92.31% to 76.92%. In this fraction (n = 7), three students still made mistakes with their legs and hands, and four only with their hands. None of the students performed the 'test for safe fall' (TSF) flawlessly - results from 95% to 85%). The results of the degree of error reduction by the fraction of 7 students are highly positively correlated (r = 0.802, p<0.05, and with a one-tailed test p<0.025) with the TSF results. The degree of error reduction by this fraction is highly negatively correlated (r = −0.769, p<0.05) with the comprehensive health effects of fall (CHEF). The relationships of these indicators are not as clear with the results of the body balance disturbation tolerance skills test (before the courses r = 0.363, after the courses r = 0.430).Conclusion: correlations of the degree of reduction of the SFI phenomenon in the course of teaching safe falling techniques to people who are resistant (in the cognitive and behavioral sense) to motor modifications with the indicators used to assess adaptation effects allow the following hypothesis to be put forward: complete resistance to motor modifications may turn out to be the simplest predictor of cognitive and cognitive potential. human behavioral health, and such knowledge would be provided by widespread research for the purpose of selective prevention and treatment of the effects of SFI, starting from early school age.

Bartłomiej Gąsienica - Walczak, Artur Kalina

Conference Proceedings

The Influence of Gender/Sex on Work-Related Musculoskeletal Disorders: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis examines the influence of gender/sex on the risk of developing work-related musculoskeletal disorders (WMSDs). Previous research has indicated a link between female gender/sex and increased WMSD risk, but findings have been inconsistent due to varying study designs and high null result rates. This study synthesized adjusted odds ratios (AORs) from 93 high-quality cross-sectional studies that examine WMSD risk while controlling for various confounding factors such as job exposure and environmental variables. The overall synthesized AOR for female gender/sex on WMSD risk was 1.50, and gender was a statistically significant predictor of risk for most but not all body parts and industries. High heterogeneity was present in the overall synthesis but recued when stratifying results by industry and body part. The results suggest a significant but low to moderate link between gender and WMSD incidence, with some variation by industry and body part.

Christy Manning, Duha Ali, Shivani Nagrecha

Conference Proceedings

Video-based Ergonomic Risk Assessment among Transportation Maintenance Workers in Shoveling

Shoveling is a physically demanding task that has resulted in various physical injuries, particularly affecting workers’ lower backs and shoulders. Specifically, shoveling gravel has been identified as one of the primary activities leading to common ergonomic injuries among transportation maintenance workers. Previous research has focused on evaluating the risks of ergonomic injuries from shoveling through simulations in the construction industry and field experiments in the agricultural industry. However, there is a lack of studies about the ergonomic risks associated with shoveling activities by field experiments within the transportation industry. In addition, prior studies have proposed some ergonomic solutions to prevent injuries in shoveling activity, such as ergonomic handles and back exoskeletons (EXOs). However, no research has yet provided a direct comparison of ergonomic risk levels when workers utilize different ergonomic solutions while shoveling. To address these gaps, this research evaluated the ergonomic risk levels associated with shoveling activity using different ergonomic solutions among 26 transportation maintenance workers. The ergonomic risk evaluation was conducted using the Rapid Entire Body Assessment (REBA) and Rapid Upper Limb Assessment (RULA) methods based on videos of their shoveling activities. Videos were recorded from October 3rd to October 17th, 2022. Each participant completed four trials of shoveling gravel, averaging around 97 minutes, using a regular shovel, a back EXO, an ergonomic handle, and both the back EXO and the ergonomic handle. Between each two subsequent trials, a 15-minute break was provided for participants to recover from the previous trials. Moreover, participants finished the four trials of shoveling gravel following the Balanced Latin Square order, in order to avoid the carry-over and order effects. During each trial, participants first shoveled broken gravel from the ground to the skid steer loader and cleaned any residual gravel from the ground in Part 1. Then, they shoveled new gravel from the asphalt hot box machine to the ground and patched it in Part 2. A 5-minute break between Part 1 and Part 2 was also offered to simulate the real-life practice. Results found that wearing a back EXO did not significantly reduce ergonomic risks during shoveling gravel, whereas the use of ergonomic handles and the combined use of the back EXO and ergonomic handle significantly decreased ergonomic risk scores during shoveling gravel. This study not only fills the gaps of ergonomic risk evaluation in real-world transportation maintenance activities, but also provides valuable insights for enhancing worker safety and efficiency in such environments.

Xinran Hu, Xingzhou Guo, Yunfeng Chen, Jiansong Zhang

Conference Proceedings

Advancing Vision-based Adaptive Gripping Technology with Machine Learning: Leveraging Pre-trained Models for Enhanced Object Classification

The rapid advancements in robotics and automation have highlighted the need for robotic systems capable of adapting to the diverse physical properties of objects. Traditional grippers often lack the versatility to handle both hard and soft objects without extensive reprogramming or hardware adjustments. Previous studies have explored various approaches to this challenge, including tactile sensors and force feedback mechanisms to distinguish object properties. For instance, research by Calandra et al. (2018) utilized deep learning with tactile data to enable robotic hands to identify objects and adjust grip accordingly. Similarly, the paper by Li et al. (2020) “Design and performance characterization of a soft robot hand with fingertip haptic feedback for teleoperation”, focuses on designing and characterizing a soft robotic hand with fingertip haptic feedback for teleoperation emphasizing real-time tactile sensing and feedback mechanisms. However, these studies primarily focus on tactile feedback or specialized hardware, limiting their applicability in scenarios where such systems are not available or practical.This study introduces a novel machine learning-based approach, focusing on the use of visual data alone to classify and adapt to the hardness or softness of objects. By leveraging the CIFAR-100 dataset, we trained a deep learning model based on the ResNet50 architecture, achieving significant results in binary classification of hard and soft objects. The CIFAR-100 dataset, consisting of 100 diverse object categories/classes, was reorganized into two classes: hard (39 categories) and soft (61 categories). The ResNet50 model, pre-trained on ImageNet, was fine-tuned specifically for this task, with modifications to the last 210 layers to enhance its adaptability.Data augmentation techniques, including rotations, translations, shearing, zooming, and horizontal flipping, were applied to simulate real-world variations, ensuring robust learning. The model was further refined with additional fully connected layers, dropout, and batch normalization to prevent overfitting. Optimized using the AdamW optimizer, the model achieved a training accuracy of 83.31% and a validation accuracy of 80.25%, with a test accuracy of 80%. The precision, recall, and F1-scores were 0.82, 0.86, and 0.84 for the soft object class, and 0.76, 0.71, and 0.73 for the hard object class, demonstrating the model’s effectiveness in distinguishing between hard and soft objects without the need for specialized sensors. It is also observed that the accuracy of the model in relation to hard objects is significantly lesser as compared to soft objects. It is understood that the CIFAR-100 dataset (comprising of 100 classes) is inadequate for model training, so we are exploring the ILSVRC (ImageNet subset) dataset for model training in future. The research is useful in a variety of fields where the focus lies on object handling. In everyday life, we encounter a wide array of objects with varying degrees of hardness, requiring different levels of care and precision during handling. By relying on visual data and machine learning algorithms, as demonstrated in this research, robotic systems can become more autonomous and versatile, reducing the burden on human operators and improving overall efficiency. This approach can lead to cost savings by reducing the need for specialized hardware, such as tactile sensors, which are often expensive and difficult to integrate.

Diptesh Kumar Mandal, Kazunori Kaede, Keiichi Watanuki

Conference Proceedings

Biomechanical modeling of subjective fatigue during high-frequency repetitive manual-handling tasks

Accumulation of muscle fatigue and subjective fatigue are significant causes of decline in individual performance. Those fatigues can also lead to work errors and the associated musculoskeletal disorders. Thus, a quantitative evaluation of fatigue accumulation during work is required to manage the risk of industrial accidents. Most of the current assessment methods of workload are based on observing and scoring the range of joint motion and work frequency at a point in time. In other words, these assessment methods do not fully consider the continuous accumulation of fatigue. However, even while repeating the same task, muscle fatigue-recovery states and work movements change over time. Therefore, risk management of industrial accidents is important to objectively evaluate the subjective sense of strain and muscle fatigue from work movement data. This study aims to biomechanically model muscle fatigue and subjective fatigue during high-frequency repetitive manual-handling tasks. In an experiment, participants were asked to repeatedly lift a bottle weighing approximately 1 kg, containing salt as ballast, from a chest-height shelf to an eye-level shelf every two seconds for ten minutes. Both start and end points were set at the point approximately 80% of the upper limb length from shoulders at those heights in the midsagittal plane. During the experiment, whole-body motion was measured using an inertial sensor-based motion capture system. In addition to the body motion, electromyograms and subjective evaluations based on the Borg-CR10 scale of the upper limb were recorded. The measured body motion data were applied to a human musculoskeletal model to simulate muscle activity at each sampling time in the experiment. The results were then applied to the Xia and Frey-Law muscle fatigue model to simulate each muscle's residual capacity and fatigue at each sampling time during the experiment. The ratio of the simulated muscle activity to the simulated residual capacity was defined as the substantial muscle activity rate (SMAR). Changes in the SMAR during the experiment were compared with the changes in subjective fatigue and EMG median frequency. Throughout the task, slight abduction and forward flexion were kept in the upper arm. Therefore, we focused our discussion on the deltoid muscle, which might be the most heavily loaded during the experiment. The frequency analysis result of electromyograms indicated that the frequency power spectrum in the medial deltoid shifted to a lower frequency band in the first few minutes and was generally constant in the rest. The residual capacity of the medial deltoid simulated by the muscle fatigue model declined nonlinearly in the first few minutes and was almost constant after that. These results indicate that the muscle fatigue model sufficiently represented the fatigue at the medial deltoid. The muscle activity rate simulated by the musculoskeletal model was almost the same throughout the experiment. On the other hand, the SMAR declined in the first few minutes and continued at a higher range than the muscle activity rate. This changing trend of the SMAR was similar to the time change of the subjective fatigue of the shoulder.

Akisue Kuramoto, Masaya Noguchi, Motomu Nakashima

Conference Proceedings

Technological and Engineering Solutions for the Prevention and Reduction of Hand Arm Vibration Syndrome in Construction Industry

Prolonged exposure to hand arm vibration (HAV) can lead to hand arm vibration syndrome (HAVS), which poses serious health risks for workers (Lache & Luculescu, 2008). This paper employs a five-stage scoping review to explore technological and engineering solutions to mitigate HAV exposure in the construction sector. Key strategies identified include process modifications, reducing continuous vibration exposure, training programs to promote best practices, and using personal protective equipment such as anti-vibration gloves. Additionally, substituting low-vibration tools is recommended as an effective measure to decrease HAV exposure. The findings indicate that engineering solutions can significantly reduce the health impacts of HAV. The paper calls for further research, especially in developing regions like Africa, to evaluate HAVS prevalence in construction and to adapt control measures to local conditions. Overall, this study provides essential insights into preventing HAV, highlighting the need for global attention to this occupational health issue in the construction industry. S

Suma Mwaitenda, Innocent Musonda

Conference Proceedings

Psychological and physiological effects of industrial noise: An applied study in the BMS ELECTRIC company in Algiers

This study aims to identify the impact of industrial noise on workers psychologically and physiological.The psychological effects were measured by the following indicators (Behavioral symptoms, Cognitive symptoms, Psychosocial problems and difficulties).As for the organic effects were determined by the following indicators (Physiological symptoms, Auditory symptoms).The study was applied to the workers of BMS ELECTRIC Company in Algiers. In order to achieve the objectives of this study, we relied on the descriptive approach, and a sample was selected that included 46 workers in the company (manufacturing and assembly) in both branches of Bir Khadem for females and Baba Hassan for males.As for the tools used to collect data on this study, they are observation, questionnaire, interview, and a noise-measuring "sonomater".After measuring and statistically analyzing the data, these results were obtained:The workers are exposed to industrial noise [85dB-113,4dB] that exceeds the permissible limit according to the standards of the American Occupational Safety and Health Organization (OSHA).There is a strong correlation (0.72) between psychological symptoms (behavioral, cognitive, social) and the overall noise level at the significance level (0.05).There is a medium correlation (0.59) between organic symptoms (physiological, auditory) and the overall noise level at the significance level (0.05).

Bayoub Aissa, Wahiba Houda Falahi

Conference Proceedings

Development of Android-based Messaging Application for Onboard Communication for UAM Simulation

The Urban Air Mobility (UAM) concept utilizes vertical take-off and landing (VTOL) aircraft for on-demand passenger and cargo air transportation services in metropolitan areas. Various designs of UAM vehicles have been developed, but research is needed to achieve their integration with the existing national airspace system to ensure flight safety and efficiency. The concept of simplified vehicle operations (SVO) can be applied to UAM to allow for novice pilots to operate the vehicle more easily and reduce the operation complexity and demands on trained personnel for mission management. Voice-based pilot-ATC communications have been shown as a major source of workload, which will also likely impact UAM pilots. Text-based communication could potentially reduce pilot’s workload and voice communication errors. In this work, we report on the development of a messaging application for pilot and vertiport (VP) manager/air traffic controller (ATC) communications. The system consisted of an Android tablet installed with a custom application for pilots and a Windows-based application for VP manager/ATC. The text-messaging application was compared to voice communications in a user study involving pilots taking off and landing at six vertiports around San Francisco Bay area while communicating with an ATC/VP managers to acknowledge their flight plans and flight plan changes. Participants were interviewed following the study to gain insights on their perceptions of the UAM operations tested and the messaging application. The results showed that the communication mode did not affect workload, but pilots reported higher situation awareness with voice communication. A qualitative thematic analysis was conducted on the debriefing data, which provided recommendations on the design refinement. Based on the user feedback, an automated feature was added to the messaging application to facilitate the transition between vertiports. The revised interface will be evaluated in a future user study.

Justin Cheung, Maegan Schmitz, Thomas Strybel, Panadda Marayong, Vernol Battiste, Stacey Ahuja, Kim-Phuong L. Vu, Praveen Shankar

Conference Proceedings

Analyzing Large Language Model Behavior via Embedding Analysis

The usage of large language models (LLMs) as a generative artificial intelligence tool is becoming increasingly widespread, yet there is limited understanding of the mechanisms by which prompts in whole or in part influence their behavior, capabilities, and limitations. In this paper, the authors conduct a mathematical and topological analysis of token embeddings – the first step in the computational workflow of LLMs. This work shows that the subspace where token embeddings lie is a stratified manifold with varying local dimension, and in those cases where semantically related tokens are co-located on a submanifold, there are non-trivial implications for model behavior. These topological and geometric findings help to explain performance aspects of different LLMs such as why the Llemma model is more likely to overfit than the GPT-2 model, yet the latter does worse at mathematical queries than the former. To the best of the authors’ knowledge, this paper is among the first to conduct such research into the topological characterization of the token embedding space and analyze LLM behavior starting from first principles.

Sourya Dey, Michael Robinson, Shauna Sweet, Andrew Lauziere, Jonathan Daugherty, Caitlin Burgess

Conference Proceedings

A hybrid Regression method for Predicting Housing Prices

Accurate house price prediction is crucial for accommodating the diverse needs of stakeholders in the home-buying process. House prices can be affected by various factors, such as location, construction date, exterior, etc. This work proposes a hybrid regression method that leverages the strengths of different regression techniques to improve prediction accuracy. Specifically, this work looks at conventional linear regression and other machine learning techniques such as support vector regression (SVR), and XGBoost regression. Then we compare these models with our proposed hybrid regression model that leverages ridge regression and lasso regression to capture hidden relationships between house properties and sale prices to reveal the different predictive power of these models. In addition, this work also highlights feature engineering to address potential issues in the data and improve prediction performance. The dataset used in this study is obtained from the Kaggle Competition “House Prices: Advanced Regression Techniques.” Different model results are submitted to Kaggle, and the scores are illustrated in the paper.

Gaurab Baral, Junxiu Zhou

Conference Proceedings

How Wearable Technologies Enhance the Implementation of Peer Support Programs in Aviation Training

Integrating wearable technologies and affective computing into aviation training presents a promising avenue for enhancing Peer Support Programs (PSPs), a critical component in promoting pilots' and aircrew's mental health and well-being. PSPs have traditionally offered emotional and psychological support to aviation professionals, fostering a culture of mutual care and intervention. However, traditional PSPs face challenges in real-time monitoring and early detection of stress, fatigue, and emotional distress. Wearable technologies, such as biometric sensors, smartwatches, and EEG headsets, combined with social and affective computing, provide a novel approach to addressing these limitations by enabling continuous, real-time assessment of physiological indicators linked to emotional and cognitive states.This paper explores how wearable technologies can augment the effectiveness of PSPs by offering several key advantages. First, real-time monitoring through wearables allows for early detection of mental health challenges, enabling timely peer or professional intervention. Second, the data collected from wearable devices can be used to create personalized mental health profiles, allowing for more targeted support tailored to trainees' individual needs. Third, affective computing enhances peer interactions by analyzing emotional states in real time, fostering empathy, and improving group dynamics during training sessions. Fourth, wearable technologies provide real-time feedback to trainees on their emotional and cognitive states, helping them develop self-awareness and emotional regulation skills, which are crucial for high-stress aviation environments.Furthermore, integrating wearable technologies into PSPs supports a broader safety and mental well-being culture in aviation. By normalizing the use of such technologies in training, the industry can reduce the stigma surrounding mental health monitoring and encourage open discussions about psychological resilience. The paper also addresses ethical concerns about data privacy and consent, proposing best practices for handling sensitive biometric and emotional data in aviation training contexts.Based on the literature review, wearable technologies and affective computing offer significant potential to transform PSPs in aviation training. This approach provides a proactive, data-driven approach to supporting the mental and emotional well-being of aviation professionals. This integration not only enhances individual well-being but also contributes to overall aviation safety by ensuring that pilots and crew members are mentally and emotionally prepared for the demands of their roles.The presented research examines how Europe has proactively explored wearable technologies to enhance PSPs. This is partly due to EASA’s comprehensive safety management system requirements, which encourage innovation in mental health support. In the U.S., while there is growing interest in using technology to monitor pilot well-being, regulatory and cultural challenges have slowed the widespread adoption of wearables in PSPs. In both the U.S. and Europe, these technologies can:1. Improve Early Detection: Wearables can help detect signs of stress, fatigue, and emotional distress earlier than traditional PSP methods, allowing for more effective peer support interventions.2. Facilitate Personalized Support: The data collected can be used to create personalized mental health profiles, enabling more tailored support for pilots and crew members.3. Enhance Training and Performance: Real-time feedback on emotional states during training sessions can help pilots develop better emotional regulation and resilience, ultimately improving performance in high-stress environments.Finally, implementing wearable technologies in PSPs requires careful consideration of ethical and privacy concerns. In Europe, robust data protection laws like GDPR provide a model for how sensitive health data can be handled responsibly, balancing privacy with the benefits of real-time monitoring. In the U.S., the lack of a unified regulatory framework presents challenges, but the growing emphasis on safety and well-being in aviation could drive further adoption of these technologies.In conclusion, this paper examines how Wearable Technologies Enhance the Implementation of Peer Support Programs in Aviation Training, following the ICAO ADDIE approach in the USA and Europe.

Debra Henneberry, Dimitrios Ziakkas, Stephanie Brown

Conference Proceedings

Developing Building Information Relational Database (BIRD) as A Knowledge-Management System Prototype for General Contractors

The construction industry increasingly demands efficient, cost-effective, and customizable project delivery, yet existing digital integration through Building Information Modeling (BIM) encounters challenges, particularly in achieving seamless cross-department and multi-platform collaboration. Addressing these challenges, this research introduces a Building Information Relational Database (BIRD) aimed at enhancing data interoperability and supporting tailored project delivery for general contractors. Despite the advantages of BIM, general contractor and design-build firms face persistent communication and data-sharing gaps caused by fragmented workflows and limited practitioner input in technology development, which impedes innovation adoption. Current standards like CSI MasterFormat and UniFormat often fail to accommodate the comprehensive needs across a project’s lifecycle. Objectives of this study are to develop a BIRD prototype with knowledge management (KM) attributes—such as standardization, flexibility, traceability, and self-learning—while integrating practitioner-centered insights to guide development. Employing a practitioner-centered, qualitative approach, the research synthesizes industrial standards and project data to establish KM foundations, integrated with expert input through focus groups, and iteratively refines the BIRD prototype with real-world testing. Findings reveal an exemplary BIRD prototype that enhances data interoperability and cross-department collaboration, aligned with construction standards, and adaptable to various project demands. By embedding expert knowledge into system design, this study not only addresses platform discrepancies but also establishes a KM-driven development model, reducing adoption barriers and fostering a more user-centered approach to construction innovation, thereby contributing a flexible, practitioner-informed tool that is relevant for current and future industry applications.

Di Liu, Robinson Preston, Adrienne Freeman, Rui Liu

Conference Proceedings

The Impact of AI on Business Ecosystem Development

The positive effects of AI implementation on the business ecosystem are manifold. AI-powered technologies enhance productivity and efficiency, automate repetitive tasks, and optimize resource allocation(Floridi, L., 2019). Furthermore, AI algorithms enable businesses to gain valuable insights from large volumes of data, leading to improved decision-making processes and the identification of new market trends (Martin, R., & McCrae, D., 2020). However, along with the promising prospects, there are notable concerns surrounding the implementation of AI in the business ecosystem. Ethical issues, such as privacy infringement and data security, arise due to the vast amounts of sensitive information processed by AI systems. (Davenport, T. H., & Ronanki, R. (2018). Furthermore, the concentration of power in AI technologies within a few dominant players can lead to challenges related to market competition and access to AI-driven solutions.This study combines a comprehensive review of existing literature with case studies and expert interviews to provide a balanced assessment of the impact of AI on business ecosystem development. By analyzing real-world examples and industry cases (e-commerce trade company "Coupang", South Korea; "Amazon", US; etc), this research aims to shed light on the practical implications of AI implementation and identify strategies to mitigate potential risks and challenges. To evaluate the effectiveness of the framework, a prototype mobile application was developed and tested by a group of participants with visual impairments. The evaluation process included usability testing, task performance assessments, and user satisfaction surveys. The results demonstrated improved accessibility and usability for participants, highlighting the significance of the user-centered design approach in creating inclusive mobile applications.The findings of this study will contribute to the ongoing discussions surrounding the integration of AI technologies in the business ecosystem. The results will be of interest to policymakers, business leaders, and researchers, providing valuable insights into harnessing the potential benefits of AI while addressing the associated concerns.

Olga Shvetsova

Conference Proceedings

Exploring the Digital Inheritance and Commercialization Strategies of Chinese Han Embroidery from the Perspective of Generative Art

This paper endeavors to delve into the inheritance pathways and commercialization strategies of traditional Chinese embroidery patterns against the backdrop of the digital-intelligence era, with a particular focus on Hubei Han Embroidery, a non-material cultural heritage that embodies profound cultural depths and unique artistic values. As technology advances rapidly, digital-intelligence technologies present unprecedented opportunities and challenges for the preservation and transmission of traditional cultures. By analyzing the artistic features, cultural connotations, and current state of inheritance of Han Embroidery patterns, this study integrates cutting-edge theories from the field of design studies to propose a series of strategies that foster the inheritance and development of Han Embroidery patterns in the new era.Firstly, the paper traces the historical origins of Han Embroidery, elucidating its artistic charm and craftsmanship as a significant representative of Jingchu culture, encompassing intricate stitchwork, rich color utilization, and profoundly symbolic pattern designs. Subsequently, it delves into the impacts of the digital-intelligence era on the traditional embroidery industry, highlighting the potential and application prospects of digital technologies such as 3D scanning, Virtual Reality (VR), Augmented Reality (AR), and Artificial Intelligence (AI) in preserving, replicating, innovating, and disseminating embroidery patterns.In terms of inheritance strategies, this paper underscores the significance of constructing digital platforms. By establishing a Han Embroidery pattern database and developing interactive experience applications, it aims to facilitate the widespread dissemination and popularization of Han Embroidery culture. Concurrently, it advocates a cross-disciplinary fusion approach, encouraging the integration of Han Embroidery with modern design, fashion industries, and cultural creativity sectors to create new products that align with contemporary aesthetics while embodying the essence of traditional culture. Furthermore, the paper discusses innovations in talent cultivation and educational models, advocating for the establishment of an integrated industry-academia-research inheritance system to nurture a new generation of inheritors who are proficient in both traditional craftsmanship and modern design skills.Regarding commercialization strategies, this paper analyzes shifts in market demands and consumer preferences, proposing precision positioning, brand-oriented operations, and online-offline integration strategies to enhance the market competitiveness and brand influence of Han Embroidery products. Through various channels such as hosting cultural festivals, participating in international exhibitions, and expanding e-commerce platforms, it seeks to broaden the market reach of Han Embroidery products, thereby achieving a win-win situation between economic benefits and cultural inheritance.In conclusion, from a design studies perspective, this paper provides an in-depth exploration of the inheritance and commercialization strategies of traditional Chinese embroidery patterns in the digital-intelligence era, taking Hubei Han Embroidery as a case study. It presents practical proposals and recommendations aimed at contributing wisdom and momentum to the innovative development and sustainable inheritance of traditional Chinese culture.

Yang Fangchao, Bao Qian, Ding Yifan

Conference Proceedings

Sick Building Syndrome and its Relationship with Work Stress as a Psychosocial Risk: A Shopping Mall Example

Recently, buildings, residences, plazas, shopping malls, skyscrapers and towers that have been rising all over the world have begun to form our living spaces as smart structures where private, social and business lives are carried out. The fact that these closed spaces threaten the health of people living and working in them and cause diseases, has led to these buildings being called "sick building syndrome (SBS)". Sick building syndrome results in the health of people who spend time and work in these buildings being affected both physically and psychologically. The aim of this study is to reveal the symptoms of sick building syndrome and its effects on stress, which is a psychosocial risk at workplace. A cross-sectional study conducted in two randomly selected shopping malls in Turkey involved 268 employees. Research findings indicate that employees suffer from symptoms like dry throat, runny nose, eye irritation, headaches, muscle-joint pain and fatigue. Additionally, it has been observed that these symptoms intensify during peak weekend traffic Moreover, the sick buildings phenomenon increases the stress levels of employees' due to the conditions associated with enclosed spaces.

Serpil Aytaç, Şahamet Bülbül, Husre Gizem Akalp

Conference Proceedings

Non-contact physiological monitoring of heart rate, facial temperature, and respiration rate with thermal and RGB cameras

In this paper, we evaluated a non-contact physiological measurement technique using a thermal camera and an RGB camera aimed at the participant's face. The thermal camera effectively measured the temperature of specific facial regions, such as the tip of the nose, which is related to stress and mental workload. It also accurately measured respiration rate, which is an important indicator of mental state. On the other side, the RGB camera successfully measured heart rate by detecting subtle color changes in the face. However, the thermal camera was not effective in measuring heart rate, possibly due to a lack of thermal sensitivity and image resolution. Overall, our results confirmed that using thermal and RGB cameras can be a practical and discreet method for monitoring an individual's mental state. Additionally, these cameras can monitor movements and detect states of medical incapacitation, such as loss of consciousness.

Mickael Causse, Nourhen Amdouni, Rodríguez Ginés, Christophe Hurter

Conference Proceedings

An Evaluation of Capabilities, Benefits, and Challenges of Developing Digital Twin Models for Sustainable Development

Since the recent AECO industry has increasingly focused on sustainable development, with an emphasis on achieving long-term goals like enhancing eco-sustainability and durability, the demand for applying digital and revolutionary technologies has increased. Digital twin technology, enabling a digital model to represent a physical entity in real-time dynamically, has gained wide attention in manufacturing, aerospace, and healthcare. Although digital twin technology, which integrates with various digital technical tools, has been explored by some researchers, The overall understanding of how digital twin technology can be applied to sustainable construction is still unclear. This knowledge gap leads to unnecessary difficulty and hinders the full realization of digital twin capacities in sustainable development. This research conducts a literature review to examine the current state of digital twins and related technologies in the AECO industry, aiming to bridge this gap. A variety of technologies, tools, and algorithms employed in the applications of digital twin technology have been analyzed. The results present the four major processes of establishing digital twin models for sustainable development: data harvesting, data transmission and processing, modeling and simulation, and decision-making process. Additionally, four distinct scenarios within the decision-making process relevant to sustainable construction are specified. Furthermore, the digital twins' capabilities, benefits, and challenges have been evaluated. Although digital twin models cooperating with extensive technologies have capabilities and benefits in terms of modeling and visualization, real-time simulation and monitoring, data integration and analysis, and making predictive decisions in optimization, challenges still exist and need to be addressed in future applications. This review highlights the challenges of digital twin technology, including data security, data integration, and interoperability, which provides future research directions for digital twin studies.

Congjun Jin, Rui Liu

Conference Proceedings

Is Virtual Reality for Retail Marketing Research? Research Opportunities and Methods

Despite of popularities of virtual reality (VR), there has been limited studies adopting VR to investigate consumer behaviors in retail marketing settings. Thus, the objective of this paper is to propose two key areas of opportunities for VR research in the retail marketing discipline: 1) research with VR as a tool to examine consumer behaviors in VR replicas of physical stores and 2) research for VR as a new retail marketing context to investigate virtual consumption behaviors within entirely virtual worlds. Further, this study proposes using advanced VR-comparable or VR-based behavioral tracking technologies to measure consumer behavior and experience by capturing immediate, unintentional, and natural human responses, such as eye movements, facial expressions, and head motions. These direct measures can provide deep insights into consumer emotions, attention, and reactions, potentially uncovering the nature and process of consumer behavior and experience that have not been discovered by self-report methods alone.

Jung Eun Lee, Wi-Suk Kwon

Conference Proceedings

Research progress, hotspots, and trends analysis of sustainable landscape design based on bibliometrics

In order to systematically understand the research characteristics of sustainable landscape design in the international scope, grasp the current research hotspots of sustainable landscape design, and analyze the future development trend according to the current research hotspots. Taking Web of Science as the source of literature data retrieval, VOSviewe and CiteSpace were comprehensively used to conduct scientific literature metrology and draw the knowledge map from the aspects of annual output distribution, country, research institution, author, keyword clustering and reference co-citation of literature within the scope of retrieval. Visualization and analysis of research context. The results show that the annual number of publications and the overall trend of literature within the scope of search are increasing, and China and the United States are in the leading position in the research field, and the research hotspots mainly focus on: urban landscape design, ecological protection design, theoretical methods and design evaluation.

Jiejun Dai, Yi Fan Chen, Cheng Qian, Mengrun He, Feiran Sun, Suwen Liu

Conference Proceedings

Sustainable Business Model Design for Generative AI

As the future commercial development direction of digital art, AI painting provides designers with creative auxiliary functions. At the same time, it also raises a series of issues in the operation of business models, such as: How to make the generative AI industry sustainable in the domestic market? Business model? How does generative AI take root in Chinese society? What sustainability-oriented generative AI operations can be applied in bottom-up business models in the market?This study analyzes how the concept of sustainability is scientifically applied in the generative AI business model in the Chinese market. First, it conducts user research from the perspective of professional users in the creative design field who use generative AI the most. Divide users into three categories based on their usage behavior and needs: senior users, general users, design art students and other potential users. Conduct in-depth interviews, questionnaire surveys, and live interactive data collection for these three categories of users respectively, and process them through analysis From the above data, we can derive the corresponding needs of different users. Then the business model canvas proposed by Ostwald & Pinel (2009) was used as the theoretical basis of the research, and a customer (user)-centered semantic replacement of various elements related to the entire business model was constructed. , and automatically screened out influential variables through a stepwise regression model, and improved the design of the business model based on this business model structure. In this way, the demand analysis of three types of people for generative AI and the relationship model between user factors and business impact of generative AI were constructed. Based on the O2O development model, we integrate the existing resources of generative AI and drive continuous iteration and innovation at all levels such as product design, service model and user experience according to customer (user) needs, thus promoting the development of generative AI in China. Sustainable development, this research has certain reference value for the future development of AI industry business models in China in other fields.

Cuiping Zhai, Xin Hu

Conference Proceedings

From Gap to Gain: Advancing Gender Equity in Venture Capital Investing

The persistent gender funding gap in the United Kingdom's venture capital sector represents a significant economic and ethical challenge, hindering the realization of substantial new value and exposing systemic inequities. Despite growing awareness and evidence suggesting that women-founded businesses perform equally well or better, growth in investments in such enterprises remains slow. While existing research predominantly explores founder- and funder-driven causes of this gap, limited focus has been placed on effective remedies and the role of venture capitalists' perspectives in addressing this issue.This paper aims to address these deficiencies by exploring venture capitalists' views on the gender funding gap, including perceived causes and their capacity to mitigate it. The study investigates motivations and barriers to adopting inclusive practices and identifies what these practices entail. Employing an inductive, exploratory approach, this research conducted ten interviews with representatives from firms publicly expressing commitment to addressing the gender gap and compared responses to founder gender investment data.Findings reveal diverse opinions on the causes of the gender funding gap among venture capitalists, with some emphasizing supply-side factors while others focus on demand-side explanations. The study indicates that recognition of supply-side factors is crucial in motivating firms to adopt gender-inclusive practices. Additionally, this paper identifies diversity, equity, and inclusion performance management as only the first step and highlights the importance of targeted strategies around an inclusive culture, deal flow, and a diverse ecosystem as critical elements in narrowing the gap.The research culminates in the development of the Gender-Inclusive Venture Capital Investment Framework, detailing the interplay between venture capitalists' perspectives and the adoption of gender-inclusive practices. This framework organizes practice categories by implementation level, serving as a practical guide for developing targeted strategies for inclusive investing while sustaining investment performance. The paper contributes to the growing body of literature on gender equity in venture capital and provides actionable insights for practitioners and policymakers aiming to address the gender funding gap.

Daniel Rukare, Lisa Steinhauser

Conference Proceedings

Extending Fitts’ Law: a model of stroke operations in commercial applications

In the rapidly evolving landscape of smartphone technology and micro-interaction design, our research aims to extend the applicability of Fitts' Law to better understand and model the dynamics of finger stroke gestures on smartphone commercial applications. Traditional interpretations of Fitts' Law, which primarily rely on distance (D) and target width (W) to quantify task difficulty (ID) in gesture input, may not be sufficient in capturing the complexities inherent in touchscreen interactions with commercial applications. To address this research gap, we propose an adaptation of Fitts' Law that incorporates dynamic physical parameters to better align with the execution of single-finger stroke gestures. Our classification of stroke gestures into two distinct types and the introduction of three new parameters – initial swiping velocity (V_start), final swiping velocity (V_end), and maximum swiping acceleration (A_max) – form the core of our modified model. Through a series of controlled experiments, we validate our models, demonstrating clear distinctions between Type I and II stroke gestures and achieving a high level of predictive accuracy (R² > 0.9).Our findings highlight the significant influence of individual biomechanical differences on movement time (MT) within a single stroke gesture, underscoring that the performance of gestures is not solely determined by target dimensions (D and W) but also by individual factors. Despite the challenge in precisely calculating D and W for complex gesture designs, our study emphasizes that incorporating dynamic parameters effectively explains the observed gesture parameter randomness in commercial applications, thereby enhancing the ecological validity of Fitts' Law.However, acknowledging limitations, we recognize the need for further investigation into a broader range of multi-touch gestures, such as pinch-to-zoom and rotation. Additionally, it awaits a deeper exploration of how individual biomechanics, cognitive states, and task complexities interplay to influence gesture execution time. Future research should strive to fill these knowledge gaps, ultimately leading to a more holistic understanding of multi-touch gesture behavior and improved design guidelines for gestural interfaces.In conclusion, this research contributes a refined Fitts' Law model, which accurately represents two types of stroke gestures in commercial smartphone applications. We also explore individual differences, informing design principles for future gesture interactions.

Haotian Ju, Fangli Song, Wei Wang, Jun Zhang, Chen Qi, Le Du

Conference Proceedings

Feasibility and properties of cement boards with waste tyre textile fibre for non-structural applications

This research underscores the potential of waste tyre textile fibre (WTTF) to contribute to sustainable building practices by reducing environmental impact through waste recycling and improving material performance in specific construction applications. It assessed the feasibility of manufacturing cement boards by incorporating WTTF for non-structural purposes like partition walls, wall sidings, and ceiling panels and eaves. The physical and mechanical characteristics of the cement boards were investigated to identify the most effective WTTF content for optimal performance and to compare the findings with commercial cement boards (control specimens). The cement boards were manufactured by partially replacing cement with 5%, 7.5%, and 10% WTTF by weight. Testing involved three specimens per mix for density, water absorption, and thickness swelling and twelve specimens per mix for flexural strength for 7, 14, 21, and 28 days of natural curing. The results indicated that average densities decreased with increasing WTTF content, and water absorption in-creased with higher WTTF content, reaching minimum density and maximum water absorption at 10% WTTF substitution, which are higher than the average density and water absorption of the control specimens. Thick-ness swelling was 0% for the control specimens but rose with increased WTTF content in the mixes. Flexural strength improved with higher WTTF content and longer curing time, demonstrating significant strength improvements. The optimum cement board mix had 5% WTTF, which showed the highest density (1952 kg/m³), lowest water absorption (28.26%), and minimal thickness swelling (3.35%). As a result, WTTF is compatible with cement paste and holds potential for non-structural construction applications when used to substitute a portion of the cement in cement boards at a 5% ratio. However, these boards are unsuitable for areas with continuous water exposure because of their high water absorption and thickness swelling.

Anuoluwapo Kolade, Ismael Aina, Bamidele Dahunsi, Bolanle Ikotun, Damilola Oyejobi

Conference Proceedings

Towards Enhancing Awareness on Sustainable Development: A Survey of the Types, Functional Uses and Project-Level Applications of Geosynthetics

Though geosynthetics are sustainable materials in the development of sustainable civil infrastructures, there is a low level of awareness among key stakeholders in the construction industry. Hence, the low project-level applications of geosynthetics globally. This desk study enhances the awareness level of geosynthetics among industry stakeholders as it seeks to give a more comprehensive literature account of geosynthetics highlighting the main types, functional uses, and project-level applications of geosynthetics in the development of sustainable civil infrastructures. The study employed the narrative literature review approach. The outcome revealed applications of twelve (12) main types of geosynthetics in the development of thirty-one (31) sustainable civil infrastructures. Project-level applications of geosynthetics included highways, ponds, airfields, and retaining structures. The main types of geosynthetics included geotextile and geomembrane. Primarily, the functional uses of the geosynthetics included soil reinforcement, stabilization, and filtration. This study informs stakeholders in the construction industry of the available geosynthetics that could be employed in the development of sustainable civil infrastructures. Also, it provides a more comprehensive basis for future country-specific studies that seek to evaluate project-level applications of geosynthetics in the development of sustainable civil infrastructures.

Matthew Kwaw Somiah, Clinton Aigbavboa, John Bentil, Wellington Didibhuku Thwala, Henry Kwadwo Boateng

Conference Proceedings

Enhancing the Structural Properties of Mortar with Treated Rubber Crumb

The applications of mortar in infrastructural developments cannot be overemphasized owing to its significances which are evident in the formation of composite structures. More importantly, mortar is one of the best construction materials required for the construction of building blocks, filling the gaps between blocks. It is a universally acceptable construction material because of its good structural and compatibility properties such as good flexibility and transformative capacity, and good binding property. As a flexible construction material, mortar is used as binder in masonry and walling units. The applications of mortar for construction purposes have highly contributed to the development of the built environment. However, ,mortar may deteriorate by deforming into powdery after used for construction, and turning into crumbling material. Thus, this research investigates on enhancing the fresh and hardened properties of mortar using rubber crumb treated with sodium hydroxide (NaOH). The strength properties of the rubber – mortar produced were evaluated through the physical and chemical properties of rubber; the consistency, workability, setting times of rubber - cement paste; compressive and flexural strengths of rubber – cement - mortar. The chemical composition and physical characterization of rubber crumb were evaluated by determining its fineness modulus, water absorption, bulk density, ash content, metal content and fibre content according to SANS 3001-AG1 and SANS 3001-AG20. Also, the workability, consistency and setting times, compressive and flexural strengths of mortar were determined according to ASTM C 1437, SANS 50196-3 and SANS 50196-1. The results of the experiment show that, the rubber treated with NaOH has good physical and chemical properties for enhancement of mortar’s fresh and hardened properties. The rubber – cement paste’s workability increases with increase in the percentage of rubber included. Also, the consistency of the mortar paste increased by 0.5 – 2.0% with increase in the value of rubber included. In addition, the application of rubber in mortar reduced its initial setting time while its final setting increases with increase in rubber content. The addition of 1.5% of rubber crumb increased the compressive strength of mortar by 3.32%, 9.13%, and 0.21% at 7, 14 and 28 days of curing respectively. Also, 1.5% rubber crumb increased the flexural strength of mortar by 5.94% at 28 days. In conclusion, the incorporation of 1.5% rubber crumb in mortar enhanced its mechanical properties.

Abiodun Kilani, Bolanle Ikotun, Rasheed Abdulwahab

Conference Proceedings

Drivers Influencing the Adoption of Innovative Building Materials (IBM) for Sustainable Construction in Nigeria

Amidst the drive for a more sustainable future, the construction industry faces a significant crossroads, a juncture demanding a reimagining of how we occupy our built environment. Within the dynamic backdrop of developing nations, where growth and progress intersect with pressing ecological concerns, adopting innovative building materials (IBM) emerges as essential for realising sustainable construction practices. This study explores the driving factors that influence the adoption of IBM for promoting sustainable construction practices in Nigeria. Employing a descriptive analysis methodology, explicitly harnessing the mean score ranking technique (MS), this study evaluates and ranks the 14 identified drivers influencing IBM adoption. The findings of this study show that the respondents strongly agreed with all the drivers for IBM. Clients' requirements, government regulations, availability of IBM suppliers and developments in information communication technology (ICT)/technology-push are the top drivers of IBM adoption. These findings also highlight the importance of client demand, regulatory policies, access to suppliers, technological advancements, and improved operational efficiency in driving the adoption of IBM. This analysis illustrates the significant role of specific drivers in shaping adoption decisions, thus providing guidance for future policy formulations, strategic planning, and industry practices in the Nigerian construction industry.

Iseoluwa Mogaji, Modupe Mewomo, Francis Kwesi Bondinuba, Emmanuel Aboagye-nimo, Yewande Abraham

Conference Proceedings

Self-efficacy and self-regulation variation in different modes of work

The paper brings about the findings of a survey conducted in two Ghanaian universities during autumn and winter 2023. Relatively large sample (n=201) helps to shed light on sense of self-efficacy and self-regulation as outcomes of different modes of work. The working hypothesis was that sociotechnical environments are challenging due to issues with information ergonomics especially from the perspectives of users. Moreover, as more work is done in sociotechnical environments spatially dispersed and even asynchronously sense of control and self-regulation are affected. There is also an underlying question about the balance between work and life. Mixed domains are the cause of conflicts in several ways. The paper presents also implications for enhancing work life balance among the people working extensively in soctiotechnical environments.

Jussi Okkonen, Mia Laine, Reetta Oksa, Edward White

Conference Proceedings

Automated Method for Quantitative Measurement of Underground Construction Sites Using iPhone LiDAR Point Cloud Data

Electrical transmission methods vary globally between overhead and underground systems. Underground transmission is increasingly favored for several reasons, including landscape aesthetics, enhanced pedestrian safety, and disaster prevention. Overhead systems, while initially cheaper and easier to repair, pose substantial risks during disasters such as earthquakes, where utility poles may collapse, obstructing emergency response and increasing the likelihood of power outages. In contrast, underground systems mitigate these risks effectively.In regions with advanced pole-free electrification like Europe, utility infrastructure development predominantly favors underground installations to ensure both aesthetic and functional equality between gas and electrical systems. This approach has resulted in nearly complete underground utility coverage in major Western cities, contrasting sharply with Japan, where the transition from overhead to underground has been sluggish. This lag is due to post-WWII reconstruction policies which prioritized quick and stable overhead installations. Despite ongoing efforts, Japan's adoption of underground systems remains notably low.Globally, the construction of utility tunnels is promoted to optimize the use of underground space, particularly in urban centers where space is at a premium. These tunnels, housing essential services like electricity, water, and gas, are seen as a solution to urban underground congestion, a problem often referred to as the "Spaghetti problem." However, high costs and recent fiscal constraints have slowed the implementation of these systems in places like Japan.This research focuses on enhancing the construction efficiency of utility tunnels to expedite their adoption. This involves night-time construction operations including excavation, installation of conduits and "CC-Box" manholes, and subsequent backfilling. Such processes are labor-intensive and require pauses for measurement and documentation, making efficiency improvements critical.Our study leverages Light Detection and Ranging (LiDAR) technology to address these efficiency challenges. LiDAR point cloud data, employed in construction since 2004, has seen increased application following Apple's integration of LiDAR scanners in its 2020 iPad Pro and iPhone 12 Pro models. We aim to develop an algorithm to extract excavation sections from this data for precise volume measurements without reliance on Building Information Modeling (BIM).Our proposed method details techniques for measuring excavation dimensions (horizontal, vertical, and depth) at construction sites and discusses results from applying this method in field tests. These results indicate significant potential for enhancing measurement accuracy and reducing both labor costs and processing time. This research contributes to the field by providing a novel approach to utility tunnel excavation that utilizes advanced LiDAR technology for more efficient construction management and hazard prevention. The final sections of the paper summarize these findings and discuss their implications for future construction practices.

Tsukasa Mizutani, Shunsuke Iwai

Conference Proceedings

Towards Holistic Work System Design: Concept for a Method to Analyze, Represent and Evaluate Industrial Sociotechnical Work Systems

When designing industrial work systems, Industrial Engineering encounters many established and emerging challenges and objectives. These include, for example, the consideration of ergonomic aspects, the implementation of lean production principles and harnessing the technological potential of digital transformation. This initial situation reveals the relevance of a contemporary, holistic approach for the analysis, representation and evaluation of industrial work systems that considers enduring challenges and objectives while also addressing upcoming ones. To meet this need, the authors outline a concept for a substantial method structured around five key components.Component I encompasses an approach for modeling industrial work systems. Component II defines a comprehensive target system for industrial sociotechnical work systems. This target system ensures that the evaluation criteria considered in the method are derived in a target-oriented manner and not arbitrarily included in the analysis. While components I and II establish the theoretical foundation of the method, components III to V address operational data collection, data representation, as well as data analysis for the work system. Regarding data collection, component III comprises a maturity model that adopts the structure of component I and reflects the evaluation criteria pointed out in component II. component IV shows how the collected data based on component III can be used for the digital representation of the work system using the concept of the Asset Administration Shell (AAS). Component V includes a target-specific evaluation of the work system, including a derivation of recommendations for work system design. Although the paper focuses on explaining the concept of the method and the process followed to develop the method, it also outlines a prototypical implementation of the method.

Roland Hall, Simon Schumacher, Thomas Bauernhansl

Conference Proceedings

Facilitating Technology Diffusion: Unveiling the Dynamics of Emerging Technologies on Construction Project Sites

Emerging technologies hold immense promise for enhancing productivity and safety in the construction industry. However, a persistent challenge remains: Why are these innovations not used on project sites and by site workers? This study investigates the phenomenon of bottom-up technology diffusion from construction sites. By examining the dynamics at the “grassroots” level, the study explores the barriers and facilitators that influence the adoption and utilization of emerging technologies by site workers. This was achieved through a mixed-methods approach, adopting interviews and on-site observations on selected construction sites in South Africa. The study uncovers factors such as power challenges, lack of trust, lack of training, resistance to change, and inadequate infrastructure, among others. The study also identified the strategies required to overcome this challenge of achieving technology diffusion to construction project sites. Ultimately, understanding the bottom-up diffusion process is crucial for bridging the gap between technological advancements and frontline workers, paving the way for a more inclusive and efficient construction industry.

Samuel Adekunle, Beauty John, Andrew Ebekozien, Clinton Aigbavboa

Conference Proceedings

Colleague, Copilot, Companion, Controller – Roles of AI in Work Systems

We initially present some findings on the importance of artificial intelligence for current HFE research based on a bibliometric study of the proceedings of the most recent annual conference of the Human Factors / Ergonomics Society in Germany (GfA, 2024). Given that importance we discuss the duality of AI as a tool and a player in work systems and based on extant research suggest that the aspects of hierarchy and emotion are considered when designing roles for AI. Using these aspects as dimensions we span a portfolio and suggest ‘colleague’, ‘copilot’, ‘companion’, and ‘controller’ as potential roles for AI in work systems thereby contributing to the discussion and analysis of yet to be properly defined “AI-infused” work systems.

Udo-ernst Haner, Wilhelm Bauer

Conference Proceedings

Technostress and the future of work at sea

The maritime industry has experienced profound technological change since the 19th century. Advancements such as big data analysis, artificial intelligence, and the Internet of Things have enhanced the functioning of ships by modernizing operation systems and making them safer and more profitable. Nevertheless, other than intensifying the efficiency of these systems, modern technologies have also brought numerous challenges to maritime workers. For instance, research shows that the rate at which technologies are implemented in ships and the stress a seafarer is exposed to learn the functionality of new technologies has impactful adverse effects on the mental health of seafarers, termed as technostress. This paper focuses on analyzing the technostress phenomenon in the maritime industry. Mainly, it concentrates on determining the effects of technological stress on seafarers' mental health on board ships. In addition, the paper seeks to investigate the status of the international legislation on technostress. Finally, since the future of the maritime industry is assumed to rely entirely on the modernization of the operations through technological advances, this paper seeks to create awareness among the maritime stakeholders about the existence of the phenomenon of technostress and proffer intervention approaches. The results presented in this article were obtained from a research field study, considered as the first of its kind in the topic of technostress, that the author conducted on a Newly built Danish-flagged commercial vessel.

Khanssa Lagdami

Conference Proceedings

The Emerging Technology-related Stressors Scale: assessing the impact of ICTs in the hybrid context

The spread of Information and Communication Technologies (ICTs) is fundamentally altering the nature of work, products, and processes, introducing potential psychosocial, organizational, and ergonomic risks and leading to what is referred to as “technostress”. For example, ICTs compel users to work faster and longer, exacerbating feeling overwhelmed and reducing their ability to manage techno-related demands successfully. The digitization of HR practices can lead to stringent control of productivity and performance, putting the worker under pressure, decreasing autonomy, and raising privacy issues. Professionally, employees may perceive their skills as inadequate in the face of technological advancements, as ICTs perpetuate a growing skills discrepancy. This can lead to feeling unable to relocate and a diminished sense of employability. Additionally, ICTs have abstracted organizational relationships, with workers increasingly communicating through email, phone calls, and virtual conferences. This shift reduces opportunities for face-to-face interactions, negatively affecting the socialization processes that build a sense of belonging and organizational identification. To accurately capture the nuanced experiences of both in-office and remote workers, the development of new, updated measurement tools for assessing the impact of ICTs is essential. Accurate measurement can enable organizations to identify specific techno-stressors and tailor interventions accordingly.This study aimed to develop and preliminarily validate the Emerging Technology-related Stressors Scale. Items were generated using both inductive and deductive approaches, resulting in a pool of 21 items administered to 3,374 Italian employees through an anonymous online survey. The factor structure of the scale was evaluated using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), with the latter conducted on a separate sample of 852 employees from a different firm. Reliability estimates and nomological validity were also assessed. The EFA identified a four-factor structure, including technology-related demands, privacy/monitoring, employability, and technology-mediated social interactions. This structure was confirmed by the CFA, which outperformed alternative models and demonstrated good reliability. Correlations showed that the total score of the scale and each dimension were positively associated with psycho-physical distress and negatively related to job satisfaction.Accurately measuring emerging technology-related stressors is crucial for identifying their impact and developing strategies to mitigate detrimental health outcomes (e.g., psycho-physical distress) and work-related issues (e.g., job dissatisfaction). This study introduces a reliable instrument for assessing employees’ perceptions of technology-related stressors, usable by both researchers and practitioners. The results can guide the effective implementation of ICTs by identifying potential sources of techno-stress and addressing them proactively. Additionally, properly evaluating techno-stressors can provide insights into how to promote healthy technology use, such as setting boundaries for after-hours online communication and offering resources for managing digital workloads. This can also encourage practices that enhance technology-mediated social interactions, including implementing collaborative platforms, promoting peer support networks, and facilitating social activities. The scale also provides valuable information for developing targeted training programs to help employees cope with techno-stressors, improving their technological skills and employability. By identifying and quantifying techno-stressors, organizations can raise awareness among employees about the potential stressors related to ICTs and educate them on effective coping strategies, thus maintaining a healthy and satisfied workforce.

Georgia Libera Finstad, Gabriele Giorgi, Matteo Curcuruto, Valentina Sommovigo

Conference Proceedings

Enhancing Communication Transparency and Teaming in Human-Autonomy Systems: Integrating Large Language Models for On-Site Construction Operations

The integration of autonomous systems in the construction industry is rapidly advancing, driven by the need to enhance efficiency, safety, and productivity on-site. With autonomous agents evolving from mere tools to collaborative teammates, there is a critical need to understand the dynamics of human-autonomy teaming (HAT) in complex construction environments. This research addresses the gap in knowledge surrounding the communication and collaboration between human workers and autonomous agents, specifically within the context of tower crane operations, where effective teamwork is crucial for safety and task success. Despite the growing implementation of autonomous systems, research on human-autonomy teaming in construction remains limited, particularly regarding the interdependencies of key attributes like team composition, communication transparency, interaction dynamics, trust, and overall team performance. Current studies on autonomous crane operations predominantly focus on the technical aspects, such as smart sensing, perception, and motion control, with little attention given to the team-based human factors involved in these operations. The lack of comprehensive studies on how various human psychological and behavioral factors interact with autonomous systems during real-time operations presents a significant challenge, which this research aims to address. This paper proposes and evaluates a novel VR-based system architecture designed to enhance understanding of the impact of communication transparency on human-autonomy teamwork in construction settings. In addition, the integration of a Large Language Model (LLM)-enabled autonomous agent adds a critical layer to the HAT dynamic by facilitating real-time communication and decision-making. The LLM processes inputs such as sensor data, crane motion sequences, and operator commands to provide actionable insights and hazard warnings, further improving transparency and reducing the cognitive load on the operator. The agent’s ability to generate predictive models also assists with obstacle detection and motion planning, enhancing the overall safety and efficiency of crane operations. Organized into a three-layered HAT framework—(1) Team Goals (Bottom Layer), (2) Team Synchronization (Middle Layer), and (3) Team Outcome (Top Layer)—the VR environment simulates a construction job site where a semi-autonomous tower crane operates alongside a human worker. The system is designed to assess how varying levels of communication transparency, based on the situational awareness transparency model, affect the cognitive states, trust levels, and task performance of human operators during dynamic role allocation. This research contributes to both academic and industrial communities by offering a foundational architecture for studying human-autonomy teaming in construction, while the VR-based system serves as a powerful tool for future experimental research. For industry practitioners, the study provides insights into designing more effective and transparent communication systems that enhance safety and efficiency in autonomous crane operations, ultimately contributing to safer and more reliable construction practices.

Di Liu, Rui Liu

Conference Proceedings

AutoGen-based AI assistant for improving the interactions between BIM and project teams for design coordination

In the construction industry, building information modeling (BIM) has been widely utilized in design coordination. However, this process is time-consuming to query the required element information and still requires the support of the BIM coordinator. Meanwhile, during diverse participants’ discussions, it is challenging to record knowledge and experiences residing in their minds and timely respond to them in the BIM model. GPT-based Large Language Models (LLMs) enable providing automatic solutions but lack accuracy and consistency, specifically for the construction domain. To bridge these gaps, we propose to develop an AI BIM coordinator by integrating basic construction knowledge and skillset into the current AutoGen model. It aims to alleviate high-skill requirements and specific functions of traditional BIM development while enhancing the interdisciplinary interpretability and performance of AI models. Specifically, we first identify the frequent and common interactions between BIM and project teams during the design coordination meetings. Correspondingly, we build the skillset that includes basic functions regarding building element semantic, geometric, and topological information. With this skillset, our designed workflow can interpret 3D BIM space and answer specific questions from users through flexible revisions and extensions. Beyond the text responses that describe relations among elements, the BIM tool can be automatically invoked to execute this task and the model can be directly built in the 3D environment for stakeholders’ discussions in the design coordination meetings. If failed, our designed checker agent will regenerate the code until execution is succeeded. As users continually communicate with the AI BIM coordinator and provide feedback, the assistant can collect and annotate these data for fine-tuning the current model to make it more adaptive to specific construction tasks. For validation, a prototype system is developed with building design coordination meeting data. The results demonstrate that our designed workflow has better performance in execution succeeded rate (84.62%) and accuracy (76.92%) despite consuming more time (1 min 12 secs – 3 mins 1 sec) than general agent workflow.

Yaxian Dong, Zijun Zhan, Yuqing Hu, Daniel M Doe, Zhu Han

Conference Proceedings

A semantic matchmaking approach to empower human decision-making in Manufacturing-as-a-Service scenarios

Fragile and unreliable supply chains, due to environmental disasters or other disruptions are a challenge for modern production companies. The concept of Manufacturing-as-a-Service (MaaS) marks a shift from traditional manufacturing, focusing on shared, networked infrastructures. In MaaS environments, effective management of demand for manufacturing capabilities and supply of production capacity is crucial, while final decisions remain with human operators. The EU project ACCURATE (Achieving Resilience through Manufacturing-as-a-Service, Digital Twins and Ecosystems) aims to create a distributed MaaS ecosystem that offers a collaborative, human-centered Decision Support System (DSS) for robust planning and resilient operations. A primary challenge is aligning services from suppliers with the demand for physical goods, which includes transportation, warehousing, and information, in addition to manufacturing. Semantic approaches and ontologies can describe these services comparably. This paper introduces a semantic matchmaking concept in MaaS networks to empower human decision makers in supply chain management. To support this, related concepts of service-oriented manufacturing concepts are analyzed and a working definition of MaaS is derived. Based on this, an approach is presented that matches supply and demand for manufacturing services while considering product process requirements. Importantly, this is not a standalone decision-making tool but a foundation for informed choices, enabling users, like order fulfilment managers, to receive tailored offers from suitable providers based on recommendations from the semantic matchmaking service.

Frauke Schuseil, Michael Hertwig, Joachim Lentes, Nikolas Zimmermann, Katharina Hölzle

Conference Proceedings

Investigating the Use of Chatbots as an Educational Tool

With the rise of online asynchronous learning and low levels of instructor presence, students have become self-regulated learners who must monitor their performance and adapt their learning strategies as necessary. Previous studies have shown that chatbots are a promising alternative to traditional study tools such as flashcards. This study examined the effects of a chatbot’s embodiment (Humanoid, Animated) and conversational style (Formal, Informal) on learning performance and behavioral engagement. Participants were asked to watch a lecture video and interact with a chatbot to review the material. After studying with the chatbot, participants completed a quiz that was evenly split according to difficulty (easy versus hard questions), as well as study type (questions that were and were not studied with the chatbot). Participants’ ratings of usability, usefulness, ease of use, and affective engagement were obtained. Results showed that participants performed better on easy questions than hard questions. Additionally, participants performed better on studied questions than non-studied questions. However, for the informal conversational style, participants scored higher on hard questions than easy questions amongst studied questions. Embodiment and conversational style had no impact on behavioral engagement. Overall, participants rated the chatbot above average in terms of its usability, usefulness, ease of use, and affective engagement. We conclude that chatbots are an effective study tool, but they may be better suited for learning easy, surface-level knowledge. Additionally, an informal conversational style may be preferred since it matches the linguistic features used by human tutors. Limitations and future directions for research are discussed.

Krystal Cachola, Kim-Phuong L. Vu

Conference Proceedings

Research-Infused Courses are Effective for Online and In-Person Education

Engaging students in research is a high impact practice known to increase underrepresented students’ persistence in Science, Technology, Engineering, and Mathematics (STEM) fields and improve their graduation rates. For broad impact, research infusion can be implemented through careful redesign of courses or through the adoption of research modules to supplement class instruction and existing student training programs. In this paper, we present data on a program for the integration of research-infused curriculum in major courses across a variety of disciplines in STEM. Specifically, the program's goal is to have faculty engage in a redesign of the class to exemplify how specific disciplines engage in research. The course redesign can be in the form of activities for in-person education or as interactive activities for online learning. Fourteen courses were included in this analysis. Anonymous surveys were administered at the end of the fall or spring semester to 864 students in the 14 courses from Fall 2020 to Spring 2023. A total of 643 students (74% response rate) participated in the evaluation.Gains in research skills: Students indicated how much they gained in various skills (on a scale of 1: no Gain to 5: Great Gain) as a result of the course. Overall, a high percentage of students (92-96%) reported gains of some kind, while only about 4% of students reported no gains, though a slightly higher proportion reported no gains in understanding what everyday research work is like (8%). Results suggest that on average, students reported moderate to good gains (Ms ranged from 3.36 to 3.70) for all items. Most students felt they had good gains in problem-solving, understanding the relevance of research, understanding research reports, and interpreting results, and moderate gains in comfort discussing research concepts and confidence in ability to do well in research courses. Course Redesign Goals: Students also indicated high levels of agreement about three redesigned course goals: Understanding research-related ethical issues, effective communication of research, and stimulating research interest on a scale ranging from 1 (Strongly Disagree) to 4 (Strongly Agree). Most students agreed/strongly agreed that due to the course, they were able to effectively communicate research information to different audiences (80% Mode=3). Although most students agreed/strongly agreed that the course stimulated interest in research (71%, Mode=3) and helped them understand research ethics (73%; Mode=3), close to one-third of students disagreed (17-23%) or strongly disagreed (3-7%) with these statements.Intention to Pursue Research: More than half of students in the redesigned course indicated that they increased their likelihood of exploring research careers (62%), joining a research/lab training program (64%), and pursuing research-focused courses (62%).Effects of Course Modality: When examining differences by the modality of the course, there were no statistically significant differences between courses that were virtual and courses that were face-to-face for gains in research skills, (X2(1)=0.22, p=.641), research intentions X2(1)=1.30, p=.254, research career perceptions (X2(1)=2.05, p=.152), or course redesign goals, X2(1)=0.08, p=.778.Faculty who received the award found it helpful in redesigning courses to make them more interactive, problem- and research- focused. One awardee shared, “through this program, I can see more underrepresented students more interested in machine learning, data science and artificial intelligence.” Overall, the redesigned courses had a large impact on student’s research skill gains. Students reported moderate to good gains in understanding relevance of research in their discipline and skills important to research like problem solving, understanding research papers, and interpreting research results. The modality of the course (virtual vs. face-to-face) had little impact. Thus, research-focus activities intentionally embedded in courses strengthening the research foundation of students and should be encouraged as a high-impact practice.

Erin Arruda, Arturo Zavala, Panadda Marayong, Jesse Dillon, Chi-ah Chun, Kim-Phuong L. Vu

Conference Proceedings

Pre-Professor Program: A Virtual Training Program to Improve Faculty Diversity

The number of science, technology, engineering, and mathematics (STEM) degrees awarded to underrepresented students has increased over the past two decades, but these graduates still represent a small percentage of STEM career professionals (Fry et al., 2021) and faculty members (Bennett et al., 2020). For diversifying faculty, Bennet et al. identified a barrier to be the lack of programs to support underrepresented groups at the postdoctoral and early career stages. The Pre-Professor Program (PREPP) was designed to support advanced doctoral students’ and postdoctoral scholars’ transition to faculty positions by engaging them in a semester-long virtual program within the California State University (CSU) system, which consists of 23 campuses across the state of California. PREPP Fellows receive individual mentorship from an experienced PREPP Mentor who engages them during weekly meetings to explore 15 topics and a few dozen activities related to teaching, service, and research at comprehensive and ethnically diverse institutions, as well as the process for applying for tenure track positions at such institutions. PREPP Mentors also discuss tenure and promotion processes and coordinate various campus and departmental activities to introduce PREPP Fellows to campus resources and learn perspectives of faculty life within their discipline. Initially designed as a local, in-person program, PREPP morphed into an online, virtual training program that allowed the program to grow and be implemented throughout the entire CSU system. The flexibility provided by the virtual platform enabled PREPP participants to be effectively immersed in learning about faculty life at a CSU campus without requiring them to be in the local area. This paper describes PREPP and how it can be used as a model to provide a pathway for highly competitive and diverse applicants to faculty positions.

Laura Henriques, David Whitney, Chi-ah Chun, Kim-Phuong L. Vu, Arturo Zavala

Conference Proceedings

An Interactive Virtual Assistant for Flexible Just-in-Time Training

Many situations call for a person to perform tasks in which they are not an expert, and for which the person does not need (or want) to become an expert, but still needs to perform the task in the moment. Simple examples might include home maintenance tasks like changing out a furnace filter or car maintenance tasks such as refilling the wiper fluid. Performing the task might involve consulting a manual or searching the internet for relevant material. However, even when useful content is found, it’s not always easy to refer to these sources while simultaneously performing the task. Looking back and forth between a manual and the thing that needs fixing, or turning pages or typing on a keyboard when hands are occupied with tools makes the process more difficult. It can also be challenging to visually relate a diagram in a manual to the actual system being worked on, especially for non-experts. To help address these challenges, we have been developing an Autonomous Virtual Assistant (AVA) that helps someone perform a task by walking them through step by step. AVA can be thought of as an interactive helper working over the user’s shoulder to help perform the task, using different modalities and tools including mixed reality to convey information. This work has focused on being flexible to the user and the situation, both in terms of providing helpful information to the user and getting input from the user. Given a procedure, AVA determines on the fly how to present information based on what resources are available and what content needs to be conveyed. With a mixed reality setting, this might include showing text or imagery on a virtual heads-up display, or overlaying 3D imagery on the physical object being worked on to help orient the user. To make mixed reality content readily available, the system allows for easy ways of aligning 3D virtual models to the physical objects being worked on. In a situation where speech might be the only modality available, the system will read procedure steps to the user, or help the user navigate to a needed item using speech alone. To suit the user’s situation, the system also affords the user different interaction modalities, such as touching virtual buttons, pointing to objects in the real world, or using voice only in a heads-up, hands-free manner. The user moves through procedure steps and related information and asks questions if they need clarification or more detail. Example interactions include initiating a session (“Okay AVA, start the wiper refill procedure”), requesting visual material related to a task (“What does that look like?” or “Show me that image”), or asking for more information on procedure step (“How do I do that?”). AVA uses the content and resources at hand to help the user complete the procedure. In this paper, we describe the motivation for AVA, the system design, its application in some real-world tasks, user feedback from hands-on evaluations, and future directions.

Glenn Taylor, Jeffrey Craighead, Kortney Menefee, Logan Lebanoff, Christopher Ballinger, Stephen Mcgee

Conference Proceedings

Advanced Chunking and Search Methods for Improved Retrieval-Augmented Generation (RAG) System Performance in E-Learning

Our study evaluates different search methodologies—Hybrid Search and Semantic Search—within a Retrieval-Augmented Generation (RAG) framework specifically for E-Learning. The primary objective is to enhance the accuracy and efficiency of using Large Language Models (LLMs), such as GPT-4, by employing advanced Prompt Engineering Techniques in E-Learning environments. Efficient search and chunking methods are critical for optimizing the quality of answers provided by these systems.To achieve this, we utilized the RAGas testing framework, focusing on performance parameters including Answer Correctness, Context Recall, Context Precision, Faithfulness, and Answer Relevancy. In our implementation, documents were divided into text chunks and indexed in a database using both vector and keyword indexing. This allowed for searches by vectors for similar records and keyword searches for exact matches. These records were then incorporated into prompts as context to improve LLM responses. The AI model used for generating embeddings, such as OpenAI's text-embedding-ada-002, plays a crucial role in this process by creating high-dimensional representations that capture deep semantic meanings.Current retrieval methods, like keyword and similarity-based searches, often fall short due to limitations in chunk quality, which directly impacts the accuracy of the RAG system. This study aims to improve the retriever component and, consequently, the overall accuracy of the RAG system by comparing three different chunking methods and two search approaches. We conducted tests using 57 questions across multiple files under various configurations.This research examines different search methods, including Hybrid Search, which integrates traditional keyword search with semantic search in order to provide more accurate and contextually relevant results. In comparison, Semantic Search utilizes deep learning models to comprehend the context and meaning of search queries and documents, thereby providing more precise information retrieval. The analysis also compared different chunking methods, such as Recursive Chunking, which divides text into hierarchical sections that are further subdivided until the desired granularity is reached. BERT Chunking utilizes the BERT model to segment text, taking semantic meaning into account to ensure coherent chunks. Token Chunking segments text based on individual tokens, offering fine-grained control over segmentation.Our results, evaluated using the RAGas testing framework, highlight the strengths and weaknesses of each search method and chunking technique. This study provides valuable insights into optimizing RAG Systems for E-Learning through advanced Prompt Engineering Techniques, aiming to improve knowledge transfer regarding efficiency and accuracy.

Daniel Danter, Heidrun Mühle, Andreas Stöckl

Conference Proceedings

Elementary Students' Reflection Tool, Content Suggestions, and Discussion

Children's inability to take ownership of their own learning might lead to a reduction in motivation and effectiveness. Metacognition and reflection can improve learners' thinking and learning efficacy; this is now the most popular strategy among college students, but there are no rules or suggestions for elementary school students. There has been past research on reflection, and through literature review, data collecting and analysis, a questionnaire for students was produced. This study will build on the previously specified reflection tool and investigate the material's usefulness for students. Through expert interviews discussing the content and guidance methods of the reflection questions, as well as interviews with four current elementary school teachers, we understand the actual application and situation of reflection strategies in teaching, which serves as the foundation for subsequent revisions of sentences, questioning methods, and content. The experts were found to have similar ideas about Teaching Reflection and the questionnaire's content. In addition to Teaching Reflection, the process of group competition should begin with topics that are of interest to the students and have a high level of relevance to their lives in order to keep their interest and efficiency in learning reflection. The questionnaire should be tailored to include a specific subject, a clear task, and easy language, and it is preferable to ask students quantitatively about their emotions or feelings at the appropriate time. With these adjustments, the reflection tool and questionnaire material are appropriate for an elementary student.

Yi Hsuan Tsai, Johan Chang

Conference Proceedings

Determination of Women Patentees and Their Impact on Participatory Ergonomics

This study examines the role of women inventors in patents and their impact on participatory ergonomics in design. The primary objective was to explore the relationship between the presence of women inventors in patent fields and the academic disciplines from which they graduated. Using correlation testing, the study analyzed the relationship between the number of women inventors in patent sectors and the degrees awarded to women in specific fields. The data was drawn from extensive databases containing patent records and information on the educational backgrounds of women inventors. This approach allowed for an assessment of how participatory ergonomics influences the patenting activities of women, particularly in areas related to their academic training. A similar analysis was conducted for male inventors to provide a comparative perspective. The study showed that women inventors are more likely to engage in patenting within fields that align with their educational backgrounds which differed from that of male inventors. Despite the increasing number of women earning degrees, there remains a significant gender gap in patent filings. This suggests the presence of systemic barriers or disparities. The study also recommends strategies to increase women’s participation in patenting, such as creating supportive environments in academia and the workplace, addressing biases, and encouraging inclusivity in innovation-focused industries. Overall, this study provides valuable insights into the contributions of women inventors to participatory ergonomics in the patenting process, and it adds to the ongoing discussion on gender equity in innovation.

Lake Crowell, Quintin Williams, Irina Buhimschi, Heather Weinreich

Conference Proceedings

Improved teaching and education of engineering students using computational fluid dynamics

This paper studies the use of computational fluid dynamics (CFD) to enhance students' understanding as an effective educational and learning method. The improved educational method studies the impact of CFD implementation in course project on students' comprehension and performance in fluid mechanics course. Implementing the CFD method is increasingly essential specifically for Mechanical Engineering students, and it can also be applicable to variety of fields, including Science, Technology, Engineering, and Mathematics (STEM). One of the most important improvements of using CFD in course teaching is the strong comprehension and improved students’ performance related to the fluid movements, frictional affect, pressure and velocity variation. This was evident through the strong interactive teaching in classroom. The use of simulation related to the studied fluid flow case has proven to be effective in enhancing student attention and improving their understanding of fluid mechanics.

Fadi Alnaimat, Bobby Mathew

Conference Proceedings

Innovation and Trends in Human Resources: Analysis of Improvement Strategies in Graduation Projects from a Master's in HR and Human Talent Management

This study analyzes the improvement strategies in the area of Human Resources (HR) proposed in 67 graduation projects (Master's Final Project) over the last 3 years from two master's programs of the Faculty of Economics and Business at Andrés Bello University: Master in Human Resources Management and Management Skills and Master in People Management and Talent Management. Using quantitative and qualitative techniques, the study examines trends and the degree of innovation in the projects presented by students. The focus is on the relevance of these strategies in addressing current challenges in the field, including talent retention, diversity and inclusion, and digital transformation. The results point to significant progress in applying modern theories and cutting-edge talent management practices. This analysis provides a valuable perspective on the evolution of HR practices and serves as a resource for academics in improving educational practices and for professionals interested in the ongoing development of the sector.

Nelson Lay, Luis Felipe Vergara Maldonado, Andres Rubio, Paula Riquelme

Conference Proceedings

A framework for developing collaborative community building tools for novice Computer Science students

Students enrolled in introductory computer science courses tend towards individual work because of pedagogical practices discouraging collaboration and a focus on individual assignments. This can discourage new computer science students and may negatively affect persistence in computer science. In contrast, social learning theory research suggests a connection between student success and their level of involvement with peers, instructors, and in the greater learning community. Motivated by these contrasting conclusions, the research presented in this paper puts forth a framework based on social learning theories and teaching and learning methodologies to leverage social computing as a learning tool. This framework’s primary objective is use as the foundation for the development and testing of tools used to stimulate social interaction in problem-solving environments for introductory programming students and, as a result, building stronger social networks within learning communities. Following the implications of social learning theory, this paper theorizes that use of tools using this framework will not only result in a stronger, more connected, social network but will also contribute to greater success in student learning outcomes. The research presented in this paper follows a mixed-methods approach with meta-analysis used to develop the framework and an iterative, user- and learner-centered design approach to develop the software tools. User-centered design is the base of our design approach, but learner-centered design helps maintain focus on the important questions we must keep in mind in the design and assessment of this tool: how can we make people more effective learners, adopt our tools (for students and instructors), and promote peer collaboration? How should learning opportunities be scaffolded in a social computing environment? How should we motivate learners to remain engaged and form connections? The framework presented in this paper emphasizes the following requirements for tools to stimulate social interaction in a learning environment. 1) Motivation generating techniques to increase user interaction with the software tools. 2) Scaffolded activities to structure and stimulate community engagement to encourage interaction with the tool and the community. 3) Focused social interaction and gamification features to foster learner success by encouraging competition and community building. Meeting these requirements should promote higher levels of interaction and may lead to improved learning outcomes, attitudes, and social connectedness. In essence, tools founded on this framework will be the focus of a social hub for learning activity and build on the social computing experience. The chosen platform and delivery for this universal tool, as presented in this research, is via a Visual Studio Code extension due to its wide adoption and cross-platform support. Tools built from this framework are based on the necessity of a universal tool focused on encouraging and building a social learning environment; one that supports collaboration and problem solving, provides support for instructor guidance and constraints, and are structured to support many problems new computer science students face in the classroom. Further, the framework developed in this paper sets the foundation for future research testing the efficacy of interventions built around a social computing hub where problem solving takes place.

Daniel Olivares, Jakob Kubicki, Katie Imhof

Conference Proceedings

Education and Training Using Digital Twin in Hazardous Chemical Manufacturing Plants

Manufacturing industries face significant challenges in equipping new employees with the requisite skills to operate complex machinery, especially in hazardous sectors like chemical engineering. Traditional on-the-job training poses substantial risks and is limited by space and budget constraints, making it difficult for educational institutions to replicate industrial environments adequately. The acquisition and customization of equipment to meet diverse industry demands are prohibitively expensive, exacerbating these challenges. In response, Digital Twin technology offers an innovative solution. By creating virtual replicas of physical environments, Digital Twins provide a virtually boundless digital space at minimal operational costs. This technology enables avatar-based interaction and collaboration, bridging the gap between theoretical learning and practical industry practice. New employees and students gain immersive experiences that facilitate a nuanced understanding of complex industrial systems, ensuring a smoother transition into real-world work environments. This paper delves into existing theories and literature on Digital Twin technology, focusing on its implications for education and training. We introduce DTLAB, a bespoke digital twin framework tailored for hazardous chemical manufacturing plants. Leveraging cutting-edge technologies, including Virtual Reality (VR), the Internet of Things (IoT), Robotics, Data Technologies (DT), and an AI Virtual Chat-GPT Trainer (AIVCGT), DTLAB creates a hyper-realistic training environment. Participants engage with virtual replicas of chemical plants, benefiting from seamless data exchange between physical and virtual workspaces. Additionally, we employ the AIVCGT approach to evaluate users' learning efficiency and engagement levels within digital twin simulations. This research highlights the potential of Digital Twin technology to transform educational practices, empowering individuals to thrive in an increasingly complex industrial landscape.

Jihoon Shin, Juhyung Son

Conference Proceedings

Using Media Equation Theory to Assess Anthropomorphism of Intelligent Virtual Reality Training Systems in Organizational Settings

The advent of immersive virtual reality (VR) media technology is revolutionizing communication by providing a platform that goes beyond traditional video, audio, and static web pages. These new media technologies allow users to engage in life-like, anthropomorphic interactions with both humans and non-human entities within immersive environments. Notably, this technology holds the potential to address and solve cultural and societal issues through more meaningful and effective engagement. This research explores the application of an intelligent VR media system in diversity, equity, and inclusion (DEI) training, highlighting its potential to enhance organizational training. Unlike traditional one-size-fits-all approaches, which may fail to meet the specific needs of different organizations—whether corporate, academic, or non-profit—VR-based DEI training offers a tailored, impactful experience. Rooted in media equation theory, which posits that humans react to media as they do to other humans, the study presented in this paper investigates how immersive VR can better equip individuals to navigate complex cultural and societal challenges.The findings suggest that successful DEI training via VR involves three critical components: an engaging and immersive user experience, the use of storytelling as a key communication tool, and interactive media to enhance learning effectiveness. Effective user experience design, supported by a strategic human-computer interaction framework, significantly boosts the impact of DEI training. Immersive environments, when well-designed, enhance learning by providing realistic contexts that mirror real-world scenarios, thereby aiding in practical understanding and memory retention. Additionally, VR creates a safe space for exploring sensitive issues, encouraging open dialogue and reflection without real-world consequences. Interactive scenarios can be customized to align with an organization's specific DEI goals, ensuring relevance and applicability to workplace situations. Ultimately, VR transforms DEI training from a passive learning experience into an active exercise in empathy and understanding, making it more engaging and meaningful for participants.

Michael Oetken

Conference Proceedings

Enhancing Flight Deck Resilience and Optimizing Risk Mitigation: A Sociotechnical Approach

The flight deck operates as a sociotechnical system where the interplay between human operators and technical components is essential for safety. Socio-processing capacity encompasses the cognitive, communicative, and collaborative abilities of pilots to manage information, coordinate with crew members, and make informed decisions. Effective aviation safety models depend on seamless collaboration, where pilots can openly admit mistakes, seek help, and provide feedback. However, research indicates that pilots may shift from clear communication to silence when the flight deck environment lacks psychological safety, undermining the Threat and Error Management (TEM) model's efficacy. This paper argues that enhancing pilots' socio-processing capacity through advanced interpersonal skills training and fostering a culture of psychological safety can bolster the resilience of the flight deck. Such improvements not only enhance risk mitigation but also lead to reduced risk and increased safety.

Kimberly Perkins

Conference Proceedings

Analysis of student perceptions of the use of business process modelling in improving organisational operations

The main objective of the article is to identify and compare students' awareness of the possibilities of using business process modelling to improve organizational operations. The survey was conducted at the beginning of 2023 in the first and final year of studies at the University of Warsaw, which at the same time allowed to compare the impact of the implementation of the study program on increasing awareness of these possibilities. In addition, the results of the survey were compared with an analysis of the core curriculum. The research was conducted using the CAWI method. The questionnaire prepared for this purpose was first reviewed by experts in the field of business process modeling and then made available on the University of Warsaw servers for students to complete. The research showed that the interest in business process modeling among students entering the University of Warsaw is not very high and that emerging innovations in this field are not known. From the point of view of the University of Warsaw, it is important to note that more than 90% of the students received basic information about Business Process Modeling at the University, so they will be able to use BPM systems in their professional work. The most significant and encouraging information is that almost half of the students graduating from the University of Warsaw use business process modeling systems in their professional work. The conducted study had its limitations - it was conducted in 2023 in only two university faculties (the Faculty of Management and the Faculty of Journalism, Information and Bibliology). It is recommended to increase the number of subjects in the area of business process management in university curricula, which will allow a deeper understanding and a modern approach to the interpretation of economic phenomena. On the basis of the research it was proved that despite the average knowledge of students about computer-based modeling of business processes, they consider it essential for the improvement of business operations.

Małgorzata Oleś-filiks

Conference Proceedings

Recommendations and Discussions on the Use of Role Play in Online Social Studies Teaching for Elementary School Students

Online teaching is increasingly being utilized in elementary education. However, elementary school students' learning performance in digital environments can be affected by online distractions and a lack of interactivity. Role play offers a highly interactive and immersive learning experience that can help students adapt to the online environment. To better achieve the teaching goals of the core competencies -- “thinking” and “teamwork” -- outlined in Taiwan's Curriculum Guidelines of 12-Year Basic Education for Social Studies, this study explores the integration of role play into Social Studies teaching. To understand the learning challenges students face in Social Studies and provide recommendations for designing role play courses, this study interviewed three Social Studies education experts. The findings reveal that the extensive and complex historical knowledge in Social Studies can make learning difficult for students. The study suggests incorporating “pre-class preparation,” “thought-tracking,” “peer assessment,” and “reflection and discussion” into role play activities. These results offer valuable materials and suggestions for designing online role play courses in Social Studies, aiming to enhance students' learning performance in online classes.

Yifeng Zhong, Johan Chang

Conference Proceedings

Education and Training in the Technological Era: Adopting the Head, Heart, and Hand Approach for Effective Social Media Usage

The various industrial revolution from the first industrial revolution birthed water- and steam-powered manufacturing facilities, the second industrial revolution birthed electrically powered mass production, the third industrial revolution led to the birthing of computers and Robots, while the fourth industrial revolution welcomed Cyber-physical systems and the internet. The advent of computers and the internet has led to the use of social media platforms such as Facebook, Twitter, and Instagram, which can be used for work and for communication. The workers who will need these platforms will be those who are already employed, as well as those who need to be employed Hence, requisite skills (which could be both hard and soft) are required to use these platforms effectively. This study is based on the use of secondary data sources such as articles and journals using inductive and semantic approaches and thematic analysis. The study aims to promote the effective utilization of social media for work and communication through the Head, Hand, Heart Approach to Education and Training. The study reveals that the Head and Hand approach, which is cognitive learning and practical doing, provides the workers with the necessary hard skills to use social media. The Heart approach, which is affective learning, relational knowing, and emotional involvement, provides workers with the necessary soft skills to use social media for communication. The study contributes to scholarly discussions on workforce education and training in the digital era, as well as empirically contributes to the effective management of the workforce of the future.

Fortune Aigbe, Clinton Aigbavboa, Lekan Amusan, Ayobami Idowu

Conference Proceedings

Evaluation of new measures of spatial ability and attention control for selection of naval flight students

Each year, several thousand applicants take the Navy’s Aviation Selection Test Battery (ASTB), a test battery designed to assess whether an applicant has the cognitive capability to become a naval aviator or flight student. The battery is comprised of measures of crystalized intelligence (subtests for math, verbal, mechanical, and aviation and nautical knowledge) as well as non-crystalized measures (e.g., psychomotor, attention, spatial and task-switching abilities). The present study investigated three new double conflict measures of attention control as well as a new measure of spatial ability, the terrain orientation task (TOT). While the ASTB already includes a measure of spatial ability called the direction orientation test (DOT), the DOT has several limitations. For example, Coyne et al. (2022) showed that scores on it were significantly improving over time and that the test was progressively losing its ability to predict training outcomes. A major limitation of the DOT is that it has a fixed and small pool of only 48 items. Motivated test takers can, and do, find ways to access and practice the test to perfection, likely contributing to the significant ceiling effect observed in test scores more recently. The new spatial ability measure evaluated in the present study addresses many of the practical concerns of the DOT, such as the ability to accommodate an unlimited number of test items of varying difficulty as informed by more advanced analytic techniques such as item response theory.The new attention control measures under evaluation here are three double conflict tasks, double in that there can be a conflict/incongruency in both the stimulus and response portions of the tasks. The tests were developed by the Randall Engle’s lab at Georgia Tech as improved and very short (under 3-minutes each) variants of traditional attention tasks known as Stroop, flanker, and Simon (Burgoyne et al., 2023). Preliminary analysis at Georgia Tech revealed the tests are reliable and valid indicators of attention control that also predict individual differences in multi-tasking ability.In the present study, we collected data on the new TOT and three new double conflict attention control tasks from 114 Naval Flight Students prior to their start of the Navy’s initial ground school training. We also had access to ASTB scores and outcome data from ground school for all participants. The results showed that both the TOT and the double conflict flanker tests were significantly correlated with grades in ground school, but only the flanker test added incremental validity to the prediction of ground school grades over the ASTB. The sample had an unusually high attrition rate and neither the new lab measures nor the ASTB ground school composite score predicted attrition. While the sample from the current study is relatively small, it does provide preliminary evidence that both the TOT and double flanker tests should be further examined as potential selection measures included in future versions of the ASTB.

Joseph Coyne, Christopher Draheim, Ciara Sibley, Cyrus Foroughi, Sarah Melick, Nicholas Armendariz, Alexander Burgoyne, Randall Engle

Conference Proceedings

Collecting Anthropometric Data from the Perspective of Ergonomics. A Learning Experience for Industrial Engineering Students

The correct collection of anthropometric measurements is crucial in the field of ergonomics, especially for the design of tools and workspaces that adapt to the physical characteristics of the users. This article presents an educational proposal for industrial engineering students in a Public University in Mexico, focused on the teaching of anthropometric data collection techniques from an ergonomic perspective. The implementation of this proposal aims to improve the training of future professionals in Industrial Engineering with a solid knowledge of the application of ergonomics, ensuring the accuracy and relevance of the data collected in real contexts. The methodology used in the study included the design of a theoretical-practical educational programme, implemented in a university course from the perspective of institutional design and using theBenjamin Bloom’s cognitive levels and Gerald Grow’s model of self-directed learning by stages. The effectiveness of the programme was assessed through tests of practical knowledge and the accuracy of data collected by the students in supervised practice. The results of the study showed a significant improvement in the students' theoretical and practical knowledge of anthropometric measurement collection and its application in a real project. The study concludes that the educational proposal implemented is effective in teaching students the techniques of collecting anthropometric dimensions using a real case study and that students approach the problem from its real context and not just the reading of the problem, which allows them to learn to apply theoretical knowledge.

Stephanie Daphne Prado Jimenez, John Rey-Galindo, Rosa Rosales-cinco, Carlos Aceves-gonzalez

Conference Proceedings

Citizen participation; a lever for the success of major events

Hosting major sporting, business or cultural events is an incredible opportunity to reveal and promote the strengths of the host territory. The organization of a major event generally generates socio-economic benefits and ensures territorial attractiveness in the short, medium and long term. In addition, beyond the fact that the event would constitute an accelerator of development, it also becomes an identity marker that will be an integral part of the identity and image of a territory in the future. Except that this event is mainly for the inhabitant, for the citizen, who is mainly concerned with territorial development.In this same vein, it is important to remember that the literature and practice in several territories has shown that the resident can play at least four roles in relation to his territory: he is from the outset a direct target, it can be an argument for promoting the territory, a partner in the construction of the attractiveness process and finally an ambassador and a passionate lawyer who can easily influence the decision of other targets.Finally, it should be noted that our analysis would only be relevant if the territories undertake an endogenous approach in the sense that they will involve citizens, deepen the relationship with them and encourage them to contribute to the development of their own hospitality and involve them in the approach of territorial marketing alternating the endogenous approach to the exogenous of territorial attractiveness. This would allow the territories to keep on site the resources already acquired by the territory (territorial hospitality) and then develop strategies around its ability to shine and attract the desired targets on the spot (attractiveness). The topic = falls at the right time with the announcement of the organization of the 2030 World Cup between Morocco, Spain and Portugal, a staggering opportunity to have a real case of discussion.The purpose of this research is to open the debate around the impact of the organization of this great event on the country-territory globally and on the host territory especially.The reflexivity around this article is to know how the Moroccan population perceives the organization of such an event? What opportunities do they see there that are so widely read that the Moroccan population strongly adheres to the quote of Mandela and Gandhi who says «everything that is done for me without me is done against me»? and how would they contribute to it? This leads us to ask ourselves several questions: Is the Moroccan involved? if so, what citizen participation tools are available to territorial decision-makers to involve the citizen? We chose a multi-target device incorporating the three targets of territorial marketing (inhabitants and territorial decision makers) and a methodological mix combining two approaches conducted simultaneously; a qualitative approach for an in-depth investigation, and a quantitative approach for a measured diagnosis. The purpose of this research would be to provide territorial decision-makers with tools that can enable them to better involve the citizen to ensure the key function of the organization of a major event; that it is above all a development accelerator.

Yasmine Alaoui, Khatb Majda

Conference Proceedings

Investigation of the contemporary value of dialects and proposals for their utilization – Possibility of maintaining cultural identity and regional promotion –

Japan has a wealth of dialects, each a unique reflection of its local culture and individuality. Recent advancements in information technology have accelerated the spread of these dialects, leading to their use across different regions. This study aims to analyze contemporary dialect usage and propose an event concept that promotes regional identity and serves as a beacon of hope for preserving these linguistic treasures. A questionnaire was conducted with approximately 100 people aged 20-60, and AI text mining analyzed the responses. The results showed that dialects remain vital in communication, especially in close relationships. Native region dialects were commonly used in daily conversations with family and friends, while dialects from other regions spread through media, serving as communication accessories. These findings underscore the importance of dialects in enriching communication diversity and preserving regional culture. Based on the results, an event focusing on dialects and regional promotion will be proposed and evaluated. This event, we believe, will not only enhance appreciation and understanding of these linguistic treasures but also pave the way for their preservation and continued use in our rapidly changing world.

Sato Gai, Namgyu Kang

Conference Proceedings

Meeting practical requirements for assessing competencies: A framework for a multi-dimensional, layer-based and dynamic model

With digitalization and automation, today's economy is undergoing fundamental changes. Organizations are facing increasing complexity and dynamism, coupled with demographic shifts that require changing workforce skills and organizational flexibility. To ensure a sustainable competitive advantage, it is necessary to efficiently deploy employees based on demand. In addition, a method for early identification and targeted development of future competencies within an appropriate forecasting horizon is required. Building on theoretical foundations, this paper examines the practical challenges of describing and assessing competencies. It also examines the interrelationships between competencies and between competencies and external factors. The paper categorizes competencies based on hierarchical level and task composition, and examines relationships between competencies and external factors. It proposes a novel multi-dimensional, layered, and dynamic competency model as a holistic approach to competency management and forecasting. Finally, this paper outlines steps for validating and implementing the model, and assesses its potential for practical application in organizations navigating the evolving digital landscape.

Steffen Jansing, Julian Schallow, Paula Danhausen, Nele Schulte-uebbing, Gerrit Hoeborn, Jochen Deuse

Conference Proceedings

Team Creativity and Innovation: What Matters?

Extensive research has been conducted on team creativity and innovation. Past research has allowed for scholars to gain a better understanding of the various factors that influence team creativity and innovation. There are different factors that influence team creativity and innovation. Mittone et al. [1] list risk preferences, past performances, and the consequences of failing to innovate as factors that influence creativity. Burpitt et al. [2] mention that leader empowering behavior is a factor that influences innovation. Past research has been unable to present and illustrate the various relationships between the factors listed above. The gap in knowledge lies wherein researchers have not yet identified the relationships between the factors and how these relationships influence team creativity and innovation. The research problem revolves around the need to identify and illustrate the relationships between the various factors that influence team creativity and innovation. The objective of this research is to formulate a method by which these factors can be presented. A cohesive framework, about team creativity and innovation, will be established. This framework will consist of the various relationships between the factors and how these factors influence one another. This framework was inspired by the components of creative performance proposed by Amabile [3]. In this framework, motivation, domain knowledge, and problem-solving ability are the three primary factors directly impacting team creativity while they can be affected by organizational influence, team members’ influence, and individual personality. Team Creativity is about how a team can develop original and innovative solutions to a problem. It is directly impacted by motivation, domain knowledge, and problem-solving abilities. It focuses on the idealization while innovation stresses implementation. Resources include resources required in implementing a creative solution in different forms such as materials, technologies, tools, human resources, etc. Implementation process is the actual process in which utility and value are realized. Many creative ideas and solutions can’t be realized due to many different reasons and constraints. Therefore, these ideas do not lead to actual innovations. It is those creative ideas that are fulfilled and become practical innovations. In the innovation stage, team creativity and resources are the two inputs to the implementation process. During the implementation process, utility and value is achieved and inputs are converted into innovation outcomes and results. In addition to the framework posed, the researchers will explore the most important factors underlining team creativity and innovation by eliciting knowledge from innovation experts and industry leaders. To obtain information, we will design a survey that consists of open-ended questions. We will leverage the connections we have in order to obtain information from students in addition to industry professionals that are actively supervising digital innovation projects. These industry professionals can be CIOs, Project Managers, Entrepreneurs, etc. We will strive to ask open-ended questions for each construct in the proposed team creativity and innovation framework. An example question can be “based on your experience, what are the most important issues in organizational influence that has impacted team creativity and innovation?”[1] Mittone, L., Morreale, A., Vu, T. What Drives Innovative Behavior? An Experimental Analysis on Risk Attitudes, Creativity, and Performance. Journal of Behavioral and Experimental Economics, 98. 2022.[2] Burpitt, W.J., Bigoness, W.J. Leadership and Innovation Among Teams: The Impact of Empowerment. Small Group Research, 28(3), 414-423. 1997.[3] Amabile, T.M. The social psychology of creativity: A componential conceptualization. Journal of Personality and Social Psychology, 45(2), 357-376. 1983.

Daniel Badro, Xiaowen Fang, Olayele Adelakun

Conference Proceedings

The Awakening Role of Design in Social Innovation

Amidst societal transformations including economic, political, social, cultural, and ecological realms, social innovation has emerged as a burgeoning field of research and practice. Influenced by societal demands, there has been a paradigm shift in design methodologies and objectives. Diverging from conventional process-oriented design approaches, this paper advocates for an outcome-oriented perspective. It comprehensively explores how design can catalyze "awakening" in social innovation through its intervention at the levels of objects, actions, and outcomes. By emphasizing this shift, the paper offers insights into how design can effectively engage with and contribute to social innovation endeavors.This paper conducts a literature review to analyze the current status and characteristics of social innovation and social innovation design. 1) Social Innovation: Social innovation projects possess four fundamental attributes: innovativeness, practicality, societal participation, and locality. They generally follow six developmental steps: problem identification, action theme determination, involvement of relevant stakeholders and institutions, solution formulation and implementation, retrospective analysis (forming event prototypes), and promotion and diffusion (becoming an incubator). 2) Social Innovation Design: Social innovation design aims for societal transformation, driven by social change, engaging in collaborative design activities. It solely aims at catalyzing positive social change, differing from traditional design in research methods, design objects, and output outcomes. 3) Design intervention in social innovation is not only a necessity for the development of social innovation but also an inevitable consequence of the evolution of design discipline. Existing design tools have accumulated a wealth of mature innovation methods and have been widely applied in fields such as product design, interaction design, and service design. However, due to the lack of a comprehensive discipline system in social innovation design, the role of design in social innovation often remains underutilized. Design requires a more proactive approach to address societal changes.This paper comprehensively discusses how design can play a constructive role in various stages of social innovation through specific case analyses of six social innovation projects including the Di Gua Community and Otera Oyatsu Club. Using deductive reasoning, the paper analyzes and summarizes the perspectives and methods of design intervention in social innovation, concluding that design can "awaken" social innovation in terms of its objects, actions, and outcomes—awakening social consciousness among individuals and facilitating communication between individuals or organizations; stimulating participants' innovative thinking and actively engaging them in social innovation activities, becoming project drivers; and transforming participants into a group with design thinking, some of whom may evolve into future initiators of social innovation, forming a virtuous cycle. This design approach is defined as "social awakening design," aiming to provide researchers with a conceptual framework for design intervention in social innovation and encouraging rational design involvement in social innovation projects.

Zhaoyi Kang, Yijun Liu, Mengfei Liu

Conference Proceedings

Exploring Driving Style Variations When Driving in Work Zone: A Driving Simulation Study

Traffic safety hinges on individual driving styles, which can vary within a single trip through a work zone. A work zone, with its limited visibility, heavy machinery, and unexpected traffic flow, is a major contributor to a high number of traffic accidents. Driving style has a significant effect on driving behavior and directly impacts driving safety. However, studies on the variation in driving styles in the specific scenario of driving through a work zone are still missing. Also, most studies used either surveys or machine learning methods for classifying driving styles, while there is a lack of comparison between these two classification methods. To address the gaps, this study aims to detect and classify variations in driving styles when driving through a work zone and compare the results obtained from the self-evaluation method with those from the machine learning method. Firstly, a lane closure work zone was simulated by Webots and SUMO, based on a real-world case of an urban road section in Indiana state. Daytime and nighttime scenarios were included to analyze variations in driving styles. Secondly, sixteen participants were invited to drive through the road section with a lane closure work zone using a driving simulator. Their driving speed, as well as acceleration and deceleration, were collected by Webots. Then, the K-means algorithm was used to classify three types of driving styles (aggressive, normal, or calm) based on the total non-linear traits in the driving data (eg, speed, acceleration). Finally, a self-evaluation survey on driving styles was conducted after the driving simulation experiment, and a comparative analysis was performed between the self-evaluation survey data and the driving simulation data. The results show that 1) The percentage of aggressive driving style was 51.6%. Participants tended towards a calm driving style at nighttime compared to daytime, and the normal driving style remained consistent across both daytime and nighttime; 2) There were significant differences between self-evaluation and K-means method on driving styles. Compared to the results from the K-means method, drivers tended to overestimate their normal driving style and underestimate their aggressive driving style based on the results from the self-evaluation method.; and 3) There was an observed increase in calm driving style before and during the work zone, contrasting with a rise in aggressive driving tendencies after exiting. The results may help understand the variance of driving styles in a work zone and improve the classification accuracy of driving styles by comparing the differences between driving data evaluation and post-survey data evaluation.

Ze Wang, Hongyue Wu, Yunfeng Chen, Jiansong Zhang, James L Jenkins

Conference Proceedings

Application of Emerging Technologies in Electric Vertical Take-Off and Landing CBTA Training

The advent of electric Vertical Take-Off and Landing (eVTOL) aircraft signifies a transformative shift in urban air mobility, promising to revolutionize transportation in densely populated areas. As the industry evolves, the need for specialized training methodologies becomes paramount to ensure the safety, efficiency, and effectiveness of eVTOL operations. The Competency-Based Training and Assessment (CBTA) approach, rooted in tailoring instruction to specific competencies required for operational roles, presents itself as an optimal framework for eVTOL pilot training. This paper explores the application of the CBTA approach enhanced with emerging technologies in the context of eVTOL training, highlighting its potential to address the unique challenges posed by this emerging technology.Traditional pilot training methodologies, designed around fixed-wing and rotary-wing aircraft, are increasingly inadequate for the novel demands of eVTOL operations. eVTOL aircraft differ fundamentally in terms of design, operational environment, and flight characteristics, necessitating a training paradigm that is both adaptive and comprehensive. The CBTA framework, endorsed by the International Civil Aviation Organization (ICAO) for its focus on developing specific competencies, is well-suited to meet these requirements.This paper outlines the core competencies essential for eVTOL operations, including situational awareness in urban environments, energy management, automation management, and emergency response. These competencies are mapped against the unique operational contexts of eVTOLs, which include low-altitude urban navigation, integration with existing air traffic management systems, and the potential for highly automated flight. By aligning the CBTA approach with these competencies, we propose a structured training program that can be adapted to various eVTOL models and operational scenarios.The paper further discusses integrating emerging technologies, such as virtual reality (VR) and artificial intelligence (AI) -Simulated Air Traffic Control Environment (SATCE) into the CBTA framework to enhance training efficacy. VR can simulate complex urban environments, providing pilots with immersive training experiences that closely mimic real-world conditions. AI-driven adaptive learning systems can personalize training modules, ensuring that each pilot achieves mastery of the required competencies at their own pace. These technologies enhance the learning experience and offer scalability and flexibility, which are critical for the widespread adoption of eVTOL operations.Moreover, the paper examines the regulatory implications of adopting a CBTA approach for eVTOL training. As eVTOLs represent a new category of aircraft, regulatory bodies must adapt existing frameworks or develop new standards to accommodate the specific needs of this technology. The CBTA approach offers a robust foundation for such regulatory development, focusing on measurable outcomes and continuous assessment, which align well with aviation authorities' safety and operational performance standards.We also present case studies from early adopters of eVTOL training programs implementing the CBTA approach, as the F.A.S.T case study. These case studies provide valuable insights into this training methodology's practical challenges and successes. The findings suggest that while the CBTA approach is highly effective, its implementation requires significant investment in curriculum development, instructor training, and technology integration.Finally, the paper addresses the future of eVTOL training within the broader aviation ecosystem. As eVTOL technology continues to evolve, so must the training programs supporting it. The CBTA approach, emphasizing continuous improvement and adaptability, is well-positioned to accommodate these changes. However, the success of this approach will depend on close collaboration between industry stakeholders, including aircraft manufacturers, training providers, and regulatory bodies.In conclusion, implementing the CBTA approach in eVTOL training represents a critical step forward in preparing pilots for the challenges of urban air mobility. By focusing on competency development, integrating advanced training technologies, and aligning with regulatory requirements, this approach can ensure that eVTOL pilots have the skills and knowledge necessary to operate safely and efficiently in complex urban environments. This paper contributes to the growing body of research on eVTOL operations. It provides a roadmap for developing effective training programs that can support the safe and sustainable growth of the eVTOL industry.

Dimitrios Ziakkas, Debra Henneberry, Konstantinos Pechlivanis

Conference Proceedings

Analyzing the Factors Influencing Scooter Usage and Safety Among Young Riders in Taiwan

Approximately 1.24 million people die every year on the world’s roads, and another 20 to 50 million sustain nonfatal injuries as a result of road traffic crashes (WHO, 2013). Unfortunately, this number has not changed significantly over the past 10 years. Worldwide, traffic accidents are the leading cause of death for people aged 15-29 years and the ninth leading cause of death across all age groups (WHO, 2015). According to the World Health Organization (WHO, 2005), motor vehicle accidents are the second most frequent cause of death for individuals aged 5-29 years, and projections indicate that these figures will increase by about 65 percent over the next 20 years unless new commitments to prevention are made (WHO, 2004). In Taiwan, statistics from the Directorate General of Highways indicate that in 2020, there were 14.97 million licensed scooter riders, among whom approximately 1.42 million were young people aged 18 to 25, representing nearly 10% of the total. A significant number of young individuals are involved in scooter accidents. Data from 2020 show that among the fatalities within 30 days of road traffic accidents, 293 were scooter riders aged 18-24 (including those riding large scooters). The age group 18-19 exhibits the highest fatality rates from scooter accidents. Additionally, the injury rate for individuals aged 18-29 is three times higher than for other age groups. The highest incidence of scooter accidents occurs among students and young professionals. This study aims to explore potential alternative transportation options for young people and their demand for such alternatives. We plan to conduct a quantitative survey among students aged 18-24 to understand their perceptions and attitudes towards transportation modes, their experiences with scooter use, and their satisfaction levels. We aim to collect at least 100 and up to 500 valid questionnaires for statistical analysis. The results will provide insights into the primary reasons young people in Taiwan use scooters as a means of transportation and identify potential demands for alternative transportation methods or enhanced safety designs for scooter riding. Ultimately, the goal is to propose suggestions for improving road traffic safety for scooter riders.

Huang Fei-Hui

Conference Proceedings

Measurements of preferred heated seat temperatures for providing thermal comfort for drivers

With global climate change exhibiting drastic temperature changes, drivers will need more robust protections especially within colder climates. Since heated seats are in direct contact with a driver's body, it is the most efficient device in maintaining a driver's body temperature in cold environments. However, because thermal comfort thresholds differ for each person and vary depending on demographic factors (e.g., gender, age, and even ethnicity), the temperature range provided by existing heated seats are insufficient. The goal of this study is to set an effective temperature range by analyzing the relationships between environmental air temperatures/humidities and preferred temperatures of the heated seat for various demographics. In this study, measurements of the preferred heated-seat temperatures, in seated postures, were obtained from various people of four ethnicity groups (Asian, African American, Hispanic, and Caucasian) and two age groups (20-40 vs. 40-60) in three ambient temperature conditions (e.g., -7°C, 0°C, and 7°C). An environmental chamber capable of providing various temperatures and humidity levels was used in conjunction with a specially designed seat that allows participants to precisely control the temperatures of six areas within it (e.g., upper-back, lower-back, seatback bolster). By utilizing the collected datasets, statistical relationships between the air temperatures/humidities in the vehicle and the participants’ selected heated-seat temperatures were quantified. Furthermore, the effects of age, gender, and race on preferred heated-seat temperature will be quantified. The study result will provide the optimal ranges of preferred heated-seat temperatures for automobile manufacturers in designing heated seats.

Jangwoon Park, Hongwei Hsiao, Hoang Wong, Baekhee Lee, Kang Yen Lee, Joo Hwan Son

Conference Proceedings

Data Acquisition and Processing for the Optimization of an Algorithm for Vehicle Safety Objective Rating Metrics and Injury Severity Prediction

evaluation and the most common ORM is CORA (Correlation and Analysis). Currently, no standards exist for the evaluation of CORA: it is up to the researcher to determine whether or not to use its software (CORAPlus) and what parameters they deem important for analysis. This high level of subjectivity shows there is a need for a more streamlined approach for the data processing of the CORA ORM. The goal of this research is to develop a systematic approach for future researchers to process and analyze the CORA ORM consistently. Data acquisition and preprocessing are an important part of this process. This paper describes how data can be extracted from the NHTSA Biomechanics Database which is comprised of over 15,000 biomechanical tests in an online repository, and how data can be filtered and processed to generate matched time histories for ORM processing. This proposed approach of data processing and optimization is the basis for the development of an algorithm that correlates objective rating metric similarity scores and injury severity. It has the potential to contribute to the improvement of vehicle safety.

Katelyn Williams, Steven Jiang, Devon Albert

Conference Proceedings

Expectations of Emergency Communication Systems in Autonomous Bus Shuttles

The advancement of public transportation through the integration of autonomous bus shuttles offers significant potential for improving multi-modal mobility systems. However, the absence of onboard driving personal presents a unique challenge, particularly during an emergency. Consequently, an easy-to-use communication system is essential for autonomous bus shuttles in such situations.This paper supports the designs of such systems by investigating passenger preferences for emergency communication systems in autonomous bus shuttles, and how these preferences are influenced by the type of emergency and passenger demographics. In particular, the paper addresses a gap in understanding which communication modalities passengers prefer in different emergencies, such as fire, medical emergencies, or robbery. To explore these preferences, an online survey was conducted with 114 participants, who were asked to assess their likelihood of using different emergency communication options. These options included audio or video calls to a service center, chatbots, SOS buttons, step-by-step guides, and written reports, all accessible via collective (public tablets) or individual (smartphones) devices.The results of the survey show statistically significant differences in passenger preferences depending on the nature of the emergency scenario. For instance, in scenarios involving fire or medical emergencies, audio calls to the control center emerged as the most preferred communication method. This preference underscores the importance of real-time, direct communication with human operators during such events. Video calls were also favored, particularly on collective devices, suggesting that passengers value the ability to visually communicate with the control center during emergencies.In contrast, the preference for using an SOS button was highest in the event of a robbery, indicating a need for discreet and immediate communication options that do not draw attention to the passenger. This preference highlights the importance of providing silent interaction mechanisms in autonomous bus shuttles to enhance passenger safety during potentially dangerous situations.The survey results also reveal gender differences in communication preferences, with women showing a greater inclination towards using audio and video calls in emergencies. This finding aligns with existing research indicating that women generally have higher safety concerns in public transport, particularly in autonomous vehicles where there is no human driving personal present.Based on these findings, autonomous bus shuttles should be equipped with multiple emergency communication options to cater to different types of emergencies and passenger needs. The inclusion of both interactive (audio/video calls) and passive (SOS buttons) communication systems can help ensure that all passengers feel safe and supported in the event of an emergency.While the study provides valuable insights into passenger preferences, it is based on survey data and hypothetical scenarios, which may limit the applicability of the findings to real-world situations. To address this limitation, the next phase of the research will involve developing prototypes of emergency communication systems and conducting usability tests in a laboratory setting adapted for autonomous bus shuttles. In conclusion, the paper emphasizes the importance of designing user-centered emergency communication systems for autonomous bus shuttles, considering the varied preferences and needs of different passenger demographics and emergency scenarios.

Cindy Mayas, Rozita Sheibani, Matthias Hirth

Conference Proceedings

Assessing driver engagement in assisted driving: Insights from Pilot Evaluation, Focus Groups and driving simulator testing

Automated driving assistance systems (ADAS) have become increasingly prevalent in consumer vehicles, particularly at L2 level, offering various degrees of safety and comfort. However, many concerns arise regarding driver attention and engagement, as drivers may not fully understand the system limitations and their continued responsibility for vehicle control. For this reason, driver engagement is a topic of significant interest in the context of ADAS development. The European Commission is already working on future regulations regarding the integration of advanced L2 systems from a safe driving perspective, as is the NHTSA in the US. Driver engagement is included in the EuroNCAP 2030 roadmap and is also being considered as one of the criteria for the assessment of Smart Cockpit according to C-ICAP (2023). This work introduces a methodology aimed at evaluating driver engagement, which combines proving ground testing, focus groups, and dynamic driving simulator testing. Proving ground testing combines subjective metrics such as mental workload and trust, together with objective measures like Time to Collision (TTC). Results indicate differences in driver engagement between medium and advanced level 2 systems, with participants showing higher trust and lower mental workload in advanced L2 systems. Focus groups highlight generational differences in perceptions of ADAS, with younger participants demonstrating higher trust and acceptance. Also, situational awareness emerges as an important factor for a proper engagement. The upcoming driving simulator phase seeks to validate these findings in a controlled environment, integrating physiological measures and eye-tracking. Future steps include conducting cross-cultural studies to capture diverse driving habits and preferences.

Francesco Deiana, James Jackson, Cristina Periago, Elena Castro

Conference Proceedings

Enhancing the mental health through a multisensorial experience in the vehicle interior

Mental health is becoming increasingly important in today's society. More and more people are turning to mindfulness exercises, relaxation techniques, and sports to unwind, alleviate stress, and enhance resilience. However, amidst the stress of daily life and the constant demands of work, family, and leisure activities, many individuals still struggle to find time to nurture their mental well-being. An often-overlooked opportunity to do so lies in daily commuting. In German cities, daily commute times can reach up to 60 minutes due to traffic jam and heavy traffic. This time can be used more effectively, especially with the increasing automation of vehicles, to focus on the personal health. In order to investigate this potential, an innovative multisensory experience was developed for the vehicle interior of a ride-hailing vehicle to promote mental health. This experience was implemented in a real vehicle and examined for its efficacy in a user study. To shape the experience, insights from psychology, environmental psychology, and design research were combined to respond to the passenger's emotional and physical states during the journey. The approach is based on chromotherapy, where different light colors and intensities are used to reduce physical and mental illnesses. Furthermore, an acoustic guidance for a breathing exercise, based on the success of Pranayama practice, was developed to be practiced simultaneously by the passenger, along with a haptic element on the belt, which further enhances the emotions during the experience. The immersive experience is individualized based on an analysis of the LIMBIC types, i.e. personality models, in order to achieve the greatest possible relaxation effect.The research methodology included comprehensive literature review on existing concepts and technologies, expert interviews with both light and sound designers as well as psychologists, and two quantitative user surveys to gather requirements and define specific design elements of a holistic immersive experience. Based on the preliminary work and findings of a previous study on light combined with a breathing exercise to enhance mental health, a multisensory concept was developed and integrated into a Hyundai Ioniq 5. To achieve this, legroom on the rear bench was expanded, the driver's cabin was shielded, flexible LED panels were attached to the back of the front seats, and a 360-degree sound system was integrated. Additionally, a belt concept was designed, equipped with vibration sensors that can transmit controlled haptic impulses to the passenger during the journey. To test the success of the designed experience, a qualitative user study was conducted with 12 participants. For this purpose, a travel scenario was recreated, which all passengers had to go through. Before and after the journey, the participants were interviewed about their well-being during the entire testing period. In parallel, the vital data heartbeat and electrodermal activity were collected through a wearable device (wristband) in order to compare them with the personal assessments. The results of the ongoing study will be presented in the full paper. In summary, based on the previous interviews and quantitative user studies, there is a need for applications to improve mental health. There is also a demand to use commuting times more effectively for personal well-being, particularly in the future with automated driving. The positive effects that have already been achieved in the areas of light and sound interaction as well as breathing exercises for relaxation also speak in favor of a combination of the principles. After conducting and analyzing the user study with the prototype, the insights into the success of the immersive multisensory experience will be presented in the final version of the scientific work. In conclusion, this paper emphasizes the importance of design innovations in the field of mobility that prioritize the psychological well-being of users. The research illustrates that by skillfully combining technology and design psychology, vehicle interiors can be created that actively contribute to mental health and thus provide added value to society.

Franziska Braun, Koray Hergül, Alina Bachofer, Katharina Bolius, Antonio Ardilio

Conference Proceedings

Advancing Perspectives: A Scoping Review of Artificial Intelligence Applications in Aviation Human Factors for Flight Crews

The Federal Aviation Administration (FAA) under FAA Order 9550.8A defines Human Factors (HF) as a "multidisciplinary effort to generate and compile information about human capabilities and limitations and apply that information to equipment, systems, facilities, procedures, jobs, environments, training, staffing, and personnel management for safe, comfortable, and effective human performance" (USA Banner, 2024). The rapid evolution of Artificial Intelligence (AI) across various industries including aviation, has dramatically impacted the overall safety, performance status and future sustainability of the aviation industry and its operational ecosystem. Specifically, AI applications in aviation HF have the potential to transform flight operations by enhancing the safety, performance, and well-being of flight crews. AI tools can assist in monitoring physiological and psychological states, improving decision-making processes, and optimizing workload management. This scoping review aims to explore the breadth of AI applications in aviation HF, focusing on their effectiveness, implementation challenges, and areas requiring further research. The main objective of this scope review is to add perspective in terms of the wide variety of tools available through within the domain of AI related to HF for flight crews in aviation. All this, while keeping focused on three major constants in aviation, that of safety, performance and overall efficiency of the existing and future human-environment interaction.

Abner Flores, Alexander Paselk, Ian Mcandrew

Conference Proceedings

IMU-based Assessment of Rider Kinematics in Motocross - a pilot study

In vehicle development, the simulation of the mechanical system is already well advanced, while especially in two-wheelers the factor ‘rider’ is mostly simplified or fully omitted. In Motocross sports, the athlete’s posture and weight shift play a substantial role for efficiency and performance. The absence of objective measurement data alongside subjective feedback underscores the need to quantify rider and motorcycle kinematics during different Motocross maneuvers. In this pilot investigation, two male participants were riding on a Motocross circuit with two combustion motorcycle variants for six laps. Inertial measurement units were used to analyze the athletes’ postures during a cornering and jumping maneuver in the field by recording the position and orientation of all body segments as well as the approximation of the approximation of the center of mass. The results showed that between the two analyzed motorcycles, differing knee and hip angles and center of mass characteristics could be observed in specific parts of the maneuvers performed. Movement patterns can be identified and can help to analyze kinematics depending on varying motorcycle characteristics. Based on these results, conclusions about efficiency and performance can be drawn to assess and improve riding technique of motorsports athletes and aid vehicle development. In further steps, the data could be used to build a more realistic rider model for different riding scenarios to improve simulation routines.

Marie Ostermeier, Sigfrid - Laurin Sindinger, David Marschall

Conference Proceedings

Advanced Sustainable Mobility: A Novel Human-Machine Interaction Approach Supporting Energy-Efficient Driving

Growing awareness of environmental issues and the constant pressure to reduce greenhouse gas emissions have prompted the automotive industry to research and develop sustainable solutions. Battery electric vehicles (BEVs) are considered as a key element in reducing dependence on fossil fuels and minimizing driving-related emissions from road transport. While technological innovation is driving the adoption of BEVs, range in relation to driving and operating strategies remain a fundamental challenge. One solution to this challenge is the application of so-called “eco-tips” in vehicles, which enable and support optimal human-vehicle interaction and thus guide the driver towards more environmentally friendly driving and operating behavior. Therefore, modern eco-tips approaches focus on increasing energy efficiency and maximizing range by striving for an innovative, human-centered design. Moreover, contemporary vehicles feature advanced recuperation systems capable of converting kinetic energy into electrical energy, further enhancing their eco-friendly credentials. Eco-tips encompass a spectrum of recommendations, ranging from fundamental behavioral adjustments like anticipating traffic flow to sophisticated real-time suggestions leveraging technological innovations. Drivers are encouraged to refine their driving styles by adopting smoother acceleration, maintaining consistent speeds, and maximizing the use of regenerative braking mechanisms. Despite the strides made in integrating eco-friendly features into modern vehicles, there remains untapped potential for enhancing the effectiveness of eco-tips and ensuring their seamless adoption by drivers without causing distractions or compromising safety. This necessitates the exploration of innovative approaches, such as user-friendly human-computer interfaces and gamification strategies, to incentivize eco-friendly driving practices and extend the range of electric vehicles. In this context, this study undertakes a comprehensive analysis of the underlying objectives of eco-tips, delves into the rationale behind specific recommendations, evaluates the current state of their implementation across vehicle platforms, and proposes a novel approach for developing an advanced, holistic, and adaptive eco-tips system tailored to individual drivers’ preferences and driving habits. By leveraging insights from human-computer interaction research, the proposed eco-tips system aims to enhance user engagement, facilitate seamless interaction between drivers and vehicles, and contribute to the broader goal of fostering environmentally sustainable mobility solutions.

Christoph Stocker, Alexander Kreis, Mario Hirz

Conference Proceedings

Evaluation of the Risky Behaviors of AV Rideshare Vehicles in San Francisco

Background. Autonomous vehicle (AV) technology has been touted as a means to reduce traffic accidents because computers always pay attention to road conditions and are never intoxicated, which are responsible for most traffic accidents. However, research has been mixed regarding whether AVs actually are involved in fewer collisions than vehicles driven by human operators. Much research has shown that most collisions involving AVs have been collisions in which they have been rear-ended by other vehicles. While this research has suggested that such rear-end collisions are caused by improper maneuvers by the AV or short following distances by the human driver, there has been no research identifying the types of AV behaviors that may result in rear-end collisions. Properly identifying such behaviors would be useful for determining what measures may be most effective in mitigating risks of collisions. Methods. To help identify AV behaviors that may contribute to rear-end collisions, we examined incidents involving AV rideshare vehicles in San Francisco, California in 2023. Descriptions of these incidents were provided in an online database that had been gathered from multiple media sources. Most of these media incident reports were not of collisions, but of incidents that could cause collisions, and therefore could be considered near-miss or potential incidents. Research has shown that evaluating near-miss incidents can provide valuable information for how to reduce the risk of injury incidents. There were 343 separate and verified incidents described in the media. The latter included 18 collision incidents. Results. The results indicated that most of the media-reported incidents (65%) involved AVs that were stopped or stalled in intersections or travel lanes when they had the right of way or exhibited other unexpected or erratic behavior such as sudden lane changes. Such unexpected behavior can result in emergency responses from human drivers, including emergency braking that may result in rear-end collisions. The media reports also included descriptions of a substantial number of incidents (21%) in which the AV committed the types of errors performed by human drivers such as illegal left turns, failing to yield to pedestrians, blocking crosswalks, and running red lights. AV manufacturers claim that AVs will reduce accidents by eliminating the type of human behavior that causes accidents such as inattention and willingly violating traffic laws. These incidents show that AV manufacturers have failed to prevent these human-type behaviors. Discussion. The results are discussed according to basic human factors principles that must be followed to design AVs that may have the best chance of success in truly reducing AV traffic accidents.

Kenneth Nemire

Conference Proceedings

Assistive Technology System for Highly Automated Vehicles to Support People with Mild Cognitive Impairment: A Human-Centered Design Approach

Older adults with mild cognitive impairment (MCI) experience difficulties in memory, processing speed, attention, judgment, and visuospatial skills, which may impede the ability to perform various daily activities efficiently, including driving. The emergence of highly automated vehicles that do not require human intervention may offer significant benefits to individuals with MCI as these vehicles can increase mobility and independence. However, individuals with MCI may still be required to perform higher-level activities during a ride, which can be challenging for this user group. This research is focused on designing and prototyping a system that can help during trip planning and when interacting with an automated vehicle during normal and emergency operations. The proposed assistive technology system includes a secure mobile app, a real-time traveler monitoring system, an interactive in-vehicle agent for emergencies and safety functions, and a platform integrating all sub-systems with vehicle operations via a dashboard. The initial system requirements were identified through a series of interviews and focus groups with stakeholders, such as subject matter experts and older adults with and without MCI. Iterative participatory design sessions were further conducted to establish the information architecture and create visual and interactive designs. A final evaluation session with five individuals with MCI was conducted and showed favorable results in terms of system usability.

Alexandra Kondyli, Andrew Davidson, Chris Depcik, John Haug, Lyndsie Koon, Sanaz Motamedi, Mahtab Eskandar, Wayne Giang, Boyi Hu, Eakta Jain, Heng Yao, Xilei Zhao, Abiodun Akinwuntan, Shelley Bhattacharya, Hannes Devos

Conference Proceedings

Auto-generating Road Trip Vlogs While Safe-driving: a Human-Vehicle-Environment System for Capturing and Editing Scenic Views En Route

Road trip vlogs have gradually become popular content for sharing among people. This study introduces an artificial intelligence (AI)-based road trips video editing system, designed with a primary purpose of preventing traffic accidents caused by drivers recording scenic views with smartphones while driving. To enable the dashcam to automatically capture materials of interest, it is crucial to define the starting-ending time and content. Data monitoring around the Human-Vehicle-Environment (HVE) is a critical factor for establishing the capture rules. Guided by audiovisual language theory, the captured video materials are used to support intelligent editing. Furthermore, stylization in editing, including narrative lyrical and documentary style, is another design factor to achieve diversity in videos. Research results demonstrate that the synergy among the HVE elements is a pivotal factor in capturing key visuals. Using AI to complete road trip videos can reduce traffic accident risks and promote the effectiveness of recording scenic views.

Zichun Guo, Xianning Meng, Haiqing Xu, Zumeng Liu, Lingkan Wang, Jiawei Chen, Yaxin Zhu

Conference Proceedings

Usability Factors and Guidelines for Climate Control Interfaces Using Big Data from Vehicles

Understanding user behavior accurately and designing interactions based on this understanding is essential for providing an enhanced user experience. This study focuses on vehicle climate control systems, aiming to quantitatively analyze user operation frequency through real-time data collected from the vehicles. By examining this behavior, the research seeks to provide actionable insights to optimize interaction design and improve the in-vehicle user experience.VCRM (Vehicle Customer Relationship Management) data was collected from approximately 70,000 vehicles whose drivers subscribed to and consented to connected services. This data is derived from the vehicles’ CAN signals and diagnostic communications, including real user information across various driving environments. The data, linked to details such as driving time, date, and weather conditions, allows for an analysis of macro-level usage patterns over time. For instance, while driving distance did not significantly influence operation patterns, interactions with the climate control system became simpler when driving speeds exceeded 30 km/h. This suggests that drivers tend to rely more on automatic controls at higher speeds, reducing the need for manual adjustments.Based on these insights, this study proposes several guidelines for optimizing climate control system layouts. Frequently used functions should be placed in easily accessible locations, while less commonly used or automated functions can be positioned farther away. This strategy aims to reduce cognitive load while driving and enhance driver safety. Furthermore, the study highlights the importance of customizable interfaces that adapt to different driving conditions and user preferences, allowing for a more personalized experience.In addition to proposing these guidelines, this study developed a concept for integrating them into an IVI (In-Vehicle Infotainment) system. This optimized layout was tested through user experiments, which demonstrated improvements in task completion times and reduced driver distraction. Eye-tracking data particularly revealed that drivers spent less time focusing on the system, thereby lowering cognitive load during operation.By utilizing real driving data instead of traditional surveys or lab-based experiments, this study presents a novel approach to accurately analyze user behavior. This data-driven methodology facilitates the design of more intuitive and user-centered vehicle interfaces, simultaneously improving both safety and user satisfaction. This study underscores the importance of data-driven UX design and offers valuable insights for the future direction of automotive interface design.

Jeewon Han

Conference Proceedings

Use of ANSI/HFES Human Readiness Level to ensure safety in automation

This paper explores and describes the Human Readiness Levels for implementing control centres managing automated system remotely. We have explored a case from the oil and gas industry managing production facilities and a case from an automated ferry in the maritime industry. The concept of Human Readiness Level (HRL) is inspired by the Technology Readiness Level (TRL) originally promoted by NASA in the ´70s. We have not found case description of HRL in the oil and gas industry or in the maritime industry. TRL was used to establish a common understanding of the state of technology development from concept to operations and has been adopted by government and industry. TRL has been adopted by API (API17N) to be used in the oil and gas industry to ensure good decisions about the inclusion, development, and integration of new technology in complex systems. The purpose of the HRL taxonomy is to assess the readiness of a technology to be used by the intended users in a defined operational context. As concepts of automation, AI and remote operations is continuously implemented we have observed the challenge of missing focus on human systems design, Human Factors (HF), and organizational readiness, leading to poor safety, productivity, and usability. Combining technology optimism with the knowledge of human factors as described by the HRL guidelines (ANSI/HFSE 400-2021) should help establish a common understanding of the state of human readiness from concept to operations. This is needed, as we have observed that poor focus on HF design has been a significant root cause (i.e., 60% to 80%) in accidents and failures. We have seen “human errors” as a cause i.e., a result of poor design and poor consideration of human possibilities and limitations. We see the need to prioritize the early phases of development (such as concept and design) since the cost of changes is increasing nearly exponentially as the development moves forward from concept through design. The lifecycle cost may be 100-1,000 higher in later phases than in concept or early design phase. We have used the standard ISO 11064/ISO 9241-200 as a framework for development, and the CRIOP method as a supporting tool to perform verification and validation of the development. The purpose of this paper is to describe key challenges related to automation and meaningful human control from the oil and gas industry and the maritime industry. How the HRL taxonomy can improve and support safety, productivity and usability by key tasks and key products/documentation in relation to a system engineering model as described by ISO 11064/ISO 9241-200. How industry and government can utilize the HRL guidelines to mitigate the key challenges and reduce risks in an optimal manner to reduce cost of change and appropriate Management of Change (MoC).

Stig O Johnsen, Hedvig Aminoff

Conference Proceedings

The Consequences of Poor Human Factors at a Super Critical Coal Power Plant, A Case Study

This case study will provide an overview of the impact that a lack of human factors integrated into the operation of a super critical coal fired power plant (CPP). The CPP was of modern design, with a digital control system; however, the plant lacked human core human factors considerations, such as: human factored procedures; sufficient operator training; adequate supervision of the workforce; poor to nonexistent labeling; and operating staff frequently operating outside of procedures and standard practices. The significant consequences of this absence were that the plant’s turbine was destroyed twice, and the generator was destroyed once. The cost of the damage was in the tens of millions of dollars. The CPP was owned by a major utility and supplied power to several smaller, local utilities. The following is a specific example of how the lack of human factors led to the costly damage at this CPP, in this case turbine damage. The plant was in a startup phase and an operator heard some chatter on his radio and left his duty station to discuss what he heard with a fellow operator. The operator then proceeded to the turbine lube oil (TLO) skid. The TLO supplies lubrication and coolant to the turbine. It also provides the seal for the generator’s hydrogen coolant. The operator, unsatisfied with his understanding of the situation, decided to adjust the TLO valve. The TLO valve is a 6-way valve. The 6-way valve was manipulated inappropriately by the operator and turbine lube oil was shutoff to the turbine and generator hydrogen seal. Communications did not occur between the control room personnel and the operator prior to position changes; plan of action was not validated with other operators prior to taking the action. The mental model of the worker did not align with the potential consequences of operating a valve for oil flow to the turbine running at 3600 RPM. The consequences of turbine damage were caused by a failed mechanical stop in the valve, which allowed the valve to fully isolate turbine lube oil. Further, human factors was not considered with regard to the operation of the valve. There was no clear way to ensure proper valve lineup, e.g., no markings, no immediate feedback that desired end-state was achieved. At the time there were no procedures for operating the valve and training on operating the valve was lacking. In fact, the valve had only been operating a few times in the life of the CPP, despite the the original equipment manufacturer recommending regular manipulation to ensure working order. The turbine was severely damaged and a small explosion occurred in the TLO filter due to hydrogen back up into the tube oil. The generator was not affected in this incident. Animations of the TLO valve incident and a detailed description of this incident will be provided during the presentation.

Lee Ostrom, Torrey Mortenson

Conference Proceedings

Optimization of the Size and Distribution of Phase Change Material (PCM) in Firefighters’ Turnout Gear

In 2022, approximately 65,650 firefighter injuries were recorded on duty, marking an 8% rise from the 2021 tally of 60,750 injuries [1]. The majority of these injuries took place during fireground operations, with burns and thermal stress accounting for about 15% of such incidents [1]. Given this problem,a pressing need exists to advance turnout gear technology for better thermal protection for firefighters. Our proposal involves integrating phase change material (PCM) into firefighters' turnout gear to enhance its protective capabilities through utilizing the large amounts of latent heat of fusion. Our study involves numerical simulations, serving as a guide for future experimental designs and testing protocols to streamline efforts and time investment. Notably, existing numerical investigations on fire protective clothing predominantly employ one-dimensional (1D) models [2], lacking a comprehensive three-dimensional (3D) turnout gear-equipped human thermal model to assess the overall thermal performance of turnout gear on the body. Therefore, our study represents a pioneering effort, being the first 3D numerical analysis aimed at determining the optimal dimensions of PCM and strategically placing PCM segments within the turnout gear to maximize thermal protection coverage while minimizing the PCM quantity required. MethodsWe conducted 3D heat transfer simulations using COMSOL Multiphysics (COMSOL, Inc., Burlington, MA 01803, USA). To accommodate firefighters' movements and activities in fire scenes, PCM was divided into multiple segments covering the main body while avoiding joints to maintain firefighter body movement and activities. The bioheat transfer module in COMSOL was utilized to model the human body's thermal regulation. The equivalent heat capacity method was employed to simulate the phase change process. Adhering to the guidelines of the National Fire Protection Association (NFPA 1971), Standard on Protective Ensembles for Structural Fire Fighting and Proximity Fire Fighting [3], heat fluxes of 83 kW/m2 and 8.3 kW/m2 were applied to the outer surface of turnout gear to replicate flashover and hazardous conditions, respectively [4]. These heat fluxes represented the radiant/convective heat sources in fire scenarios. Utilizing 3.0-mm-thick PCM segments with a melting temperature of 60°C, as established in prior research by our team [5], we investigated three different sizes of PCM segments and their corresponding distributions within the turnout gear. These sizes included small (1"-2") segments ranging from 4 to 12 pieces, medium (2"-4") segments with 2 to 6 pieces, and large (4"-6") segments with 1 to 2 pieces distributed in each thermal zone of the human body. Using a larger number of small PCM segments can maintain the same latent heat capacity as the large PCM segments but have more efficient heat absorption.ResultsThe size of PCM segments did not significantly affect the thermal protection time as long as there were enough PCM segments to cover the area. These segments proved effective in reducing temperature increases in areas not directly shielded by PCM segments during periods of intense heat.ConclusionThis computational study has demonstrated that the segment size of PCM has minimal impact on the overall thermal protection efficacy of PCM-integrated firefighters’ turnout gear, provided there is sufficient coverage of PCM pieces within the gear. However, smaller PCM segments are recommended for enhanced flexibility and comfort in firefighters’ turnout gear. The findings from 3D modeling can serve as a foundation for the advancement of next-generation firefighter turnout gear.DisclaimerThe findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the National Institute for Occupational Safety and Health (NIOSH), Centers for Disease Control and Prevention (CDC). Mention of any company or product does not constitute endorsement by the NIOSH, CDC

Susan Xu, Jonisha Pollard, Weihuan Zhao

Conference Proceedings

Analysis of human factors in container ships' marine accidents

Around 80% of the world’s trade is transported by sea, and more than half of it is transported by containers. Container ships are getting bigger and bigger, and their average size has doubled in the last 20 years. Their size has increased from 1st-generation ships that could carry about 1000 Twenty-foot Equivalent Units (TEU) to ships carrying 24000 TEU. However, accidents involving giant container ships can cause catastrophic consequences for world trade and the global economy; such was the case with the grounding of the container ship Ever Given in the Suez Canal in 2021. Therefore, it is imperative to reduce the probability that such accidents will occur by improving the safety of container ships. In addition, according to literature, about 85% of marine accidents are caused by human factors, so to understand accidents’ origin and causes, there is a need to meticulously examine accidents, namely safety accident investigation reports, to classify human and other factors of accidents, such as organizational ones. This process leads to determining the most common factors, enabling suggestions for corrective measures, and implementing proactive ones. The investigation and analysis of marine accidents is a corrective approach where the immediate and root causes of accidents are discovered. Based on the analysis of accident investigation reports, suggestions for the reduction of such unwanted events can be brought to light.In this paper, the marine accident reports involving container ships are analyzed using the Human Factor Analysis and Classification System for Marine Accidents (HFACS-MA) method, aiming to determine the most frequent marine accident causes connected to human factors. Based on the results of the analysis, associated corrective safety measures are proposed.

Nermin Hasanspahić, Vlado Frančić, Marko Strabić, Ivan Krivokapić

Conference Proceedings

Development of a Near-Miss Event Analysis Support System for Different Types of Human Error Using AI Technology

Preventive measures against various human errors are being taken based on information on near-miss events. However, the process from collecting near-miss events to analyzing them and planning countermeasures is labor-intensive. Focusing only on high-risk near-miss events can reduce labor, but many of the collected near-miss events will not be used. To solve these problems, we believe that a "near-miss event analysis support system" consisting of the following tools will be useful.(1st Tool) A tool to support the analysis of near-miss events, especially factor analysis (automatically extracts factors and identifies human error type. Analysts can add or modify.)(2nd Tool) A tool to support risk assessment of near-miss events (calculates the possibility of human error occurring in the target work on a 5-point scale. Analysts input the 5-point scale based on the expected extent of damage when it occurs. These two values are multiplied, and the risk is evaluated on a 5-point scale [1. Take physical measures immediately, 2. Implement on-site response plan immediately, 3. Horizontally deploy to the site and issue a warning, 4. Share information at the site manager level, 5. No response necessary])(3rd Tool) A tool to present countermeasures for near-miss events that are judged to be high risk (automatically presents appropriate human error countermeasure policies and three specific candidate measures based on human error type. Analysts select countermeasures based on the presented countermeasure policies)(4th Tool) Near-miss event occurrence trend analysis tool (Automatically performs statistical analysis of the causes of near-miss events that occurred during a period set by the analyst. Also performs categorization analysis based on the work site, work time period, and SRK level of the work.)(5th Tool) Near-miss event management tool (Connects the near-miss event input tool with the above four tools, stores all data such as evaluation results in the cloud, and supports horizontal deployment within the company. Based on the evaluation results, the urgency is evaluated in four stages (Level 0: no contact required, Level 1: information sharing, Level 2: detailed warning to the site, Level 3: immediate on-site inspection and improvement), and if it is Level 2 or above, a function is added to automatically contact related departments from the system.)We implemented these five tools based on AI technology and built a near-miss event analysis support system. This system is currently being test-operated by safety personnel from several companies, and although we are still in the process of collecting operational issues, it has been confirmed that it has the expected effects.

Joohyun Lee, Yusaku Okada

Conference Proceedings

Human error prevention activities in manufacturing sites based on information from normal work

In factories such as aircraft manufacturing, where the number of productions is small and the defective rate must be reduced to zero, a large number of human error prevention measures are taken. “CRM” in the airline industry is a specific example of ones. However, the burden on workers due to too many measures has exceeded the limit, and there is an urgent need to optimize the management of error prevention measures as a whole. To achieve this, (1)　Detailed collection of human factor information on problematic events such as nonconformity events, (2) Collection of human factor information during normal times of the target work, (3) Structural analysis of human factor, (4) Proposal of guidelines for human error prevention measures based on the analysis results and presentation of multiple specific measures. Of these, (3) and (4) have already been developed in our laboratory and are at the practical stage. Structural analysis methods for human factors include the Swiss cheese model, m-SHELL, PSF list and variation tree. It has been confirmed that (1) can be resolved by measuring human factor management courses for work team leaders through e-learning and factor analysis training incorporating active learning for six months. The realization of safety among business operators has also changed from the traditional "Safety-I" to "Safety-II," and the demand for (2) is increasing, but method (2), which seeks to discover issues when no problems have occurred at all, cannot be addressed with methods such as traditional near-miss event analysis. Therefore, in this study, the image of collected information was changed to "hints that lead to good work" and methods of collecting human factor information from on-site conversations were examined, centering on stimulating constructive communication on-site.

Taisei Kiryu, Chikori Ino, Yusaku Okada

Conference Proceedings

Development of a Support System to Improve the Ability to Analyze Incident Reports in Hospitals Using Generative AI

A major issue in the analysis of in-hospital incidents is the lack of skill and experience of the analyst. When an analyst with little experience analyzes an incident, they tend to only extract superficial characteristics and list only ineffective measures such as minor work improvements and thorough confirmation. To solve this issue, it is essential to educate the analyst. However, the higher the safety of the organization, the less experience employees have with accidents and serious incidents. Compensating for this experience with only regular education and virtual experiences is too laborious and takes a lot of time for the analyst to grow. Therefore, in this study, we examined strategies to enhance the awareness of analysts through the routine analysis of incident reports in medical settings. Specifically, this involves the development of the Medical Risk-Managers' Awareness Enhancement System in Medical Incident Analysis.

Yuriko Imura, Yusaku Okada

Conference Proceedings

Methods of Measuring the Effectiveness of On-site Human Error Response Training Based on Employee Engagement Indicators

One of the important issues in the field of safety management is effective human error prevention education for on-site staff. Currently, many sites not only provide basic human error response training such as confirmation and thorough implementation of basic actions, but also various education methods such as work improvement that takes human factors into consideration, active follow-up with team members, and communication methods that lead to accurate reporting, contact, and consultation. However, the effectiveness of such human error prevention education has only been measured qualitatively.Therefore, this study focused on the engagement of workers and examined a method to multifacetedly evaluate each trainee's attitude toward safety activities before and after the course, including the individual characteristics of the workers (personality such as personality analysis). A questionnaire was designed with work engagement, personal engagement, burnout, employee engagement, psychological safety, personality (Big Five theory), and attributes (job type, position, years of experience) as basic parameters, and a model was created using machine learning to evaluate the following four main factors based on the answers. The four main factors are: (i) loyalty to work, (ii) desire for growth, (iii) desire to contribute to the company, and (iv) sense of happiness (well-being). These indicators were evaluated on a 10-point scale. The effectiveness of the method for measuring the effectiveness of on-site human error prevention training based on the employee engagement index obtained in this study was verified through a survey at several hospitals in Japan. However, there are cases where the effectiveness measurement is unclear, and we are currently continuing to improve the accuracy by expanding the data.

Yu Shibuya, Yusaku Okada

Conference Proceedings

Exploring the Impact of Error Feedback Methods on User Experience in Voice Interaction

Voice interaction has played an important role in various scenarios such as smart homes, cars, and healthcare due to its ease of use, efficiency, and convenience. However, errors in voice interaction can greatly affect the user experience. This paper aims to explore the impact of different error feedback methods on user experience, with the goal of improving the user experience of voice interaction. The study utilizes a combination of subjective and objective approaches by creating an experimental platform to collect facial expression data and emotional valence evaluation data from participants. By analyzing the data, user preferences for different feedback methods can be determined. The findings suggest that in directive task scenarios, users prefer feedback that directly explains the error. In broadcast task scenarios, users prefer feedback that explains the error and provides a commitment to resolve it. In conversational task scenarios, users prefer intelligent voice assistants to take the lead in the conversation, guide its direction, and provide specific event suggestions. This research contributes to a better understanding of the impact of error feedback methods on user experience and provides guidance and reference for the design of future error feedback methods in voice interaction.

Tongtong Xie, Meng Li, Yinyin Bai, Xie Jieren, Zhu Aibin, Zengyao Yang

Conference Proceedings

Investigating Reading Behaviors of Elementary School Students in Oman Using Eye-Tracking: A Study on Familiar and Unfamiliar Arabic Content

This research aims to identify Oman's elementary students' reading behaviours in familiar and unfamiliar Arabic texts through an eye-tracking device. When comparing the results regarding the fixation duration and the number of fixations and saccades of second-, third-, and fourth-grade students watching the two different forms of content, fundamental differences were revealed. Specifically, students in second and third grades read unfamiliar content with longer F1, more F, and S than reading familiar content, indicating that the students invested more cognitive processing time. Therefore, the results presented herein demystify the difficulties young students experience when confronting new content and the need to employ specific intervention approaches in teaching Arabic reading.

Hilal Al-maqbali, Bader Alsinani, Ali Alriyami, Ruqaia Alshezawi, Hala Alfaliti

Conference Proceedings

Human-centric analysis of a pallet loading process: User Journey Map and Design Thinking for needs assessments

Loading pallets in truck bays presents significant human factors challenges, including physical ergonomics, workplace safety, task efficiency, and operator well-being. Forklift operation, in particular, demands both physical and cognitive effort and carries a risk of injury. Work injuries have significant social and economic impacts, both for the injured individuals and for the company. Therefore, analyzing ways to reduce these risks, streamline processes, and enhance efficiency is crucial for both human and organizational well-being. This study focused on analyzing the current operational flow of pallet loading in an industrial facility where this process is integral to production. Using a user journey map, which combined storytelling and material visualization, issues were identified from a human factors perspective issues from the perspective of human factors. The study followed the early stages of the Design Thinking Methodology, particularly in need identification and problem definition. In the initial phase, a multidisciplinary human factors team visited the workstation, employing observation, semi-structured interviews, and on-site recordings. This data was validated through consultations with operators. In the second phase, the user journey was outlined, highlighting six dimensions: user actions, interfaces, goals, experiences, emotions, pain points, and opportunities. After that the user journey map was validated with an industrial team.Through an empathic analysis based on user-centered design, the journey map revealed critical issues such as visibility frustrations and maneuverability challenges. By deeply understanding the operators' experiences, the study provided practical insights and recommendations for improving safety, efficiency, and overall operator well-being.

Isabel Varajão, Rosane Sampaio, Iara Margolis, Emanuel Sousa, Sérgio Monteiro, Luis Louro, Nuno Ribeiro, Rafael Pedro, Estela Bicho

Conference Proceedings

Determining Factors of Adherence to Psychological Therapy in a Chilean University Context: A Multinomial Logistic Analysis

This study explores the determinants influencing adherence to psychological therapy among university students in a Chilean clinical setting. Using a multinomial logistic regression model, we examine the impact of various factors, including sociodemographic characteristics, academic performance, and clinical supervisor attributes on therapy adherence. Key findings indicate that adherence is significantly affected by patient compliance rates, hours in therapy, and the quality of clinical supervision, with a notable gender difference showing higher adherence rates among female patients. The study underscores the importance of patient-provider relationships and highlights the role of personalized support in enhancing adherence to therapy. These results have practical implications for mental health service optimization in educational institutions and contribute to a more comprehensive understanding of the factors that influence therapy adherence in higher education contexts. Future research is recommended to assess the universality of these findings across diverse cultural and educational settings.

Nelson Lay, Eduardo Busto, Hanns De la Fuente-Mella, Luis Felipe Vergara Maldonado, Catalina Ojeda, Macarena Norambuena

Conference Proceedings