Human Interaction & Emerging Technologies (IHIET 2023): Artificial Intelligence & Future Applications

AHFE International

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

Human Interaction & Emerging Technologies (IHIET 2023): Artificial Intelligence & Future Applications

book-cover

Editors: Tareq Ahram, Redha Taiar

Topics: Artificial Intelligence & Computing

Publication Date: 2023

ISBN: 978-1-958651-87-2

DOI: 10.54941/ahfe1004002

Articles

Human Risk-Informed Design Framework (HURID) for integrating human factors in the design of systems and operations

This paper presents the Human Risk-Informed Design framework (HURID). HURID facilitates the integration of human factors into the design of systems and operations, safety assessment, and regulation. The scarcity of human factors data obtained from the investigation of domain accidents/incidents and the lack of effective feedback loops from operations back to designers create challenges to making human risk-informed decisions. HURID aims to fill these gaps by providing a standardised approach for data collection and analysis, supporting operators in making the right design decisions. The framework was developed to be scalable, proportionate to the risks involved, and customisable. HURID consists of five main steps to ensure the inclusion of Human Factors in risk-informed design: 1. Understanding the Design Intent, 2. Analysis of relevant past experience, 3. Application of Human Assurance Tools and Methods, 4. Risk Modelling, and 5. Consolidation of Design Requirements. During these phases, the framework entails the use of tools such as an incident taxonomy - named SHIELD - which allows to systematically identify the Human positive and negative contributions, precursors, organisational aspects; the Human Assurance Toolkit, which includes the state-of-the-art of HF methods and tools in the context of designing/redesigning safety-critical systems or operations; and Risk Models, which are tools that represent the major accident categories and provide information about human actions and influences that affect human performance. HURID is also supported by a web-based tool, the Human Factors Compass, whose purpose is to guide the user in the application of one or more of the HURID components. The Human Factors Compass was the result of a user-centred design process that aimed to identify user requirements and then solve the main pain points for operators that are unsure as to how to integrate human factors in their day-to-day work. The paper presents an aviation case study detailing how the HURID framework supported the design team in the different design phases, to collect human data and derive design decisions.

Barry Kirwan, Roberto Venditti, Simone Pozzi

Conference Proceedings

On the development of an ergonomic approach for the design of an industrial robotic coworker

As industries push for continuous technological innovation to boost their competitiveness, the need to balance techno-economical goals with emerging societal needs is now more pressing than ever. Inspired by the novel paradigm of Industry 5.0, we aim to place human physical and cognitive needs at the center of the production process, introducing proactive and human-aware robots capable of collaboration as co-workers. Although Human-Robot Collaboration (HRC) has successfully permeated different industrial sectors, they still have a relatively limited role as agents that share the human workspace mostly executing pre-programmed actions. Based on this gap a research project is ongoing, including researchers in Ergonomics and Robotics. The current article presents the first stage related to the design of a workstation prototype that emulates industrial tasks and will allow us to explore the different HRC scenarios. The selection of the assembly task was supported by ergonomic assessment (Rapid Upper Limb Assessment), and questionnaires focused on the workers' psychophysical and cognitive overload perceived. Then, the CoppeliaSim simulation software was used to allow us to accurately reproduce both the visual and the physical aspects of the prototype, including the model of a humanoid abstract avatar. In addition, a set of ergonomic and safety requirements were defined to support the human-centered design of the prototype. The results of this research phase will be important for the next steps of our project and for other researchers/industrial practitioners focused on the human-centered design of HRC scenarios.

Ana Colim, André Cardoso, Estela Bicho, Luís Louro, Carla Alves, Pedro Ribeiro, Débora Pereira, Sérgio Monteiro, Nélson Costa, Paula Carneiro, Sacha Mould, João Oliveira, Duarte Fernandes, Pedro Arezes

Conference Proceedings

AI Technology, Holocaust Survivors, and Human Interactions at Holocaust Museums

In this presentation, I will focus primarily on three constituencies: the individuals who developed the strategies for using AI technologies to tell survivors' personal stories; the survivors who were willing to participate in the Dimensions in Testimony (DiT) project to use volumetric capture in order to record the narrative of their (and their extended family's) experience of the Shoah, and the audience members who visit with the interactive DiT survivor recordings.Currently in use at over a dozen museums worldwide, pre-recorded interviews with individual Holocaust survivors incorporate specialized display technology and natural language processing in order to generate interactive conversations between survivors and visitors. The video recordings are prepared to answer well over 1,000 possible questions visitors might ask of them. In addition, a limited number of these AI recordings also are available to visitors to the Dimensions in Testimony (DiT) website.Members of the public who “visit with” individual survivor AIs are able to interact with eyewitnesses to history to learn from those who actually were there. Given that, these conversations are directed by the visitors to specific Holocaust museums and/or the DiT website themselves, visitors participate in a highly-personalized, inquiry-based educational interaction.For the past five years, I have studied both the responses of survivors who participated in this effort and I have engaged in observational study of individuals interacting with the DiT recordings both in a museum setting (asking questions of Renée Firestone at the Holocaust Museum Los Angeles [HMLA]) and students interacting with the DiT recordings available through the USC Shoah Foundation website (in particular, how students interact with the interactive DiT recording of Pinchas Gutter).In order to evaluate how this particular technology has been “accepted,” I will address the following points of inquiry:1.How might engaging in interactions that feel like self-directed interviews encourage greater empathy and/or compassion on the part of interlocutors? Or, conversely, is it possible that “users” will try to “game” the recordings by asking questions the recording cannot answer?2.What were the ground rules for capturing the testimony of the survivors?3.How do survivors themselves feel about participating in this innovative technology/project? 4.What do we learn about ourselves as a result of engaging in these interactions with the DiT recordings?5.How might these interactions redefine Holocaust education?

Cayo Gamber

Conference Proceedings

Software Usability for Different Age Groups

The writers of software are the people who have sound knowledge about all the technicalities that take place behind the scene. But these people are not the sole users of the software. In this modern era of scientific evolution, the usage of software in day-to-day life is inevitable. Scientists have been working for ages to make human lives better and the creation of smart software has boosted this advancement to a great extent. The majority of the world population has access to some sort of software that they use irrespective of their age and gender. However, the real question is, as the rate of software usage is increasing rapidly, is there any effort being made to simplify the way users should interact with software? In this paper, we propose a guideline for developing age-neutral software interfaces. For the sake of limiting the scope of this study, we will only consider software systems that we use in our personal devices such as desktops, laptops, tablets, cell phones, notepads, and kindles, etc.

Naila Bushra

Conference Proceedings

Post-Pandemic Impact Analysis for airport processes from security to boarding – How to respond to the next pandemic

The COVID-19 pandemic globally affected the complete transport sector and especially passenger air transport with nosediving traffic numbers, wide-ranging travel restrictions and long-lasting uncertainties (see IATA, 2020). As air travel starts to recover cautiously from severe losses of traffic volumes over the pre-pandemic year 2019 and travel restrictions are relaxing, air transport providers have to ensure that passengers as well as people working within the air transport sector will remain safe and be prepared for the next Pandemic. For Example, arboviruses have the potential to spark the next epidemic, warns the World Health Organisation (WHO) and it might only be a question of time when the next pandemic will rise. Airports need to prepare to cope with the next pandemic efficiently and effectively. For this purpose, we develop a toolbox to analyse and evaluate operational measures along the process chain of travelling at an airport.This paper examines the contamination risks at airports covering the travel process from security checks to aircraft seat. In our study we examine the possibility of an infection by dint of simulation with the Pandemic Simulation Model (Pandemic SiM). For this purpose, we advanced an earlier version of Pandemic SiM that only covered the security check area by adding typical boarding processes of a medium sized European airport. The model is based on a real European airport serving around 12 million passengers per year (in 2019). The simulation model incorporates a new algorithm calculating the probability of spreading a virus (like COVID-19) via droplet, airborne or contact transmission during different airport travel processes along the travel chain. The algorithm considers different infection situations and incidence values and allows for a quantification of infection risks per individual simulated passenger. Based on the output of the simulations of the process chain in combination with that algorithm we can show the effectiveness of measures like social distancing and their consequences to minimize contamination risks along travel processes at airports. The paper describes the modelling, the algorithm to calculate contamination risks, as well as results and findings of the simulation runs. It will show how contamination risks, capacity, waiting times and waiting space are affected. This will provide airport operators with decision support for challenges arising from the need to be prepared for the next pandemic.

Martin Jung, Axel B. Classen, Florian Rudolph

Conference Proceedings

Human-centric decision for the Integrated Planning of Smart Port Systems

While the context of Industry and Logistics 4.0 is mainly related to smart systems and automation, new efforts are being applied to develop human-centric super-smart system, under the name of Industry 5.0. One example of a logistics system in this context can be seen in port terminals, which are migrating from traditional modern ports to Smart Ports. In this context, a series of questions arise related to the intrinsic human factors influencing the performance of smart systems. Thus, the main objective of this research is to develop a conceptual framework of human-centric decision for the integrated logistics operation and maintenance planning in smart port systems. A systematic literature review is adopted to build the scientific pillars for the conceptual framework. Afterwhile, under the Industry 5.0 context, we developed a human-centric decision framework connected with smart technologies to acquire real-time data and integrate logistics operations. As conclusion, we identified that the interaction of humans with recommendations from smart systems are not explored properly, and, so, the constructed framework presented an approach demonstrating that human decision can be influenced by intrinsic factors and affect the interaction between humans and intelligent systems.

Maurício Randolfo Flores Da Silva, Enzo Morosini Frazzon, Guilherme Luz Tortorella, Julia Cristina Bremen, Bruna Rigon De Oliveira

Conference Proceedings

Design and Evaluation of A Wearable Adaptable Setup System for Occupational Exoskeletons

Background: Industrial activities depend upon tasks involving manual material handling; these expose workers to considerable risk of injuries causing low back pain and musculoskeletal disorders. A potential solution for this problem presents the use of wearable robots known as exoskeletons. Their purpose is to improve ergonomics and reduce the load on the lumbar spine. Exoskeletons can be classified in two categories according to the actuation type: (i) passive, and (ii) active. Active exoskeletons are based on the principles of man-machine interaction and equipped with drive, sensor and control systems. Such devices require system adaptation in diverse scenarios to produce the proper assistive modulation forces for the user. A novel solution is allowing the user access capabilities to certain areas of the exoskeleton controller. The user command interface is a wearable adaptable setup system device for occupational exoskeletons. This device commands the interactions between the user and the exoskeleton to achieve easy adjustments in the system.Purpose: In this paper we present the design and evaluation of a human-machine interface called the User Command Interface, a wearable device to access the different domains of the exoskeleton control system. The interface is an electro-mechanical device attached to the exoskeleton. Its design is divided into two software layers, a hardware architecture and the mechanical interface. The main objective is to control who has access to the exoskeleton and how some domains could be modified without affecting the safety of the user and performance of the exoskeleton. There are twenty actions you can perform using the device, seven of them directly affect the exoskeleton's operation. Some examples of the actions you can do are: (i) accessing the exoskeleton system using fingerprint recognition, (ii) calibration (iii) parameters modification, (iv) monitoring the exoskeleton's signals, and (v) displaying instructions as safety rules or tutorials. Our group is focused in the design and development of upper/lower-limbs active occupational exoskeletons such as XoTrunk and Shoulder-sideWINDER.Methods: To assess the interface we performed functionality, experience, and usability tests. We divided the experiment according to the type of interactions (interface-only and interface-exoskeleton interaction) between the user, the interface, and the exoskeletons. The interface-only interaction evaluates the navigation intuitiveness of the graphical layer and the functionality of user data-base management. On the other hand, the interface-exoskeleton interaction assesses the rapid parameter configuration during lifting tasks related to real scenarios.Results: In total 52 test subjects participated in the study. The evaluation was most frequently conducted using controlled tasks. The study results are divided in: (I) subjective results (user pain points and system usability scale), and (ii) completion time for activities. The evidence shows that the assessment of the interface is a dynamic process. There are statistically significant effects in terms of usability and the completion time of the tasks.Conclusions: The interface allows simple access to the exoskeleton's adjustments and user database management. After evaluation, the device presents a solution for occupational exoskeleton design matters when the user requires parameter modifications during task performance.

Olmo Alonso Moreno Franco, Daegeun Park, Christian Di Natali, Luigi Monica, Francesco Draicchio, Darwin Caldwell, Jesus Ortiz

Conference Proceedings

User Centered Design of a Digital Platform for Therapeutic Education and Respiratory Rehabilitation in Patients with Post-COVID-19

The World Health Organization (WHO) reports that the coronavirus disease 2019 (COVID-19) has been identified in over 617 million people. Most people who develop COVID-19 fully recover, but approximately 10%-20% of people experience a variety of mid and long-term effects after they recover from their initial illness. These mid and long-term effects are collectively known as post-COVID-19 conditions.COVID-19 sequelae may vary from mild in terms of fatigue and body aches to severe forms requiring long-term oxygen therapy and lung transplantation due to lung fibrosis leading to significant impairment in quality of health.Post-COVID-19 functional impairment can limit the ability of the individual to perform activities of daily living. Information and communication technologies (ICTs) could be an excellent strategy to target those individuals' physical and functional recovery and social reintegration through pulmonary rehabilitation. Telerehabilitation is a branch of telemedicine in which ICTs are used to provide remote rehabilitation activities directly. The goal of this study is to present the design, through a User-centered design approach, of a Telerehabilitation platform that includes therapeutic education exercises for the respiratory rehabilitation of people who have suffered from COVID-19 or any other respiratory disease. The research team designed a digital platform that includes therapeutic education exercises for the respiratory rehabilitation of people who have suffered from COVID-19 or any other respiratory disease. The result is an accessible digital platform that provides therapeutic education to users according to their age through remote respiratory self-rehabilitation sessions.User-centered design (UCD) is an iterative design process in which designers focus on the users and their needs in each phase of the design process. In the construction of our proposal we used an iterative design process in which designers and users are actively involved in artifacts. Our approach called iPlus, is a methodology for designing software with an educational purpose. The iPlus design approach is flexible and offers a design approach integrated with other agile methods. The design process begins by defining the problem according to its specific needs and defining the expected learning outcomes. iPlus offers a phase for the ascertainment of consensual requirements through the participation of experts and users. iPlus gives the participants options for active and creative involvement; it proposes a participatory approach in which designers and users focus on the user's requirements in each phase of the educational software design process.Finally, the methodology and the resulting platform will improve people's quality of life.

Marco Santórum, Mayra Carrion Toro, David Morales Martinez, Patricia Acosta Vargas, Verónica Maldonado-garcés, Gloria Acosta-vargas, Manuel Ayala-chauvin, Esteban Ortiz-prado, Mario González-rodríguez

Conference Proceedings

Towards Smart Building: Visualization of Indoor CO2 Concentration. Adapting Modern Computational Tools for Informing Design Building Decisions

Carbon dioxide (CO2) is part of the indoor air. According to the American Environmental Agency (EPA), one of the world's worst polluted places are indoor spaces where we spend more than 90% of our time (U.S.EPA, 1989). It has been shown that excessive CO2 indoor concentration can cause different health problems, including allergies, lung cancer, induced asthma, and respiratory infections like Covid-19 virus. Health problems often occur in poorly ventilated space that allows CO2 to increase beyond acceptable levels due to inefficient air circulation. To better understand the dynamics of this condition requires a fine grain model of how CO2 builds up and moves through space. In our study we developed a CO2 sensor network to record CO2 data and to visualize CO2 spread through a typical classroom to monitor air quality and to inform engineering and design building decisions to eliminate health risks. The CO2 sensor network is deployed inside 16 equally divided parts of the classroom. Each part is equipped with one sensor node for CO2 concentration monitoring. Collected data is visualized using modern computational tools and AI data-driven techniques. The results show that the increase in the quantity of classroom occupants as well as the time which they spend indoors directly impacts the level of CO2. Higher occupancy in the room triggers a higher value of CO2 concentration. Sensors in close proximity to people have higher CO2 readings. One of the data visualization charts shows readings from sensors installed in the different sections of the classroom. It visualizes approximately 5000 seconds of the readings done every second and shows the minimum and maximum indoor CO2 value. Another visualization is a three-dimensional model that spatially represents different CO2 concentrations in the equally divided parts of the classroom. Additionally, the airflow circulation analysis conducted in the classroom sheds light on how to adjust ventilation rates, to change the ventilation setup, or to adjust the building geometry. Personalized knowledge-based recommendation systems can be built to monitor indoor air quality inside the various classrooms at the university.

Anna Gelich, Jefferson Ellinger

Conference Proceedings

The impact of automation frameworks on today's data science competencies

The digital transformation has led to a rapid advancement of today's working environment. The increasing demand for AI solutions, especially in skilled professions, is deepening the relationships between humans and smart machines. These new relationships require an evolution and transformation of the skills of today's workforce. Furthermore, technologies can be used to close potential skills gaps and thus make the interaction and collaboration between human and technology work in the best conceivable way. Among the many digital competences required in today's working environment, data scientific competencies like data-preprocessing, feature-engineering and Model-generation are essential in order to cope and analyze small-to-big data sets arising in various data spaces. These Data Science competencies combine statistics, computer science and expert knowledge to gain insights from data and to develop a data-driven solution. With the amount of data increasing every day, there is a growing demand for subject matter experts with Data Science skills to help companies to be competitive by making data-based decisions, identify future trends, identify patterns, optimize processes, or develop new products and services. The competencies needed to accomplish these tasks are as multidisciplinary as the field of Data Science itself. Starting with the ability to write in multiple programming languages, to apply mathematical and statistical concepts, to practice machine learning algorithms and techniques, to the ability to understand industry-specific requirements, to critically question and visualize their results, to the ability to work in a team and to interact socially. These various requirements are met by employees, each of whom is not capable of handling such a wide range of competencies. Since the combination of these competencies is in high demand on the job market, but the small number of high talented employees cannot meet this demand, intelligent solutions are being sought that can replace some of these competencies. The goal of this paper is therefore to investigate whether AI-based automation frameworks have Data Science competencies in their design. It serves as an impulse for further discourse on whether AI-based automation frameworks can empower humans in acquiring Data Science competencies. For this purpose, a total of four automation frameworks out of 17 were selected in an initial analysis, which were most indicative of the following characteristics: automation, flexibility, ease of use and interoperability. These are AutoPrep, Auto Gluon, AutoClust and DeepEye. Based on the EDISON Data Science Framework, these research papers were coded by means of a qualitative content analysis and the obtained data were subsequently analyzed and discussed. Initial results show that by using automation frameworks, needed skills for applying Data Science competencies can be made available to companies and workers in the short term. This concerns components from the EDISON competence groups Data Management, Data Analysis, Data Modeling and Communication.

Maria Potanin, Maike Holtkemper, Christian Beecks

Conference Proceedings

Conceptual modeling for Human Systems Integration in Manned-Unmanned Teaming

Future systems are becoming increasingly complex as autonomous systems work closely with human operators. Transdisciplinary development is needed to create systems functioning in dynamic Manned-Unmanned Teaming (MUM-T) operations. This paper demonstrates the use of conceptual modeling during Human Systems Integration in the early phase of MUM-T development. We used case study research in a company with participatory action research. This paper highlights three suitable conceptual modeling approaches that provide insight into human factors and manpower distribution in the context of manned and unmanned systems in a search and rescue operation. These models include storytelling, visual ConOps, and dynamic workflow models. Through visual support, these models facilitate engaging stakeholder discussions, enhance contextual understanding, and allow for easy modifications during co-creation. They are particularly useful in preparing for workshops and eliciting knowledge from end-user meetings.

Tommy Langen, Gerrit Muller, Kristin Falk

Conference Proceedings

Sensing Intra-clothing Climate to Increase Comfort According to time, place, and occasion

Humans wear comfortable clothing depending on time, place, and occasion (TPO) to improve their quality of life. The wearing comfort of clothes varies with the microclimate formed between the skin and the clothes, referred to as the intra-clothing climate. Though comfort is related to the intra-clothing climate, comfort can be sacrificed to some extent, depending on the TPO.This study refers to unbearable discomfort as UD. Clothing giving UD differs depending on the TPO. In addition, the temperature and humidity inside the clothes affect the probability people feel UD. The study aims to find the relationship of the probability of UD with the temperature and humidity inside the clothes for each TPO to recommend clothes that prevent UD from occurring according to the TPO.The study assumes that the probability density of comfort at a specific TPO follows a two-dimensional Gaussian distribution of the temperature and humidity inside the clothes. It means not the temperature and humidity inside the clothes around the mean of the Gaussian distribution but those at the foot of the distribution are assumed to cause UD. The paper proposes a method to verify the assumption through a temperature and humidity sensor in the clothing. A temperature/humidity sensor in a small mesh case is attached between the clothes and the skin with a strap around the neck, to obtain temperature/humidity data. In addition, the comfort at each TPO is obtained by questionnaire in the range of "0 (uncomfortable)" to "4 (comfortable)". The distribution of comfort for the climate inside clothes from the sensor data is compared with questionnaire results.Experiments with 3 male subjects in their 20s during the 2-week experiment period have been conducted to observe the climate inside clothes in real life. The observed data are examined to extract the relationship with comfort for each TPO. The experiment has shown that the degree of comfort changes like a mountain on the two-dimensional plane of the temperature and humidity inside the clothing for a specific TPO of the subject. It also demonstrates that the degree of unbearable comfort increases at its foot. The data with the highest comfort level for each TPO of each subject are extracted to be applied for the GMM, to obtain a mixed normal distribution representing the area with the highest comfort level. The result accounts for the degree of unbearable comfort increasing at the tail of each Gaussian model. These results can be used for clothing recommendation considering comfort for each TPO based on the temperature and humidity sensed inside the clothing.

Takayuki Hiwatari, Fumiko Harada, Hiromitsu Shimakawa

Conference Proceedings

Attention Training Products for Preschool Children using AHP-TOPSIS

This study aimed to explore the design elements and their corresponding weights for attention training products for preschool children to enhance their effectiveness. A mixed-methods approach was used to investigate factors related to attention training in preschool children. An evaluation matrix for the design elements of attention training products was constructed for preschool children using an Analytic Hierarchy Process, and a weight analysis was conducted. The Technique for Order Preference by Similarity to Ideal Solution was then utilized to obtain positive and negative ideal solutions for the three attention training product designs, and the best design was selected based on their relative closeness. The results revealed that genetic factors (C13), health level (C14), and family upbringing (C34) were important design elements for attention training products for preschool children. Among the three tested designs, the clip-on-ball toy was found to be the best solution. These findings provide valuable insights for the optimized design of attention training products for preschool children and practical application in the product development cycle's design and selection stages.

Tingmin Yan, Zihe Chen

Conference Proceedings

Universal Design in Public Housing: Enhancing the Quality of Life of Older People with Mild Cognitive Impairment Living Alone

The population of Hong Kong is ageing and is expected to gradually increase, and thus an increase in single older people with mild cognitive impairment is expected. This may progress to dementia overtime. By 2064, a third of Hong Kong's total population is expected to be aged 65 or above, which will put extreme pressure on long-term health services and increase social care costs. Studies of mild cognitive impairment (MCI) and dementia have mainly been conducted in the west, and evidence-based research addressing the genuine needs of patients with MCI in their daily activities is limited. The home is the central focus of many people's lives, and the elderly will spend most of time in it.The specific objectives of the study are first, to briefly review and explore the common strengths and limitations of public housing in Hong Kong and selected cities; second, to identify the deficiencies of current public housing in terms of universal design and broaden the scope of this approach; third, to develop a model of the relationships among coping strategies for enhancing quality of life, unmet needs and the feeling and concerns of people with MCI living alone.The present ethnographic study is aimed at revealing some of the contemporary concerns about human culture and social interaction. A triangulation study approach is taken, beginning with participatory design workshop followed by participant observations with five residents living alone with MCI, and an in-depth interview with a centre manager who assisted in this study and is a carer for those with dementia.This study suggests that universal design principles are not sufficiently applied in the development of public housing for single elderly people living with MCI. To address this deficit in interior, home furniture and product designs, the concept of a visible reminder has been suggested, which includes multisensory and psychological considerations. Design practitioners should fully utilise this conceptual model when developing universal design furniture for the general public, without stigmatising those with disabilities such as MCI. The coping strategies for improving the quality of life these older people are identified as continued home care and family support, an awareness of universal design principles, social networks and engagement and revisiting public health policies. Governments should take the lead in helping to improve the quality of life of people with MCI through healthcare, social engagement, caring and universal design.

Alex Pui-yuk King, Kin Wai Michael Siu

Conference Proceedings

Product Design to Effectively Alleviate Emotional Exhaustion Caused by Long Hours of Digital Interactive Work

With the rapid development of the Internet, more and more people must use electronic devices such as computers to do their work digitally and interactively. We have observed that employees who work with computers for long periods of time may be resistant to electronic devices. In previous studies, the specific sources of this resistance and the factors influencing it have not been clearly identified. The purpose of this article is to study the emotional exhaustion caused by prolonged digital interactive office work, analyze the antecedent space leading to this emotional exhaustion, reveal the psychological mechanism of the fatigue process, and further explore product design research that effectively alleviates the emotional exhaustion caused by computer office work in the Internet era.Methods: The design investigates the non-experimental, cross-sectional correlation. We administered an online questionnaire to participants. Participants had to be people who use computer offices for long periods. The questionnaire contained questions related to emotional states (depression, anxiety, etc.) and certain concomitant behavioral manifestations (overexertion, avoidance, excessive rest, etc.). At the same time, the intensity of the participants' perceived fatigue was statistically assessed with the help of the Fatigue Scale. In the data analysis, we adjusted for individual characteristics, work nature, and work environment in order to explore the antecedent space of emotional exhaustion.Conclusion: The analysis of the data obtained from the questionnaire showed that there was a positive correlation between the time users spent working on computers and emotional exhaustion. Most participants had emotional exhaustion accompanied by physical fatigue. In addition, in the subgroup analysis, we found that emotional exhaustion caused by long hours of computer work was influenced by factors such as work environment atmosphere and complexity of work content. This study helps us to find the direction of product design research to alleviate emotional exhaustion. Employees who work with computers for long hours need adequate rest time and. If necessary, a certain degree of psychological intervention. Based on the above results, the research and design are closely integrated with the psychological and physiological needs of the computer office group. The design principles for products to alleviate emotional exhaustion are summarized in order to design products that can improve the quality of life of people who use digital interactive work for long periods. At the same time, the relevant product design can somehow guide people's behavioral activities and work styles in specific scenarios, meet the needs and services of the business, explore its potential market advantages, and better enhance the quality of people's office environment in the future.

Ziyan Dong, Li Xu

Conference Proceedings

3D Prototype of an Interactive Adding Machine to Improve Basic Numerical Skills

3D printing in industries like medicine and education has led to major improvements in designing, developing, and printing useful models, including body prostheses and educational toys. The 3D printer's commercialization has risen thanks to more manufacturers, models, and reasonably priced equipment. As a result, prototypes and gadget creation have merged cutting-edge design techniques like gamification and electronic components, allowing accessibility and interactive and enjoyable devices. This paper describes the design, production, implementation, operation, codification, and printing of a 3D prototype of an interactive adding machine to improve basic numerical skills and help children and others with cognitive disabilities learn easier or lessen distractions. The prototype and all the necessary documentation are available for anyone to replicate. The paper also discusses difficulties encountered during the design process and proposes future improvements for the next version.

Boris Astudillo, Jonathan González, Julio Mora, Cristian Bastidas, Erick Vera

Conference Proceedings

Designing 3D-Printed Smart-Sole Shoes for the Elderly: Examining Appearance Acceptance in Hong Kong

The continuously evolving technology has driven researchers' investigation into integrating 3-Dimensional (3D) printing and smart functions into footwear. Comfortability has been identified as a crucial factor in creating shoe soles. Thus, numerous studies have been conducted to focus on the development of comfortable and functional footwear. Recent research has indicated that a prototype should be adapted in designing footwear to meet the expectations of older people, taking into consideration factors such as aesthetics and comfort. Of particular concern, the appearance of footwear is the top consideration for older women. Notably, their preferences revolve around the combination of shoe colours, fabric materials, patterns, shapes, heel height, and functional design features.This research aims to investigate the footwear appearance preferences of elderly individuals in Hong Kong, laying the foundation for designing and developing comfortable 3D-printed midsole smart sole shoes. A total of 50 healthy male and female subjects aged 50 and over will be recruited to complete a shoe aesthetics survey. The survey, consisting of 50 questions, will delve into the participants' subjective evaluations of shoe design aesthetics and the willingness to adopt the prototype. It will be divided into five parts, which will analyze the design of shoe faces, including colour, materials, fastening mechanism, heel height, and shoe styles for the elderly in the fashion market.The research will reveal the footwear appearance preferences of elderly individuals in Hong Kong, highlighting their design requirements. The survey results will aid in designing and developing comfortable 3D-printed midsole smart sole shoes for older people. Through the participants' expressions of design requirements on shoe aesthetics, further development in footwear design will be required to meet the needs of elderly individuals in terms of aesthetics and comfort. This study emphasizes the critical consideration of shoe aesthetics as a significant parameter in footwear design for older people.This research seeks to investigate the footwear appearance preferences of elderly individuals in Hong Kong to develop comfortable 3D-printed midsole smart sole shoes. By analyzing the participants' design requirements on shoe aesthetics, the findings will aid footwear manufacturers in developing shoes that meet the design preferences of elderly individuals, thereby improving their comfort and style. This study highlights the significance of considering shoe aesthetics as a crucial parameter in footwear design for the elderly population. Ultimately, the successful development of comfortable and stylish shoes can promote increased mobility and enhance the quality of life for this demographic group.

Ling Cheung, Roger K.P. NG, Simon Chow, Jim Luk, Rainbow Lee

Conference Proceedings

Human-centred design: Promoting interactions between children and caregivers in play spaces

Most of the time children are necessary to go to play spaces with caregivers. However, play spaces in general are designed for children that caregivers are always excluded. Sometimes only basic resting facilities are provided for the caregivers. In the recent years, some studies have already concerned the inclusiveness of public play spaces for the needs of children and their peers with different motion, sensory and cognitive capabilities. On the other hand, there is still very rare to have research on the inclusiveness of the design of public play spaces for caregivers. Taking Hong Kong as a case study, this paper reviews and explores the meanings of public play spaces and identify direct and possible indirect users. The study also explores the current social issues, in particular the family and household-member factors, related to the design of public play spaces, in a densely populated city. The paper then identifies the needs and preferences of different direct and indirect users of public play spaces, addresses the commonly overlooked needs of caregivers in the design of public play spaces, and uncovers the design gaps which, if addressed, could significantly enhance the inclusivity and relevance of public play spaces amidst evolving social contexts.

Kin Wai Michael Siu, Izzy Yi Jian

Conference Proceedings

CLIP-Based Search Engine for Retrieval of Label-Free Images Using a Text Query

In January 2021, OpenAI released the Contrastive Language-Image Pre-Training (CLIP) model, able to learn SOTA image representations from scratch on a dataset of 400 million (image, text) pairs collected from the Internet. This model enables researchers to use natural language to reference learned visual concepts (or describe new ones), enabling the zero-shot transfer of the model to downstream tasks. One of the possible applications of CLIP is to look up images using natural language queries. This application is especially important in the context of the constantly growing amount of visual information created by people. This paper explores the application of the CLIP model to the image search problem. It proposes a practical and scalable implementation of the image search featuring the cache layer powered by SQLite 3 relational database management system (RDBMS) to enable performant repetitive image searches. The method allows efficient image retrieval using a text query when searching large image datasets. The method achieves 32.27% top-1 accuracy on the ImageNet-1k 1.28 million images train set and 55.15% top-1 accuracy on the CIFAR-100 10 thousand images test set. When applying the method, the image indexing time scales linearly with the number of images, and the image search time increases minorly. Indexing 50,000 images on Apple M1 Max CPU takes 19 minutes and 24 seconds while indexing 1,281,167 images on the same CPU takes 8 hours, 31 minutes, and 26 seconds. The query through 50,000 images on Apple M1 Max CPU executes in 4 seconds, while the same query through 1,281,167 images on the same CPU executes in 11 seconds.

Yurij Mikhalevich

Conference Proceedings

Assessing Engagement of the Elderly in Active Listening from Body Movement

This study propose s a method for estimating the conversational state in active listening using voice and body movement data to facilitate for participants to exchange their words. In recent years, the problem of apathy among the elderly has run into a serious problem as the population ages. Active listening, a type of counseling technique, is useful to address the problem. In active listening, to activate the elderly person, a listener should do nothing other than listen to what the elderly person talks. However, it is difficult for the elderly person to willingly talk because they are not familiar enough with each other to make conversation in a frank mode. In the study, the body movement of the elderly person is recorded as well as the voice of both participants. Hidden Markov models , to which those data are fed, estimate the latent conversational state during active listening. A random forest models are constructed to examine the importance of each variables fed to the hidden Markov model.To test the usefulness of the proposed method, a one-on-one listening experiment is conducted between a listener and a speaker. The difference in the body movement derives two personas, for each of which hidden states are estimated. The body movement data with a small variance estimates three explicit states of the listener's speech, the speaker's speech, and silence, as well as two implicit states of the speaker's thinking and the speaker's laughter. On the other hand, the persona of large body movement variation indicates the same three explicit states, as well as the implicit state of the speaker's giving responses and an uninterpretable state. The result above indicates that it is possible to estimate almost all of the conversational states. Labeling manually some of the voice data, random forest models are constructed to know the importance of the variables. It turns out the mean of the body movements has the highest importance for the body movement with a small variance, while the maximum value of the voice per interval has the highest importance for that with a large variance.An initial prediction using only voice data presents the accuracy of 0.61 and 0.59 for body movement with small variance and for that with large variance, respectively. On the contrary, the prediction using body movement greatly improves the accuracy to 0.96 and 0.99 for body movement with small variance and large variance, respectively. This suggests that body movement is useful for estimating the conversational state.The method for state estimation enables us to automate the labeling of conversational states that previously had to be done manually.Furthermore, the method to find hidden conversational states the analyst has not assumed can provide a stepping stone to facilitating listening. The uninterpretable state may come up because of the shortage of information to be fed to the model.The need for biometric data other than body movements and video data during listening is indicated to interpret the uninterpretable state.

Yuji Tanabe, Hiromitsu Shimakawa

Conference Proceedings

Machines and cities. An evolving relationship in the age of artificial intelligence

This contribution aims to investigate contemporary conceptualizations of the relationship between city and digital technology, in order to identify useful indications for contemporary cities. Starting from an examination of the most conceptually significant approaches, we aim to shed new light on challenges and opportunities connected with the contemporary urban conditions and particularly with the implementation of Urban Artificial Intelligences (UAI). The issue of UAIs will be investigated through a hybrid approach that connects philosophy of technology and urban planning. An approach that is able to connect the ethical implications of the use of AI in urban contexts and its design consequences. The main objective of the paper is to analyze two of the first and most interesting reflections on the connection between digital technology and urban space (Tòmas Maldonado and W.J. Mitchell) to understand how they can be useful for future planning challenges. One of the first systematizations of this issue stressed the tension between a Platonic interpretation of cyberspace, conceived as an escape from reality, and an infrastructural perspective that regards the physical and digital space as deeply connected (Maldonado 1992, 1997). Maldonado's reflection is useful in exploring the dialectic between an immaterial conception of digital space and its interpretation in an infrastructural sense. This ambivalence was also present in the context of urban planning theory (Mitchell 1996), in which digital space is sometimes conceived as a parallel dimension, sometimes as a dimension inherently embedded into the physical one. In Mitchell's urban planning thought and practice, this ambivalence gives rise to decisive differences in the design of hybrid objects and spaces This historical analysis will be useful in understanding how the concepts of materiality and immateriality also come into play in contemporary discourse on AI Urbanism by defining its planning trajectories, modes of human-machine-environment relationship, and guiding its investments (Barnes 2021, Cugurullo 2021, Batty 2018). Urban Artificial intelligences have the potential to re-shape ontologically and epistemologically (Floridi 2022 Benanti 2018, Carpo 2017) our cities, influencing physical space and the way in which cities are represented. The analysis of these two frameworks will result in a better understanding of the concept of urban space in the age of UAI. The interaction between various forms of agency (human, natural, artificial) in the urban context will be a decisive design theme in the coming years. The geometry of this interaction will also be defined by the ability we have to think concretely and appropriately about digital space, making use also of the insights that can be drawn from the recent history of the relationship between the city and digital technology

Otello Palmini, Marco Negri, Gabriele Lelli

Conference Proceedings

Lip-Reading Research Based on ShuffleNet and Attention-GRU

Human-computer interaction has seen a paradigm shift from textual or display-based control towards more intuitive control such as voice, gesture and mimicry. Particularly, speech recognition has attracted a lot of attention because it is the most prominent mode of communication. However, performance of speech recognition systems varies significantly according to sources of background noise, types of talkers and listener's hearing ability. Therefore, lip recognition technology which detects spoken words by tracking speaker's lip movements comes into being. It provides an alternative way for scenes with high background noise and people with hearing impaired problems. Also, lip reading technology has widespread application in public safety analysis, animation lip synthesis, identity authentication and other fields. Traditionally, most work in lipreading was based on hand-engineered features, that were usually modeled by HMM-based pipeline. Recently, deep learning methods are deployed either for extracting 'deep' features or for building end-to-end architectures. In this paper, we propose a neural network architecture combining convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) with a plug-in attention mechanism. The model consists of five parts: (1). Input: We use Dlib library for detecting 68 landmarks of the face, crop the lip area and extract 29 consecutive frames from the video sequence. The frames go through a simple C3D network for generic feature extraction. (2). CNN: with neural networks becoming deeper and deeper, computation complexity increases significantly as well, which motivated the appearance of the lightweight model architecture design. Then a lightweight CNN named ShuffleNet pre-trained on ImageNet dataset is used in our method to perform spatial downsampling of a single image. The ShuffleNet mainly uses two new operations, namely, pointwise group convolution and channel shuffle, which greatly reduce the computational cost without affecting recognition accuracy. (3) CBAM: In the field of image processing, a feature map contains a variety of important information. The traditional convolutional neural network performs convolution in the same way on all channels but importance of information varies greatly depending on different channels. To improve the performance of convolutional neural networks for feature extraction, we utilize an attention mechanism named Convolutional Block Attention Module (CBAM), which is a simple and effective attention module for feedforward convolutional neural networks and contains two independent sub-modules, namely, Channel Attention Module (CAM) and Spatial Attention Module (SAM), which perform Channel and Spatial Attention respectively. (4) RNN: The traditional Recurrent Neural Network (RNN) is mainly used to process sequential data, but with the extension of the RNN network, it may be unable to connect to all related information which may cause key information loss. It cannot solve the long-distance dependence problem and the performance may drop significantly. Due to this shortcoming of the traditional RNN network, we select the GRU network in this paper, which is a variant of the LSTM. It has a simpler structure and better performance than the LSTM neural network. (5) Outputs: Lastly, we pass the result of the backend to SoftMax for classifying the final word. In our experiment, we compare several model architectures and find that our model achieves a comparable accuracy to the current state-of-the-art model at a lower computational cost.

Yixian Fu, YUANYAO LU

Conference Proceedings

Simulating and Quantifying Inequality in Strategic Agent Networks

Transactions are an important aspect of human social life, and represent dynamic flow of information, intangible values, such as trust, as well as monetary and social capital. Although much research has been conducted on the nature of transactions in fields ranging from the social sciences to game theory, the systemic effects of different types of strategic agents transacting in real-world social networks (often following a scale-free distribution) are not fully understood. An influential economic measure that has not received adequate attention in the complex networks and game theory communities, is the Gini Coefficient, which is widely used to quantify and understand wealth inequality. In this paper, we define a network model called a strategic agent network (SAN) and present a methodological framework based on game theory for investigating questions of inequality using SANs. We briefly comment on results obtained from a preliminary experimental investigation using a real-world dataset based on Bitcoin.

Mayank Kejriwal

Conference Proceedings

Optimizing Rate of Penetration in Drilling Operations with Metaheuristic Algorithm

The rate of penetration (ROP) in drilling operations is a critical factor that can significantly affect the overall cost of drilling activities. Achieving an optimum ROP is crucial in reducing non-productive time and increasing drilling efficiency. In this study, we proposed a novel approach to predict ROP using a hybrid method Extreme Learning Machine and Grey Wolf Optimization algorithm (ELM-GWO). We use the Grey Wolf Optimization (GWO) algorithm for optimizing the weights and biases between input and hidden layers of ELM and updating the predictive model at each formation to reduce the dimension of input data and mitigate the impact of non-real-time data, such as formation properties, on the bit speed prediction. The model has been trained and tested using data collected from an Algerian field. The results of the statistical and graphical evaluation criteria showed that the ELM-GWO model exhibited higher accuracy and generalization performance compared to the ELM-PSO (Particle Swarm Optimization) and ELM-WOA (Whale Optimization Algorithm) models.

Abdelhamid Kenioua, Omar Djebili

Conference Proceedings

Digital Primer Implementation of Human-Machine Peer Learning for Reading Acquisition: Introducing Curriculum 2

The aim of the digital primer project is cognitive enrichment and fostering of acquisition of basic literacy and numeracy of 5 – 10 year old children. Here, we focus on Primer's ability to accurately process child speech which is fundamental to the acquisition of reading component of the Primer. We first note that automatic speech recognition (ASR) and speech-to-text of child speech is a challenging task even for large-scale, cloud-based ASR systems. Given that the Primer is an embedded AI artefact which aims to perform all computations on edge devices like RaspberryPi or Nvidia Jetson, the task is even more challenging and special tricks and hacks need to be implemented to execute all necessary inferences in quasi-real-time. One such trick explored in this article is transformation of a generic ASR problem into much more constrained multiclass-classification problem by means of task-specific language models / scorers. Another one relates to adoption of "human machine peer learning" (HMPL) strategy whereby the DeepSpeech model behind the ASR system is supposed to gradually adapt its parameters to particular characteristics of the child using it. In this article, we describe first, syllable-oriented exercise by means of which the Primer aimed to assist one 5-year-old pre-schooler in increase of her reading competence. The pupil went through sequence of exercises composed of evaluation and learning tasks. Consistently with previous HMPL study, we observe increase of both child's reading skill as well as of machine's ability to accurately process child's speech.

Daniel Hromada, Hyungjoong Kim

Conference Proceedings

Unraveling Scenario-Based Behavior of a Self-Learning Function with User Interaction

In recent years, the field of Artificial Intelligence (AI) and Machine Learning (ML) has witnessed remarkable advancements, revolutionizing various industries and domains. The proliferation of data availability, computational power, and algorithmic innovations has propelled the development of highly sophisticated AI models, particularly in the realm of Deep Learning (DL). These DL models have demonstrated unprecedented levels of accuracy and performance across a wide range of tasks, including image recognition, natural language processing, and complex decision-making. However, amidst these impressive achievements, a critical challenge has emerged - the lack of interpretability.Highly accurate AI models, including DL models, are often referred to as black boxes because their internal workings and decision-making processes are not readily understandable to humans. While these models excel in generating accurate predictions or classifications, they do not provide clear explanations for their reasoning, leaving users and stakeholders in the dark about how and why specific decisions are made. This lack of interpretability raises concerns and limits the trust that humans can place in these models, particularly in safety-critical or high-stakes applications where accountability, transparency, and understanding are paramount.To address the challenge of interpretability, Explainable AI (xAI) has emerged as a multidisciplinary field that aims to bridge the gap in understanding between machines and humans. xAI encompasses a collection of methods and techniques designed to shed light on the decision-making processes of AI models, making their outputs more transparent, interpretable, and comprehensible to human users.The main objective of this paper is to enhance the explainability of AI-based systems that involve user interaction by employing various xAI methods. The proposed approach revolves around a comprehensive ML workflow, beginning with the utilization of real-world data to train a machine learning model that learns the behavior of a simulated driver. The training process encompasses a diverse range of real-world driving scenarios, ensuring that the model captures the intricacies and nuances of different driving situations. This training data serves as the foundation for the subsequent phases of the workflow, where the model's predictive performance is evaluated.Following the training and testing phases, the predictions generated by the ML model are subjected to explanation using different xAI methods, such as LIME (Local Interpretable Model-Agnostic Explanations) and SHAP (SHapley Additive exPlanations). These xAI methods operate at both the global and local levels, providing distinct perspectives on the model's decision-making process. Global explanations offer insights into the overall behavior of the ML model, enabling a broader understanding of the patterns, relationships, and features that the model deems significant across different instances. These global explanations contribute to a deeper comprehension of the decision-making process employed by the model, allowing users to gain insights into the underlying factors driving its predictions.In contrast, local explanations offer detailed insights into specific instances or predictions made by the model. By analyzing these local explanations, users can better understand why the model made a particular prediction in a given case. This granular analysis facilitates the identification of potential weaknesses, biases, or areas for improvement in the model's performance. By pinpointing the specific features or factors that contribute to the model's decision in individual instances, local explanations offer valuable insights for refining the model and enhancing its accuracy and reliability.In conclusion, the lack of explainability in AI models, particularly in the realm of DL, presents a significant challenge that hinders trust and understanding between machines and humans. Explainable AI (xAI) has emerged as a vital field of research and practice, aiming to address this challenge by providing methods and techniques to enhance the interpretability and transparency of AI models. This paper focuses on enhancing the explainability of AI-based systems involving user interaction by employing various xAI methods. The proposed ML workflow, coupled with global and local explanations, offers valuable insights into the decision-making processes of the model. By unraveling the scenario-based behavior of a self-learning function with user interaction, this paper aims to contribute to the understanding and interpretability of AI-based systems. The insights gained from this research can pave the way for enhanced user trust, improved model performance, and further advancements in the field of explainable AI.

Marco Stang, Marc Schindewolf, Eric Sax

Conference Proceedings

Instinctive Intelligence: Our Next AI

Today, our world changes drastically. Yesterday, changes were smooth, so we could differentiate and predict the future. Today, they are sharp. So,we cannot predict the future. And our world was closed with boudnary yesterday, but todayour world becomes open. Thus, yesterday, we could control. Today, datasets become not only complex, but complicated. And materials are getting soft with the progress of material engineering. When things were hard, we could understand what it is and how we should handle it with our eyes alone. But today, we need to interact with them directly. To cope with such drastically changing real world, we need to coordinate all parts of our body. Thus “coordination” is increasing its imortance. Brain is getting wide attention. But most of these studies focus on digital processing. But drastically changing real world needs not only digital processing, but analog procesing, too. Take medical diagnosis for example. Doctors observe blood flow using MRI. Blood is analog. And even after brain death, heart circulates blood around body. And while blood is circulating, we can transplant body parts. In AI, heart is rarely talked about. But heart is deeply associated with emotion. Our need is material-centric at early stage, but with time it shifts to mental and finally to “self-actualization”. We want to demonstrate how capable we are as “self”. Humans can think about the future. Animals live for now. But humans live for tomorrow. This contributed greatly to the development of humans. Many species became extinct because they were not diversified enough. We should realize the big role of instinct. In material-based world, objective and quantitative evalution was important. But to satisfy our emotional expectations, we need to evaluate things subjectively and qualitatively. We need to make decisions what actions we should take by trial and error. AI has been regarded as a man-made tool, and nature has nothing to do with it. But this is a big mistake. Humans are part of nature. The etymology of artifical is related with art. It is associated with “creation”. But who creates? It is us, human and human is part of nature. Babies learn to scrall and walk by themselves. They learn using their instinct alone. So, if we can make the most of our instinct, we can create experience and adapt to the drastically changing world. And “emotion” and “motivation” come from the same Latin word “movere”, i.e. movement. We perceive the environment and situation and we became situationally aware and motivated. And we make decisions what actions to take. If it satisfies our emotional expectation, then it is fine. It not, we repeate the process until we are satisfied. Thus, AI in the next step will be Instinctive Intelligence.

Shuichi Fukuda

Conference Proceedings

Exploring the Potential of ChatGPT in Enhancing User Experience (UX) Writing

Artificial Intelligence (AI) has revolutionized various industries, including the field of User Experience (UX) writing. This paper aims to investigate the role of ChatGPT, an AI language model, in aiding UX writing and to assess the impact of ChatGPT on the quality and effectiveness of UX writing. A mixed-method approach was used to collect and analyze data from various sources, including academic articles, online resources, and case studies. Qualitative analysis was used to identify the challenges and opportunities in UX writing and to understand the experiences and perspectives of UX writers who have used ChatGPT. The findings suggest that the use of ChatGPT can help overcome some of the challenges in UX writing, including the need for speed and efficiency, the need for consistency in tone and style, and the need for personalized content for different users. ChatGPT can also assist in generating ideas for content and in improving the overall quality of the content. Quantitative analysis was used to measure the impact of ChatGPT on the quality and effectiveness of UX writing. The results suggest that the use of ChatGPT can significantly improve the speed and efficiency of UX writing tasks, such as creating microcopy, error messages, and user prompts. ChatGPT can also help in generating more personalized and engaging content that resonates with the target audience. Overall, the findings suggest that ChatGPT has great potential to aid in UX writing in the modern world. ChatGPT can help overcome some of the challenges in UX writing and enable UX writers to create more engaging and effective content for users. However, there are still some limitations and challenges that need to be addressed, including ethical considerations, data privacy, and the need for human oversight and interpretation. In conclusion, this paper provides insights into the role of ChatGPT in aiding UX writing and highlights the potential benefits and limitations of this technology. The findings can inform future research and development in this field and can help organizations and individuals in making informed decisions about the use of AI in UX writing.

Amanda Lentez, Gabriela Mager

Conference Proceedings

The learning curve and benefit of artificial intelligence for the built environment

Artificial intelligence (AI) technology has the power to unlock the challenges faced in construction projects such as poor efficiency issues, design errors, and accidents on-site. Therefore, this paper is aimed to evaluate the benefit of implementing AI on South African construction projects. The quantitative approach was adopted for this study. Well-structured questionnaire surveys were disseminated to built environment stakeholders such as quantity surveyors, project managers, construction project managers, contractors and architects. A total of 260 questionnaire surveys were distributed and 223 were received back with an 86% response rate. The findings revealed the learning curve benefit of AI is improved quality of work post-construction, reduces budget overruns, saves time, overcomes shortages of experienced labors, improves performance on construction work, improves the health and safety of the construction projects, elicits faster information exchange, improves productivity, reduces construction risks such as on-site accidents, reduces construction errors, improves customer relations, improves profitability and saves cost. However, the study has indicated that the implementation of AI technology in the built Environment in South Africa is still at an early development stage. The study would hopefully contribute to the body of existing knowledge of AI technology. In Addition, it could assist construction industry professionals to advance their workplaces and organizations.

Xolile Mashwama, Siyabulela Dywili, Gift Phaladi, Clinton Aigbavboa

Conference Proceedings

Investigating Public IP Address Assignment in Infrastructureless Social Networks

An Internet Protocol (IP) address is a logical address that is used by the router to identify a device on a network. An IP version 4 (IPv4) address is composed of 32 bits that are split into 4 octets of 8 bits each. Each IPv4 address is encoded using decimal notation giving the address the appearance of being composed of 4 integers. As such IPv4 addresses range from 0.0.0.0 to 255.255.255.255 with 232 or 4294967296 possible addresses. An IP version 6 (IPv6) address is composed of 128 bits that are split into 8 octets of 16 bits each. Each IPv6 address is encoded using hexadecimal notation giving the address the appearance of being composed of 32 alphanumeric characters. As such IPv6 addresses range from 0000:0000:0000:0000:0000:0000:0000:0000 to FFFF:FFFF:FFFF:FFFF:FFFF:FFFF: FFFF:FFFF with 2128 or 340282366920938463463374607431768211456 possible addresses. Infrastructureless Networks are distributed networks where no sense of infrastructure is present in the network. As such, no central server or administrative device is present and each device operates as a client and a server. When such infrastructureless networks are used for sharing news and social interactions, it is defined as an Infrastructureless Social Network. Hence given the finite set of public IP addresses available to devices on Infrastructureless Social Networks and the dynamic nature of Infrastructureless Social Networks, there is a need to conserve public IP addresses on such networks. Therefore, this work proposes the Law of Conservation of IP Addresses and uses Infrastructureless Social Networks as a test base. The proposed Law of Conservation of IP Addresses states that a public IP address cannot be created nor destroyed but rather redistributed by a DHCP Server from one end device to another. Based upon this proposed law, Infrastructureless Social Networks are used as the testing ground for testing the proposed law. In Infrastructureless Social Networks, one approach by which public IP addresses are normally assigned is based upon some form of grouping or clustering. In the group, the group leader is used as the administrator of the group and is normally charged with distributing the IP addresses to members of the group. The public IP addresses are assigned based upon those that are available on the network and hence are not created as the Law of Conservation of IP Addresses proposed above. When each device leaves the network, the device releases the public IP address back to the network and it is once again available for use by a device. Hence the public IP address is not destroyed. If the group leader leaves the network, the members of the group appoint a new group leader and the public IP address is updated accordingly. Even though there is no central device, each end device acts as a DHCP server and distributes addresses as they join and leave the network. Hence the Infrastructureless Social Networks have proven to be an excellent testbed for the Law of Conservation of IP Addresses. As such the conclusion is that the Law of Conservation of IP addresses aptly describes how public IP addresses are assigned and have proven its applicability to the world of Infrastructureless Social Networks.

Amit Ramkissoon

Conference Proceedings

Automatic Text-to-sound Generation by Doc2Vec

Nowadays, the market size for games and video viewing services has been expanding. The demand for sound effects to produce content using these services is also rising. However, sound-effect production often requires expensive software or hardware, exceptional equipment use, and experience. Therefore, this study aims to reduce the cost of sound effects production and enable the output of sound effects as imagined. It examines a method for automatically generating sound effects based on text input using Doc2Vec. The Natural Language Processing Model (NLP) calculates the similarity between the input text and the labels in the dataset. The Natural Language Processing Model (NLP) is created by Doc2Vec pre-loading sound-related language expressions (labels). The model is pre-trained using labels from VGG-Sound data. The calculated highly similar sounds are downloaded from VGG-Sound, a specified number of sound datasets. The data downloaded from highly similar data is synthesized in similarity order, and the audio is output.Furthermore, we verify the correlation between the sentences used in the proposed method and the generated sound effects. We conducted an experiment in which we presented the generated sounds and the sentences used to create them and had the participants rate them on a 5-point scale. The sentences used for a generation are those that live in the dataset, those that lived in a small number in the data set, those that did not exist in the data collection, those to which information such as location or scene has been added, and those that contain multiple events. The results show that the more speech in the dataset, the higher the rating and that sentences with added information or numerous events produce lower ratings.

Kakeru Iwamoto, Hironori Uchida, Yujie Li, Yoshihisa Nakatoh

Conference Proceedings

Investigation of Weaknesses in Typically Anomaly Detection Methods for Software Development

Software systems are rapidly increasing and diversifying due to technological innovations such as IoT, artificial intelligence, and blockchain. Accordingly, automatic analysis of software logs has recently attracted particular attention as a research area to ensure system reliability. Currently, in the research domain, anomaly detection in text logs using CNN, LSTM, and Transformer-based DNN models has shown high accuracy of over 90%. However, contrary to these excellent results, there are reports that it has not been used in the field of the software development field. We predict that the reason for this lies in the way the models are evaluated and, in the datasets, so we investigate using a representative anomaly detection model and the common dataset BGL. First, we investigate the effect of the splitting ratio of the dataset. As a result, we confirm that the accuracy decreases as the number of unknown anomaly logs increases. As a result, we identify features that are over-learned in all supervised learning models. In addition, we validate the generality of the model with the validation datasets and learning curves. The results show signs of overfitting in both supervised and unsupervised learning models. These results suggest that the composition of the dataset used affects the accuracy of the log-text anomaly detection model. Therefore, we plan to create a dataset with multiple anomaly patterns based on the logs used in the software development domain and create a model that can detect anomalies with the created dataset.

Hironori Uchida, Keitaro Tominaga, Hideki Itai, Yujie Li, Yoshihisa Nakatoh

Conference Proceedings

Are SMEs Ready for AI Embedded Mobile Robots?

The introduction of both mobile robots (MR) and AI-embedded mobile robots (AIMR) into the industry is very slow compared to other types of industrial robots (IR) and automation systems. Many scientific articles and studies are focused on the programming and design of MR. At the same time, integration issues, topical problems and related obstacles are almost entirely absent from the scientific literature. The authors of this paper acknowledge that the complete analysis of this area is a very challenging task. Therefore, for the purposes of this study, we focus on the local problem of analysing the introduction of MR and AIMR in small and medium-sized enterprises (SMEs). The authors offer the analysis of the current challenges and trends in the introduction of mobile robots into SMEs. They also propose solutions to these problems based on their own as well as external experience in the design, programming and implementation of mobile robots.

Vadym Bilous, Kirill Sarachuk

Conference Proceedings

Buddy4All – A mixed reality-based solution for enabling intergenerational interaction

With increasing age of society, the number of seniors living alone is steadily rising. This often leads to a feeling of loneliness or a decline in mental health and physical fitness. Seniors often feel overwhelmed by today's technology and speed of life and do not feel needed anymore partly due to lack of contact to the younger generation. On the other side, young adults – especially from lower social class – often lack positive role models and have problems establishing trustful relationships with adults. Buddy4All addresses these challenges by connecting the younger and older generation via an innovative technology-driven buddy platform. The solution combines classical smartphone-based interactions via the Buddy4All social app and Mixed Reality (MR) experiences via the novel and lightweight Nreal MR glasses. The social app provides multimodal cross-generational communication, experience exchange, and support content. The mixed reality solution connects the younger and older generation via fun cross-generational activities such as location-based games and cognitive exercises. These activities keep both generations mentally stimulated and physically active. The Buddy4All solution fosters the wellbeing and active lifestyle of both generations as well as the cross-generational interaction between these generations and thus, the understanding for each other.

Elisabeth Broneder, Christoph Weiß, Valentin Miu, Monika Puck, Stephanie Puck, Sabine Wolf, Miroslav Sili

Conference Proceedings

Virtual try-on of Additively Manufactured Orthosis via Augmented Reality

Virtual try-on applications came to market not too long ago to be a supportive part of online shopping, allowing consumers to try clothes or accessories on before making the purchase. This kind of applications proved to be highly useful in decreasing return rates of the products. More and more online markets are using AR technology to improve the shopping experience of consumers in fashion field. However, AR technology should be able to do more than making products more attractive, especially in the medical field. Finding an orthosis product that both satisfies the medical requirement and has an appealing design has always been hard for patients with physical inconvenience, especially during corona time. Traditionally, consumers first need to make a mould in a physical orthosis store, then they have to make multiple trips to the store to keep giving suggestions to the staff of how the orthosis needs to be adjusted, until they are satisfied with the final product. This process takes a long time, since orthosis are usually hand-made, and the adjustment process could be frustrating for the orthosis consumers. To go to the physical store, orthosis consumers have to tolerate the time spent on the way, limited choices of design to try on in each store, and the risk of corona infection due to close contact with people over there. The producers also have to cover for the wear-out samples, the time it takes for multiple discussion on improvements, as well as taking the risk of the patients not liking the design after production. A virtual orthosis try-on application is the best solution to satisfy both sides, it bridges the gap between orthosis consumers and the producers. This application would make individualization of orthosis products easier, saving the time of communications and possible miscommunications. Moreover, this app make the digitalized production line to be more appealing and trustworthy to orthosis consumers. The orthosis model is automatically generated with the 3D scan of the consumers' leg, then the consumers use this application to try on different designs and colours, and the final product can be additive manufactured after they made their choice. In this way, consumers do not need to go to the physical store anymore, saving much time and effort. The try-on application was first designed and assigned functions that it is supposed to achieve using design thinking methods, then designed and build with game engine Unity, which has many ready-to-use packages, together with the tracking technology from the Vuforia engine. Both Marker-less and Marker-based tracking were tried out during the development. Marker-based tracking were chosen in the end for a more satisfying end-product. Finally, a preference test was made for a better version of this application with a controlled group.A marker-based Android application was successfully made after many trails. Consumers only need to place two QR codes on both sides of their thighs, then they can view the augmented orthosis from different angles on the camera of a personal Android device, choose the design patterns and colours of the orthosis model by simple clicks on the user interface, and select the model that attracts them the most.

Gustavo Menezes De Souza Melo, Chenyan Feng, Stefan Reich, Johannes Henrich Schleifenbaum

Conference Proceedings

User performance analysis in guided and non-guided stressful virtual reality scenarios

Virtual reality (VR) is a potentially useful technology for training and simulating hazardous scenarios. It is particularly useful for firefighters, healthcare staff or the military, which face emergency situations that involve high levels of stress. Studies have shown that the participant's stress level is increased when confronted with a hazardous scenario in a virtual environment, as would be expected in a realistic simulation. This research describes a methodology based on measuring interactions and objectives in hazardous scenarios, and an empirical study for assessing the participant's performance improvement. A prototype virtual reality experience in which the participants face a radiation emergency has been developed and a pilot study has been run. The methodology, a qualitative and a quantitative analysis with preliminary but promising results are described.

Alejandro Villar, Carlos León

Conference Proceedings

Framework for Defining the Perspectives of the 3D Driving Visualization Interface for Driving Automation System-Engaged Vehicles

3D driving visualization is a crucial component of in-car Human-Machine Interface (HMI), as it effectively conveys the behavior and intention of driving automation system-engaged vehicles. However, the performance of 3D interface information transmission is significantly affected by perspectives. This paper presents a perspective definition framework based on overall cockpit interaction. It discusses the factors that affect 3D perspective definition in driving scenarios and how they impact it.

Jun Li, Xuejiao Sun, Hejin Gu, Xingyao Su, Jifang Wang

Conference Proceedings

Can small and medium enterprises benefit from AR technology? Current challenges and trends

Albeit augmented reality (AR) technologies first have been discovered in the third quarter of the 20th century, their widespread use began just two decades ago. Existing paper trails show that AR has a wide range of industrial application: it simplifies human-machine communication, improves human-machine interfaces (HMI) for quick information exchange in training (including feedback to study the workflow), correction of errors, machine maintenance, assembly assistance etc. However, broader industrial acceptance of AR, prior to all by small and medium-sized enterprises (SMEs), recently faced considerable problems and the expansion of AR solutions does not match the high potential it has demonstrated. That results in a limited practical use, mainly for demonstration and advertising purposes. This short review is to present the state of the art of the industry, challenges that SMEs face in adopting AR technologies, and several practical examples of a (commercial) adoption of AR. Some prospects for further development of AR and its ongoing integration into industry are briefly discussed in the summary.

Vadym Bilous, Kirill Sarachuk

Conference Proceedings

Imersive Virtual Reality during work out with movable sports equipment: the effect on oculomotor, disorientation, and nausea before and after training

The combination of immersive virtual reality and sport has garnered significant attention in the academic world and the industry domains. There is a decent amount of literature that shows positive effects but also critical voices when it comes to learning and wellbeing in a virtual world during work out. In our study we postulate the hypothesis that subjects with a higher degree of predisposition in simulation sickness will show higher values in all three subscales of the simulation sickness questionnaire (SSQ) while doing exercise with sports gear with moveable parts in a fully immersive VR application than subjects with lower degrees of predisposition in motion sickness. However, our data did not support the hypothesis. Surprisingly, we even found a disproportionate significant improvement in the oculomotor subscale of the SSQ. These results are being discussed and further studies are being suggested.

Oliver Christ, Michelle Deuber, Anina Gächter, Jordin Guedel, Andreas Papageorgiou

Conference Proceedings

Designing for the investigation of microclimate stressors and physiological and neurological responses from the perspective of maker culture

The 2021 United Nations Climate Change Conference (COP26) resulted in the Glasgow Climate Pact. Initial work in the study reported in this paper investigated relationships between environment and physiological measurements using smartwatches, and self-designed bespoke environmental modules which are wearable around the waist. Data from this initial phase was analysed with a Random Forest regression model. The next phase of this project involves neurophysiological measurement, specifically electroencephalography (EEG). EEG was introduced to the model to explore how the changes in environmental or biometric measurements correlate with changes in neurophysiological measurements. In this latter phase, EEG data is viewed as an independent data type that is distinct from environmental and other physiological data. The headset model used to record EEG data is again a bespoke hand-made design, comprising a combination of biosensing board and electrodes from OpenBCI and widely available items like adhesive tapes and staples. A subsequent step involved validation of this DIY EEG headset data against research grade equipment, of which the analysis of different features of EEG data have shown to be of statistically comparable trends. For data collection, all data recorded is stored in Google Drive; Python is used to synchronize, pre-process data and train regression models. The first headset prototype was assembled in mid-October 2021, and was tested and developed in early November. From mid-November to late January 2022, the authors wore the devices for one to two hours per day to collect data. For EEG data, eight channels were recorded, basic filters (bandpass and notch) and REST re-referencing are applied. In this project, EEG time-series are used as input in regression models with other data types as output. Two regression models were trained then compared, the first being convolutional neural network with pre-built architecture and the other being a Random Forest model with features extracted from EEG time-series. Inferences are made from the models using open-source interpreters, with an eventual aim to infer how one's local environment might impact one's emotions and health. The results suggest that sound level, carbon dioxide concentration, and dust concentration feature more importantly in the regression models trained on collected datasets. These factors were continually associated with high feature importance scores in the EEG data signal and in both the objective scores recorded from the electronic instruments and the more subjective self-report forms. Furthermore, it was found that visual stimulus and problem processing, in terms of information, touch, and spatial relationships, are the most influential factors affecting the participants' physiological well-being in this research. Most recently, one aspect that is currently being investigated is electrodermal activity (EDA). EDA is marker of sympathetic network activity (Zangróniz et al., 2017). As such, it is an indication of human stress and emotion arousal, (Rahma et al., 2022). It is hoped that analyses of EDA data will further strengthen the emerging model describing the intersections between local microclimate and physiological and neurological stress. Early validation experiments comparing DIY EDA devices against research-grade Empactica E4 sets have shown promising results.

Minh.Tuan Nguyễn-Thiên, Minh.Anh Nguyễn-Đức, Kenneth Y.T. Lim

Conference Proceedings

Industrial HMI design principles for highly automated manufacturing processes

The number of industrial robotic installations in Asia, Europe and the Americas is continuously growing every year, and a forecast from the International Federation of Robotics (IFR) shows that these values will increase more in the future. Process automation level measured by operational industrial robots relative to the number of factory employees is getting higher in the multiple industries of mass and serial production. With the expansion of robotic-based solutions and automation tools for manufacturing processes, the industrial HMI (human-machine interface) integration to operations management becomes vital for end users to operate efficiently on the daily basics. As a result, each equipment vendor and software solution provider supplies custom HMI screens, which makes the lack of a homogeneous user experience one of the main issues for rapidly growing Industry 4.0 applications. Intuitive interfaces and well-designed human-machine interaction improve visibility to robotics cell operators, prevent them from unexpected errors and allow maintenance engineers to recover from faults and resolve issues quickly in case of line stoppages. Usually, such interfaces support the factory commissioning phase, and after a successful launch and go-live decision, the integration team handovers commissioned system to the operations team after training with personnel and the hypercare period. As an Industry standard, the main problems that Industrial HMI solves are factory operations use cases and essential manufacturing business processes: production management and process control, process and equipment configuration, equipment monitoring and diagnostics, reactive and predictive maintenance management, historical reporting and analytics, health and safety. To be able to design, develop and release to production user interfaces for specific manufacturing and assembly processes, we provide the HMI product design framework and design principles for configurable scalable factory interfaces. Using such an industrial HMI framework, the development team can rapidly prototype and build custom-tailored applications from existing tested and validated components and keep a holistic user experience across multiple sites. Flexible product architecture for HMI applications allows automation integration businesses to deliver to the end user robust UI solutions with a high level of accessibility to control robotic cells and lines supporting specific process implementations in different production environments. The central proposal of this paper is the design framework and design principles for configurable industrial HMI based on the product strategy that allows the creation of customised interfaces on demand. The principle methodologies of the design system presented in the paper have been validated and tested through multiple research studies and continuous product improvements in the production environment. Several HMI solutions have been integrated into automotive production, composite materials manufacturing, high-voltage modules production and battery assembly, transportation and warehouses with autonomous mobile robots. The research and automation community can use described approaches to design better human-computer interaction for their HMI solution and dramatically improve the user experience of using them.

Matvei Bryksin, Nikita Vysotsky, Pavel Guseynov

Conference Proceedings

The Effect of An AI Model for Conceptual Similarity on Design Ideation in a Co-creative Design System

This paper describes a co-creative system that enhances design creativity in the initial idea generation process. The Collaborative Ideation Partner (CIP) is a co-creative design system that selects and presents inspirational images based on their conceptual similarity to the design task while the designer is sketching. In this paper, we present a study of how the different types of similarity of the contribution of the AI partner influences design ideation in a co-creative system. We conducted an experiment with a control condition in which the images are selected randomly from a curated database for inspiration and a treatment condition in which conceptual similarity is the basis for selecting the next inspiring image. Our results show that the AI model of conceptual similarity used in the treatment condition has a significant effect on the novelty, variety, and quantity of ideas during human design ideation.

Jingoog Kim, Mary Lou Maher

Conference Proceedings

Utilising state of the art eye tracking equipment to improve outcomes for maritime watchkeeper's on nocturnal navigational watches

The International Regulations for Preventing Collisions at Sea (IRPCS) require a ship's Officer of the Watch (OOW) to maintain a proper lookout at all times. This includes looking out of the window as well as monitoring information via Multi-Function Displays (MFDs) that are found on the modern-day ship's bridge. These displays lead the OOW to spend time interrogating their various menus and functions to seek required information, thus distracting them from their primary task of maintaining a lookout. This paper identifies the function of the human eye in performing the lookout function during the hours of darkness. State of the art Eye Tracking Devices (ETDs) are utilised to collect eye movement data in both real-world and simulator-based ship bridges, and this is used to identify the impact that MFDs have at night in reducing the eye's effectiveness in the watchkeeping task. A novel scanning pattern is presented that can be adopted by OOWs to make the best use of the eye's physiology, improving lookout effectiveness at night and reducing the distraction caused by MFDs. This paper aims to assist OOWs in making better use of their eyes, enabling them to maintain optimum lookout performance during the hours of darkness.

Abdul Khalique

Conference Proceedings

Human-computer Interaction Evaluation Method for Nuclear Power Plant Control Room Based on Operator Physiological Characteristics

In the design optimization process of the control room in a nuclear power plant, personnel workload is an important evaluation indicator. A well-designed control room can effectively reduce the workload of operators during their work processes, improve work outcomes and efficiency, and reduce the possibility of accidents caused by human errors. Currently, subjective evaluation methods are mainly used to evaluate personnel workload in related research. These methods are simple and easy to implement with short evaluation times, but they are highly subjective and difficult to perform a comprehensive and objective quantitative evaluation. Physiological measurement method is a research approach that observes and measures the physiological data changes related to behavior in order to analyze the state of individuals, providing more objective and reliable quantitative results. With the advancement of sensor and computer technology, it has become a hot research topic. Among them, physiological characteristics such as electroencephalography (EEG) and eye movement are widely studied, and their relationship with the psychological and mental states of individuals have been fully medically validated. This paper proposes a method for evaluating the workload of nuclear power plant control room operators by collecting EEG and eye movement physiological signals and analyzing their features using advanced machine learning algorithms. It also explores evaluation methods for control room design achievements.

Chenxiang Jiang, Shiguang Deng

Conference Proceedings

User Experience of a web-based platform that enables ethical assessment of Artificial Intelligence in the Public Sector

As public sector organizations increasingly adopt Artificial Intelligence (AI) technologies, it is important to ensure that they are used in a responsible and ethical manner. The use of AI systems can have unintended consequences, such as exacerbating existing inequalities or infringing on individuals' privacy rights. Therefore, the use of a web-based platform that enables the ethical assessment of AI helps to identify potential risks and ethical concerns before these technologies are deployed and used by public administrations. This paper presents a web-based platform implemented to support the ethical assessment of AI use in Public Sector, along with its evaluation. The web-based platform implemented for this purpose is designed to address ethical, legal, and social vulnerabilities, allowing Public Sector stakeholders to adopt AI applications in a trustworthy, controlled, and responsible manner. This platform is designed to offer easy transparency of latent risks and the corresponding mitigation measures. The evaluation of this platform was conducted by four public administrations from three different European countries (Italy, Greece and Norway), while the feedback was collected through questionnaires and interviews. The findings of this study can be taken into consideration by developers and research community for the development and adoption of AI applications in public administrations.

Maria Tsourma, Noemi Luna Carmeno, Jaime Alessandro Codagnone, Sara Mancini, Jesper Krognos, Anastasios Drosou, Dimitrios Tzovaras

Conference Proceedings

Determining the user experience and continuance use of a mobile application and an online portal

The increasing number of users with access to the internet, computers, and mobile devices propels most institutions to avail their services through online portals and mobile applications. However, there are instances where users underutilise or completely opt out of these platforms. This is a cause for concern since funds are invested in their development, with the anticipated return on investment. Against this backdrop, this study aimed to compare the user experience and continuance use of a mobile application and online portal for an organization in South Africa. This single case study followed an explanatory sequential design, where the initial phase consisted of data collection using a self-administered questionnaire. For the second phase, the data was collected using an interview protocol. The results established that the study participants had a positive experience with the online portal but not so much with the mobile application. The contributing factors to the online portal's positive user experience were its efficiency, attractiveness, perspicuity, dependability, novelty, and stimulation. The interview results corroborated the quantitative results, as participants indicated overall positive experiences with the online portal. In contrast, participants had negative experiences with the mobile application, citing its limited features and lack of user-friendliness, understandability, and learnability. Regarding continuance use, the quantitative and qualitative results suggested that participants were keen to use the online portal in the future. However, the quantitative results for the mobile application indicated no participant interest in using the mobile application again in future, despite the interview results indicating otherwise. Participants identified improvement in efficiency and visual appeal as conditions for their future re-use of the mobile application.

Thobani Mhlongo, Lizette De Wet, Silas Verkijika

Conference Proceedings

Investigating Consumers' Demand for Electric Scooter Usage Based on User-Product Interaction

Scooters have traditionally been the most popular mode of transportation for the majority of the Taiwanese population who rely on two-wheelers. However, due to concerns about environmental sustainability and air pollution reduction, the Taiwanese government has been actively promoting electric two-wheelers (E2Ws). For example, to improve the charging convenience of E2Ws, the Taiwanese government initiated the infrastructure for charging pillars in 1995 and innovative battery swapping system services in 2010. It wasn't until the emergence of Gogoro, a company that introduced lightweight and aesthetically appealing electric scooters (e-scooters) and over 2,200 battery swapping stations in 2016, that E2Ws became competitive in the scooter market. These developments have contributed to promoting the adoption of E2Ws as a more sustainable and environmentally friendly alternative to gasoline-powered scooters. However, despite these efforts, scooters still dominate the two-wheeler vehicle market, accounting for over 90% of sales in 2022, while E2Ws, including e-scooters, electric bicycles (e-bikes), and Pedal Electric Cycle (Pedelec), account for only 2%.The development of E2Ws has primarily concentrated on addressing consumer issues through technical solutions, leading to industry growth. However, convincing consumers to switch from mature products and services like gasoline-powered scooters and gas stations to emerging E2Ws like e-scooters and battery swapping stations without considering their actual needs presents a significant challenge. Therefore, emerging products and services must be designed with a user-centered approach to fulfill their requirements, offer innovative solutions, and enhance competitiveness in the market. This study aims to investigate why consumers prefer to purchase scooters over e-scooters. The study will use a subjective questionnaire survey to gather qualitative and quantitative feedback from respondents with experience riding E2W vehicles. The survey data will be analyzed to better understand consumers' preferences and needs for two-wheeler transportation. The study's results are expected to provide valuable information for policymakers and stakeholders in the transportation industry, as well as manufacturers of e-scooters, who can use the information to improve their products and services to meet the needs and preferences of consumers.Ultimately, this study aims to promote the adoption of e-scooters as a more sustainable and environmentally friendly alternative to gasoline-powered scooters. The findings of this study will help identify the key factors that influence consumers' choices and will provide recommendations for improving e-scooter products or related services to meet consumer demands, not only in Taiwan but also in other countries facing similar transportation challenges. By doing so, this study will contribute to the development of more sustainable and efficient transportation systems globally.

Fei-Hui Huang

Conference Proceedings

Telerehabilitation Platforms in times of COVID-19: Usability Evaluation

Following the pandemic caused by the SARS-CoV-2 virus, telerehabilitation (TR) has become a tool for safely providing health services. TR has positioned itself as an innovative health strategy that seeks to improve access to healthcare by applying advances in information and communication technologies (ICT). The rise of TR, an emerging field of telehealth, brings new challenges, mainly related to supporting physiatrists in planning, monitoring, and evaluating rehabilitation.Currently, it is common for patients who have shown improved health following hospitalization caused by the SARS-CoV-2 virus to be sent home. However, many of these patients may experience consequences of prolonged hospitalization and isolation, such as physical symptoms (fatigue, weakness), cognitive difficulties (delirium), and emotional complications (depression).The research conducted by some authors has demonstrated the effectiveness of TR for physical and mental health problems, improving patients' quality of life by overcoming obstacles such as distance to the institution providing care, strain associated with face-to-face rehabilitation appointments on family members, and lack of homecare for rehabilitation.Using software within TR programs supports professionals in constructing a rehabilitation program and serves as a source of learning and knowledge. When designing and developing technologies to improve TR, it is important to consider usability, a key aspect that facilitates the use of the product and relates to the ability to learn, efficiency, error reduction, and satisfaction. The correct incorporation of usability must consider principles, metrics, and patterns that facilitate effectiveness, quality, and service usefulness. Lack of usability and a user-centered approach can lead to problems such as confusion, repetitive errors, or even abandonment of the TR program.In this paper, our proposal is to evaluate three TR platforms using the concept of "usability" from the field of Human-Computer Interaction. To carry out this evaluation, we will follow the process proposed by Rautela A. and utilize the CSUQ (Computer System Usability Questionnaire), which is an inquiry method used by IBM to compare the results with the SUS (Systems Usability Scale). The SUS will allow us to determine the acceptability of the TR platforms based on the final users' ratings. Platforms that score above 70 are considered "acceptable," while those that score between 50 and 70 are categorized as "marginal," and those below 50 are labeled "unacceptable." Our evaluation will focus on analyzing the usability of these platforms and identifying areas for improvement to enhance their overall user experience.The usability evaluation results will help us consider web platform design and development features for the TR of physical and cognitive disorders. Consequently, we encourage health professionals to adapt their job to TR, improving patients' autonomy and quality of life.The results of the usability evaluation will assist in the consideration of web platform design and development features for TR of physical and cognitive disorders. As a result, we encourage health professionals to adapt their practices to TR, ultimately enhancing patients' autonomy and quality of life.

Mayra Carrion Toro, David Morales Martinez, Marco Santórum, Patricia Acosta Vargas, Verónica Maldonado-garcés, Gloria Acosta-vargas, Manuel Ayala-chauvin, Esteban Ortiz-prado, Mario González-rodríguez

Conference Proceedings

Towards accessibility in educational resources for respiratory therapies

Ensuring accessibility to educational resources on respiratory therapies is crucial for patients and healthcare professionals to access accurate and up-to-date information. However, not all websites and resources meet accessibility standards, making it difficult for those with disabilities to access them. Multimedia resources, especially videos, pose unique challenges in terms of accessibility, but it is essential to develop methods and tools to assess and improve accessibility. This research applied a manual review method to evaluate video content with WCAG 2.1 guidelines. The results revealed that while the most complied with is the "perceptible" principle, with a compliance rate of 34.1%, the AA level, which is the appropriate level according to WCAG 2.1, is not reached. These findings emphasize the need for further efforts to improve the accessibility of educational resources, especially multimedia resources. This research can contribute to future studies and computer applications and help reduce the digital divide. The development of accessible educational resources is vital for promoting equal opportunities for all individuals to access and benefit from such resources, regardless of their physical or cognitive abilities. The findings of this study highlight the importance of continuous efforts to improve the accessibility of multimedia resources, which will ultimately lead to a more inclusive and accessible society.

Patricia Acosta Vargas, Marco Santórum, Mayra Carrion Toro, Gloria Acosta-vargas, Verónica Maldonado-garcés, Manuel Ayala-chauvin, Esteban Ortiz-prado, Camila Madera, Martin Saltos, Christian Tapia-reyes, Wilmer Esparza, Mario González-rodríguez

Conference Proceedings

AffectiveTree: Visualizing Collective Stress Amongst Chinese Telecommuters through Dynamic Painting

Under the epidemic situation of Covid-19, many companies are promoting telecommuting to protect employees' health. At the same time, telecommuting created an additional communication barrier for people to communicate with their colleagues or express their feelings. Stress can lead to health problems and burnout. In this paper, we propose AffectiveTree, a dynamic painting that can visualize collective stress among Chinese telecommuters in an abstract way. According to the stress level and duration of the Chinese telecommuters, the shape and color of the trees in the painting will be morphed. We used participatory design to involve the user in the design of the AffectiveTree and to verify its effectiveness and usability. The result showed that this dynamic painting could visualize the stress level of Chinese telecommuters through dynamic abstract art, and it can relieve their stress.

Zhenyu Liu, Cheng Yao, Qiurui Wang, Fangtian Ying

Conference Proceedings

Future design outlook of wearable devices

Wearable fitness devices have become increasingly popular among fitness enthusiasts, athletes, and health-conscious individuals seeking to improve their overall wellness. These devices have transformed how people approach fitness by providing real-time feedback and personalized insights into physical activity, sleep patterns, and other vital signs.In recent years, a significant focus has been on designing wearable fitness devices that can accurately track and monitor performance metrics. This has reshaped sophisticated sensors and algorithms to capture and analyze real-time data. However, the current generation of wearable fitness devices primarily focuses on tracking past performance and providing basic analytics.In the future, wearable fitness devices are expected to become more sophisticated and accurate in predicting future performance. This will be possible by incorporating advanced sensors and machine learning algorithms to analyze real-time data and provide personalized recommendations.One of the critical challenges associated with designing wearable fitness devices is the selection of appropriate sensors. Sensors must be able to capture accurate data that can be analyzed to provide meaningful insights into a user's physical activity, sleep patterns, heart rate, and other vital signs. Some commonly used sensors in wearable fitness devices include accelerometers, gyroscopes, heart rate monitors, and GPS. However, integrating these technologies into wearable devices contributes to a limitation in the space of such devices, which may result in reduced user comfort while wearing them. However, there is a possibility that the monitors and integrated chips can be made softer in the future. This is also in line with the development trend of wearable devices, which are expected to become more comfortable and user-friendly over time.In addition to sensors, wearable fitness devices must incorporate advanced algorithms to analyze data and provide accurate predictions. Machine learning algorithms are particularly well-suited for this task, as they can analyze large volumes of data and identify patterns that are difficult to detect using traditional statistical methods. These algorithms can predict future performance based on past activity, identify areas for improvement, and provide personalized recommendations for training and recovery. Real-time data monitoring is essential for timely interventions in the early stages of health issues, facilitating early detection and intervention, and maintaining long-term health prevention.Another important consideration when designing wearable fitness devices is user experience. Wearable devices must be easy to use, comfortable, and visually appealing. A well-designed interactive interface can significantly enhance users' interest in wearable devices and their overall experience while using them, ultimately helping them to achieve their health goals more effectively.Besides, they must also integrate seamlessly with other devices and platforms, such as smartphones and fitness apps.In the future, wearable fitness devices can potentially revolutionize how people approach fitness and wellness. Real-time performance prediction can give users a more accurate and personalized view of their physical activity, allowing them to optimize their training and recovery. Customized coaching and recommendations can help users achieve their fitness goals more efficiently and effectively.Overall, the design of wearable fitness devices and their ability to predict future performance is an exciting area of research and development. As technology evolves and improves, we expect to see more sophisticated and accurate devices that provide users with a comprehensive view of their health and wellness.

Zhiming Liu, Xiangyu Liu

Conference Proceedings

The impact of the complexity of the interactive interface of e-commerce apps on user satisfaction and efficiency

Objective With the rapid development of e-commerce, more and more people have begun to use e-commerce apps for online shopping. However, with the continuous expansion of e-commerce App functions, its interactive interface is becoming increasingly complex. This could affect user satisfaction and shopping efficiency, but the issue must be thoroughly studied. Therefore, this study explores the impact of the complexity of e-commerce apps' interactive interfaces on user satisfaction and efficiency. Methods A questionnaire survey was conducted in this study on the aspects of function and content, navigation bar, controls and elements, layout and design, device compatibility, and their satisfaction scores were collected. A total of 89 valid questionnaires were collected from Chinese users. Then SPSS was used for data analysis.Results The results show that the complexity of the interactive interface of e-commerce apps significantly impacts user satisfaction and efficiency. There is a negative relationship between the complexity of the interactive interface and shopping satisfaction and a negative relationship between the complexity and shopping efficiency. In addition, users pay more attention to product information's presentation and recommendation function when shopping. Hence, they must pay more attention to these aspects when designing e-commerce apps. Conclusion and Revelation This study confirmed the influence of the complexity of the e-commerce App interface on user satisfaction and efficiency. Our results suggest that simplified versions of e-commerce apps can improve shopping efficiency. These results suggest that e-commerce App developers need to balance shopping efficiency and user satisfaction in interactive interface design and make customized designs according to the needs of their target user groups.Keywords: Interactive interface complexity, user satisfaction, shopping efficiency

Xinran Liu, Li Xu

Conference Proceedings

Design and Evaluation of Affinity Expressions for Child-like Characteristics Robots

With the rapid development of service robots in the senior care industry, academics have paid more attention to the study of the expression and perception of affinity for companion robots in order to reduce user barriers and mistrust. We designed an aging-in-place service robot, CareBot, and proposed six design guidelines for affinity expressions of child-like characteristics. These affinity expressions were evaluated by simulating the interaction experiment of aging in place. The results showed that participants identified three of the affinity expressions (enthusiastic, indifferent and safety) significantly more correctly than the other three (pleasant, friendly and approachable). We further found that the appearance of robots with child-like interaction characteristics such as big-eyed expressions, cute movements, and children's voices are more approachable to the elderly and are easily appreciated by them.

Huang Zhaohui, Liu Shun, Zhu Chunxue, Huang Xue

Conference Proceedings

The use of gamification in the knowledge management practices

This study develops a new conceptual model through an extensive review of previous literature and explains how gamification artifacts such as points rewarding is inducing intrinsic motivation and how those motivational factors like knowledge self-efficacy and playfulness are influencing the employees' knowledge sharing attitudes, through which the intentions are shaped. The Theory of Reasoned Action and the Motivational Affordances Perspective (MAP) model are used to explain the mediation effect of intrinsic motivation on the relationship between the gamification artifact and employees' attitudes towards knowledge sharing. This study also focuses on identifying the factors that improve the predictability of attitudes towards knowledge sharing. In a managerial context, this study helps practitioners recognize the importance of devising strategies and creative ideas to include and advance the features of gamification artifacts in their gamification systems to enhance their intrinsic motivation and drive an inner change in employees to share knowledge with others.

Prasheenaa Jeyaranjan, Rukshan Alexander

Conference Proceedings

Building a Better Mouse App: New Modalities For Human-Computer Interaction

The rigid conventions for mouse and keyboard design are ripe for reinvention. We present a collection of new modalities for mouse and keyboard design, which explore possibilities that untether the user from the constraints of surfaces, both screens and tables, and investigate novel relationships to emerging HCI modalities that reconsider how we situate the user in physical and virtual space. We discuss our design process, and present a collection of prototypes that serve as provocations for this and future work. We conclude with a discussion about how these prototypes might provide new opportunities for HCI design in augmented and virtual reality, as well as their application to new possibilities for ubiquitous computing.

Ian Gonsher, Frank Carber, Jesse Gallant, Fuka Ikeda, Chien Lu, and Claire Poissonnier

Conference Proceedings

The Effect of Auditory Stimulus on Gazing Behavior in Driving Assistance Systems

In order to prevent traffic accidents caused by drivers ' inattention, various driving assistance systems have been developed. These systems alert the drivers through sound and warning displays. However, since the type of sound and the location of the sound differs depending on the car model, if the driver does not pay attention, may miss the warning signs. This study examines a method to support drivers' perception of danger by presenting auditory stimuli to promote visual awareness of an arbitrary location. A previous study showed that when a simple visual task was used, the presentation of stimulus sound accelerated the selection of the next fixation target. There were differences in confirmatory behavior toward the target depending on the direction of sound production. Based on these results, we hypothesized that when watching actual driving images, the differences in gaze behavior would emerge depending on whether sounds were presented from the target direction and the type of sound and measured subjects' gaze. The results obtained in this study do not indicate that the sound has an inductive effect, because there are conditions and non-existences in which the sound significantly shortens the induction time of the target. In addition, it is considered that a motive to move the subject's gaze is necessary to induce visual attention, and the induction of attention by auditory stimuli is considered only an auxiliary function. In a subjective evaluation conducted after the experiment, more than half of the subjects responded that their attention was directed toward the direction of the sound presentation. We would like to examine the relationship between sound presentation and picture features and its effectiveness in inducing attention in the future.

Kisa Takao, Hironori Uchida, Yujie Li, Yoshihisa Nakatoh

Conference Proceedings

Investigation of Graphical User Interfaces for Online Driving Style Customization of Highly Automated Vehicles

Technological progress in the field of autonomous vehicles may lead to the introduction of such vehicles into traffic in the upcoming decades. However, user acceptance of the technology is an important factor besides the technical possibility of the introduction of the technology. Since driving is a complex task and people drive differently, they may prefer different driving styles of an autonomous vehicle. Giving the users the possibility to adjust and personalize the driving style of their autonomous vehicle might help with the user acceptance and adoption of the technology. For this purpose, we conducted a driving simulator study wit N=11 participants to investigate whether the participants would like to have the possibility to adjust driving style parameters through a graphical human-machine interface. During the experiment the participants experienced a simulated ride in a fully automated vehicle in a dynamic driving simulator and had the possibility to change driving style parameters like the speed or time-headway of the simulated automated vehicle. After the experiment the participants filled out a questionnaire with items about technology acceptance. Overall, the results of the questionnaire suggest that the participants found the HMIs beneficial. Overall, there was an above average rating of 4.38/5.00 that such driving style personalization HMIs are going to support the driver during the vehicle use. By analyzing the experimental data, we found that most of the participants were able to find a suitable set of driving style parameters before the end of the experiment. We hypothesize that the possibility for a user to adjust some driving style parameters may help the adoption of the technology and its user acceptance.

Alexander Trende, Ina Krefting, Lars Weber, Andreas Lüdtke, Jochem Rieger, Martin Fränzle

Conference Proceedings

Systematic review of technologies to collaborate and co-educate students with special educational needs and supporting their schooling

Since 1994, the inclusion of students with special educational needs (SEN) has been a vital part of the educational system (UNESCO, 1994). In the early 2000s, educational systems underwent reforms to accommodate this change, leading to increased communication and collaboration efforts between families and educational partners (Wehmeyer & Patton, 2017). These efforts are supported by the growth of digital technologies (Kefallinou et al., 2020; Zallio & Ohashi, 2022). Various models of family-professional collaboration, such as the "Sunshine Model" (Haines et al., 2017), "Whole School Model" (Lewallen et al., 2015), "Smart Holistic Model" (Hafidh et al., 2019), and polycentric approaches (Ebersold & Detraux, 2013), have been developed to involve the broader educational community.Despite the integration of technologies and the recognized importance of collaboration, limited research has been conducted on the potential of collaborative technologies in the educational context for SEN. However, relevant stakeholders endorse their use.To address this gap, a systematic review of international literature was conducted to identify collaborative technologies for the inclusion of SEN, along with their advantages and limitations. Out of 1360 identified articles, 10 were selected for analysis.These 10 articles focused on 8 different digital technologies that facilitate collaboration between families, education, and healthcare actors. The technologies were developed using various methodologies and aimed at different communication and collaboration objectives. Some technologies focused on communication related to student behavior or school activities, while others emphasized collaboration related to the student's inclusion project.We will present each of these technologies, their development context, as well as their advantages and limitations. We will hightlight their relevance to the different theoretical models applied to family-professional collaboration, and their contributions Finally, we will highlight the contributions of collaborative technologies to promoting SEN inclusion and reducing educational inequalities.

Eric Meyer, Hélène Sauzeon, Isabeau Saint-supery, Cécile Mazon

Conference Proceedings

Informational Assistance System – a Key to Self-Empowerment of Persons with Cognitive Disabilities in Manual Assembly?

The development trend in manual assembly towards increasing demands in terms of quality, variety, and cost pressure makes the transition for people with cognitive disabilities to the general labor market extremely difficult. Nevertheless, this employment sector is a central component of many activities in a sheltered workshop. Therefore, this paper investigates the use of an informational assistance system for persons with cognitive impairments to close the gap between the characteristics of this group and the operational requirements. In this way, the transition from the sheltered workshop to the general labor market will be facilitated and promoted.

Sven Bendzioch, Sven Hinrichsen

Conference Proceedings

Hybrid Cognitive Capabilities in EDGE Operations

Contemporary and future defense and security operations are increasingly time-critical, resource-critical and safety-critical, requiring vigilance, awareness and determination. Commanders and operators frequently encounter uncertainty, risk, time-criticality and resource shortages while mastering the challenges of distributed, complex systems, strong functional coupling and interdependencies. Operational characteristics are highly dynamic and non-linear; Minor events, decisions and actions may have serious and irreversible consequences for the entire mission. This requires adaptive and versatile principles and concepts for Emergent, Dynamic, Global and Evolutionary operations (EDGE) operations, along with high-performance human and technological (i.e. hybrid) cognitive capabilities.Additionally, operating in a hazardous operational environment requires comprehensive operational awareness - shaped, supported and utilized by human and machine agents, in joint capabilities. Joint human-machine agents constitute hybrid capability components, able to accurately and rapidly sense, perceive and interpret relevant events and circumstances in order to sustain and improve decision-making and action, enabling every commander and operator to develop a wide-ranging appreciation of the situation. This paper is a précis of a balanced analysis, development, evaluation and assessment of hybrid multi-domain scenarios where the EDGE operational approach is superior regarding managing and maintaining operational availability, versatility and efficiency. A number of strategic capability elements will be identified and described. The capability elements will be incorporated in a dynamic capability architecture, operationalized into measurable evaluation criteria, enabling hybrid cognitive capabilities to accurately and rapidly perceive and interpret mission-relevant events and circumstances, in order to provide the context, insight and foresight required for effective decision-making and action. Complex Information and Cyber Operations are of particular concern; while some operational tasks necessarily would employ a human component, other tasks can only be accomplished through non-human intelligent entities, acting autonomously within the socio-technical enterprise. The Cognitive Systems body of research was utilized to overcome the duality of traditional human-machine research, focusing on better understanding what people actually do with technology rather than what functions belong to the machine and what functions belong to the human. The Complex Adaptive Systems (CAS) body of research contributed with characteristics of self-learning, emergence, and evolution among the entities of the complex system, demonstrating heterogeneous and adaptive behavior. According to the body of research for Autonomous Adaptive Agents (AAAs), an agent is also viewed as a team member, meaning it is able to autonomously complement human decision-making when executing its tasks. Building cognitive systems and capabilities requires a mental shift – striving towards an Agility mindset that permeates security and defense policy, legal and financial frameworks, science and technology agendas, strategy and operations. Adopting an EDGE perspective requires matching internal operations with the degree of turmoil of the external environment, a principle known as requisite variety. EDGE defines system structures across domain boundaries and operational dimensions through an intersection of fundamental operational dynamics: Physical, Information Cognitive and Networks, allowing actions in one domain, ex. cognitive, to achieve an operational effect in another, ex. physical. A conflict situation within or with operational reach into the information and cognitive dimensions can rapidly escalate or change character in fractions of a second, and this requires adequate response times. This is beyond the ability of humans, hence requiring the use of high-performance, automated cognitive capabilities comprised of multiple, distributed human-autonomy systems. Furthermore, without the appropriate distribution of information, and the necessary decision rights to the AAAs that match their required level of autonomy, the decisions and actions needed for success in MDO will not be achieved in a timely manner.We propose formulating a future-oriented Essence of Joint Cognitive Systems Command, with equal relevance and applicability on human operators and artificial agents. Employing the Cognitive Systems, CAS and AAA paradigms for MDO permits the integration of all capability elements into an adaptive distributed system that can achieve a mission safely and efficiently. This Essence of Command is domain agnostic and applicable for human as well as non-human agents, although the dynamics are different.

Arne Norlander

Conference Proceedings

Legal preconditions for sustainable remote work in EU in the time of emerging technologies

The aim of sustainable work is to create a living and working environment that encourages individuals to enter and remain in the workforce for an extended period. During times of crisis, sustainable work has become a key factor in supporting economic growth while simultaneously prioritizing workers' well-being. While emerging technologies have the potential to enhance productivity, they can also contribute to an "always-on" culture in the workplace and widen working time, which can adversely affect the work-life balance of remote employees. Assessing the legal framework for remote work in the EU and its suitability for ethical employment practices, it is essential to support the future viability of remote employees' professional lives. Although an increasing number of individuals are choosing to work remotely, and more companies are offering remote work options, there still are unresolved legal issues in EU regulations, such as the definition of working time in the context of remote work and the regulation of employees' right to disconnect. Additionally, EU member states have differing attitudes towards promoting remote work, which can create a risk to the protection of employees' rights and the principle of equality within the EU.The goal of the research is to provide a comprehensive analysis and identify legal obstacles to sustainable remote work in the EU, based on an examination of the legal framework in the EU and case law of the EU Court of Justice and to draw evidence-based conclusions about the legal preconditions of sustainable remote work in EU.The research employs thorough research methods including literature analysis, legislation analysis, case law analysis, and secondary data analysis. The author uses different legal research methods, such as analytical, comparative, deductive, and inductive to identify legal obstacles to sustainable remote work in EU regulations. The main findings indicate that, even though there are efforts at the EU level to promote remote workers' well-being and legal protection, specific tools in EU legislation are still required to achieve the objective of sustainable remote work in the EU. For instance, the right of employees to disconnect has been initiated, but no legally binding document has been created to execute this right uniformly across all EU member states. It is also determined that different levels of encouraging remote work exist in EU member states, resulting in various protections for remote employees. This results in a scenario where remote workers have no efficient legal protection, which can be a basis for human rights violations. The research also finds instances of successful remote work initiatives and good practices in the EU, highlighting the potential advantages of sustainable remote work.

Marta Urbane

Conference Proceedings

Respiratory Disease Diagnosis through Comprehensive Analysis of Spectrograms of Lung Sounds

The study proposes a digital stethoscope to assist physicians who are not respiratory specialists to diagnose specific diseases from lung sounds in local areas which lacks specialists and advanced medical equipment. The digital stethoscope presents a spectrogram of the auscultatory sound that illustrates changes in its feature values to visually present the area where the abnormal sound occurs. It not only assists non-specialist physicians in diagnosis but also provides easier explanations for patients. Accurate auscultation requires specialized knowledge and experience. Non-specialist physicians have difficulty distinguishing the characteristics of abnormal sounds among lung sounds which include a wide variety of sounds. Even if they find an abnormal sound suspected to be a disease, physicians will provide patients with only oral diagnosis explanations which would prevent patients from understanding their conditions in depth. The proposed method converts lung sound data collected by a digital stethoscope into a visual spectrogram showing the frequency features. The method uses the short-time Fourier transform as a method to extract the frequency features of lung sounds for each short segment in the whole time series of the lung sound. The converted spectrogram is used to detect disease-specific abnormal sounds comprehensively. The degree of abnormal sounds that appears in the inspiratory and expiratory phases varies with disease progression. The proposed method identifies abnormal sounds in the inspiratory and expiratory phases. Based on the inspiratory and expiratory phases recorded in the diagnostic by specialists, the method derives whether the abnormal sound occurs in each phase. It enables the method to detect specific respiratory diseases along with the degree of their progression. Furthermore, it also allows the method to visually present the location of detected abnormal sounds to patients. This paper uses a short-time Fourier transform as a method for extracting frequency features of lung sounds in a certain range. It also shows that feature extraction as a spectrogram that emphasizes the low frequency band, which is the human audible range, is effective in assisting the non-specialist physician in diagnosis. This paper prepares experimental data from real diagnoses so that data noise and disease features can be taken into account. The diagnostic accuracy is evaluated with a method of segmenting spectrogram images to extract frequency features at specific times. The method constructs a model for detecting fine crackles using the machine learning algorithm Decision Tree. The experimental results have shown that the accuracy of detecting fine crackles is 0.89. The high accuracy obtained from this model allows us to confirm the effectiveness of the proposed method for supporting for non-specialist physicians to distinguish abnormal sounds. The successful detection of fine crackles in the expiratory or inspiratory phase suggests that the progression degree of the disease could be estimated with the proposed digital stethoscope. The digital stethoscope will make it possible to accurately diagnose respiratory diseases along with a comprehensive explanation of diagnosis results to patients in areas with poor medical facilities. It also provides non-specialists with dependable diagnostic aid.

Takuma Mitsuke, Hiromitsu Shimakawa, Humiko Harada

Conference Proceedings

Decision-making while interacting with unmanned vessels

The presence of autonomous vehicles in the maritime domain is already a reality, even though being confined to very specific domains of operations (environmental monitoring, surveillance and defense, R&D) or segregated spaces (exclusive spaces for the operation of autonomous vehicles). Artificial Intelligence algorithms for navigation control applied in autonomous vessels are based on the adoption of rules that currently regulate navigation, namely the International Collision Regulation (ColReg), the maritime Buoyage System, and routing regulations. However, considering Jen Rasmussen's decision model, in many situations, the navigator makes decisions not only based on rules (Rule-Based) but based on perceptions that stem from his skills (Skill Based) or knowledge (Knowledge-Based). An example is the concept of safe speed or safe distance, defined in ColReg, but with a variable quantification depending on the circumstances. On the other hand, the navigator's perception of the concept of navigation safety varies significantly and usually goes beyond the ship domain. For instance, some may decide not complying a ColReg priority rule to facilitate another vessel's movement and prevent a decrease in the operation safety level. Safety perception is conceived holistically, that is, it is not restricted to the vessel, but to all those in the vicinity and the natural environment. Finally, it is important to understand the behaviour of navigators in the face of the existence or interaction with unmanned vessels, not only to understand how the decision process is affected but also to improve the AI algorithms applied in autonomous vehicles.To understand how the perceived status of the encountered vessels affects the navigator's decision, we conducted an experimental study to assess how the decisions made by the participant vary when interacting with unmanned vessels. Recognizing that trust in automation is a critical influential factor, we adopted existing framework models to evaluate the participants' perceptions of Maritime Autonomous Surface Ships (MASS), as classified by the International Maritime Organization.The adopted method comprises a combination of questionnaires and participation in six simulated scenarios. This mixed approach aimed to understand the familiarity with MASS; the need to change operational regulations; concerns, challenges, and opportunities from the implementation of MASS; trust in MASS; and the differences between the declared perception and decision-making when interacting with MASS.The study comprised three stages. firstly, a pilot study to appraise and validate the questionnaire, with 49 participants. Secondly, the online implementation of the questionnaire, with a desktop version of the six simulated scenarios, with 110 valid questionnaires, 73 students from the naval academy and 37 professional mariners. Each scenario presented an interaction situation with another vessel, referencing a clearly stated rule of the Collision Regulation. The target vessel could randomly assume one of three statuses: Manned vessel, Unmanned vessel and unidentified vessel. By varying the control mode of the target vessel in the same situation, we aimed to see if the perceived status of the vessel had any influence on the decision-making process. In the last stage of the study, the six desktop exercises of the scenarios were replaced by a simulator game of the same situation, with 33 participants. On the desktop exercise participants reported: Time for acting, change of heading, change of speed, and aimed final position. Reaction time, change of heading and speed were automatically logged on the simulator game. The questionnaire comprises four sections: Unmanned vessels and levels of automation, scenarios decisions, trust in automation and demographic data.The results suggest that despite having a reduced familiarity with autonomous ships, the participants have a very positive opinion. However, in the same situation, they react differently to conventional ships and autonomous ships. The way navigators react was analyzed through parameters such as reaction time, course and speed variation and the Closest Point of Approach between vessels. There is a greater discrepancy between those parameters in participants with less training, suggesting a need to address the issues of interaction with unmanned vessels during the course program. Results from the simulators provided more precise shreds of evidence, namely when interacting with unidentified vessels, pointing out the need to design solutions for clear identification of the target vessel.

Vítor Fernando Plácido Da Conceição, Beatriz Sousa, Pedro Água, Joakim Dahlman

Conference Proceedings

Integrating Rule Based Expert Systems into a Simulation framework for digital twins

The loss of expert knowledge due to experienced workers retiring in the coming years poses a significant challenge. To address this, we proposed to digitize and preserve this knowledge using the digital twin concept. Traditionally, expert systems have been used to emulate human experts. Rule-based expert systems, such as Prolog and CLIPS (C Language Integrated Production Systems), are one class of expert systems. Fuzzy CLIPS is an extension to CLIPS that can handle Fuzzy logic. Compared to machine learning techniques such as neural networks, rule-based expert systems are more reliable and can provide explanations for their reasoning.VEROSIM is a simulation framework for Digital Twins, into which Fuzzy CLIPS was integrated. Rules are executed depending on the status of the Digital Twin or user input and manipulate the state of the digital twin or generate an output. The Network Modeler is a graphical user interface built with QML that was developed to enhance the process of connecting simulation components, similar to OpenModelica, and visualize or manipulate the data flow between ports. The network modeler was extended to support the formulation of CLIPS rules. The existing Rule Visual Modeling Language was adapted for this purpose. The user can use the GUI to create thing templates, add properties called slots whose state can be fuzzy, such as cost (from low to high) or surface quality (low to high), and based on these templates, rules can be formulated. Rules have zero to several conditions and at least one action that is executed when the conditions are met. VEROSIM objects were created and mapped to a QML file for all required components, which defines the appearance inside the Network Modeler. A parser either parses FuzzyCLIPS code and produces a VEROSIM Model of the rules that can be visualized in the Network modeler or the user can graphically build the rules and the parser produces executable code. This approach allows non-experts to easily build a rule-based expert system, which can be extended or changed even during execution. Additionally, it can visualize which conditions lead to which actions in a more intuitive way than looking at the code. Finally, the integration into VEROSIM allows for direct interaction with the digital twin.This process is used to recommend the best tool to use based on optimization parameters given as user input and the geometry of a part to produce in the context of the production of individualized parts made out of fiber-reinforced plastics. The result will be stored in a production plan which is part of the digital twin and information about the produced part is fed back to the digital twin and used to update the ruleset of the expert system.

Dominik Hüsener, Jürgen Roßmann

Conference Proceedings

Machine Vision, Prompts and Neural Network Structure in Art: Reverse Engineering in Image Generation

The paper proposes the use of reverse engineering and artistic creation perspective to explore the convergence of machine vision and neural networks for generating images that closely resemble the original objects. With the rapid and significant development of machine learning and neural networks, these technologies have garnered significant attention in recent years due to their image generation and prompt text functions, which offer new possibilities. Rather than utilizing these technologies solely for creating new works, it is important to investigate their potential for generating images that resemble the original objects. By converging different technologies in the era of machine intelligence, it is possible to achieve greater flexibility and adaptability in image generation processes, leading to a wider range of potential outcomes. It is hoped that it can shed light on the possibility of generating images in particular using artistic approaches.

Lai Man Tin

Conference Proceedings

Assessing the Transparency and Explainability of AI Algorithms in Planning and Scheduling tools: A Review of the Literature

As AI technologies enter our working lives at an ever-increasing pace, there is a greater need for AI systems to work synergistically with humans at work. One critical requirement for such synergistic human-AI interaction is that the AI systems' behavior be explainable to the humans in the loop. The performance of decision-making by artificial intelligence has exceeded the capability of human beings in many specific domains. In the AI decision-making process, the inherent black-box algorithms and opaque system information lead to highly correct but incomprehensible results. The need for explainability of intelligent decision-making is becoming urgent and a transparent process can strengthen trust between humans and machines. The As AI technologies enter our working lives at an ever-increasing pace, there is a greater need for AI systems to work synergistically with humans at work. One critical requirement for such synergistic human-AI interaction is that the AI systems' behavior be explainable to the humans in the loop. The performance of decision-making by artificial intelligence has exceeded the capability of human beings in many specific domains. In the AI decision-making process, the inherent black-box algorithms and opaque system information lead to highly correct but incomprehensible results. The need for explainability of intelligent decision-making is becoming urgent and a transparent process can strengthen trust between humans and machines. The TUPLES project, a three-year Horizon Europe R&I project, aims to bridge this gap by developing AI-based planning and scheduling (P&S) tools using a comprehensive, human-centered approach. TUPLES leverages data-driven and knowledge-based symbolic AI methods to provide scalable, transparent, robust, and secure algorithmic planning and scheduling systems solutions. It adopts a use-case-oriented methodology to ensure practical applicability. Use cases are chosen based on input from industry experts, cutting-edge advances, and manageable risks (e.g., manufacturing, aviation, waste management). The EU guidelines for Trustworthy Artificial Intelligence highlight key requirements such as human agency and oversight, transparency, fairness, societal well-being, and accountability. The Assessment List for Trustworthy Artificial Intelligence (ALTAI) is a practical self-assessment tool for businesses and organizations to evaluate their AI systems. Existing AI-based P&S tools only partially meet these criteria, so innovative AI development approaches are necessary. We conducted a literature review to explore current research on AI algorithms' transparency and explainability in P&S, aiming to identify metrics and recommendations. The findings highlighted the importance of Explainable AI (XAI) in AI design and implementation. XAI addresses the black box problem by making AI systems explainable, meaningful, and accurate. It uses pre-modeling, in-modeling, and post-modeling explainability techniques, relying on psychological concepts of human explanation and interpretation for a human-centered approach. The review pinpoints specific XAI methods and offered evidence to guide the selection of XAI tools in planning and scheduling.

Sofia Morandini, Federico Fraboni, Enzo Balatti, Aranka Hackmann, Hannah Brendel, Gabriele Puzzo, Lucia Volpi, Davide Giusino, Marco De Angelis, Luca Pietrantoni

Conference Proceedings

Pay-per-use models, the backbone of a sharing economy: How to stimulate a sustainable human-centered ecosystem success to achieve a faster Society 5.0

In Society 5.0 humans aim to leverage advanced technologies to create innovative solutions for social and environmental issues. Public awareness of the need to act now to shape a liveable future for the next generations and to set the course for a climate-friendly and sustainable future has reached its peak. This societal and political pressure is currently changing and will change industries, corporate strategies, buying behaviors, and society dramatically and lastingly in the coming years. Strengthening the concept of the sharing economy is essential to achieving the sustainability goals of Society 5.0. Effective and mature implementation of pay-per-use models is the heart of the sharing economy and essential to drive that concept to the next level. Due to their cost-effectiveness, flexibility, scalability, and predictability pay-per-use models are attractive to both businesses and consumers and offer several benefits. Pay-per-use is nowadays established as the standard for payment processes of native cloud services, electric vehicles, and many others, but the full potential is not exhausted, and currently serves as a payment model rather in niche areas. We will discuss how this can be changed, and what possible implementations could look like enabled with micropayments, cryptocurrencies, and distributed ledgers. We will provide the architecture overview and explain how it fits future (should we change for the future or leave current?) banking architecture. The implementation of frictionless payment models is a significant opportunity to improve customer perception and increase revenue by providing a more convenient, secure, and efficient payment experience and is, therefore, a win for the industry, consumers, and the environment. Finally, we describe what obstacles there have been so far in implementing, and what a roadmap to strengthen pay-per-use models and sharing economies might look like.

Joerg Kleine-gung, Elizabeth Koumpan

Conference Proceedings

How to Generate Assembly Instructions with Robotic Process Automation

With the trend towards shorter product lifecycles, smaller batch sizes, and more product variants, the complexity of manual assembly activities is increasing. To support employees in carrying out complex assembly tasks, the use of assembly instructions is indispensable to ensure high process capability and work productivity. However, the creation of assembly instructions is often time-consuming. Thus, the use of automation approaches can be a way to simplify the creation of assembly instructions. Therefore, this paper introduces a promising automation concept for applying robotic process automation (RPA) to generate assembly instructions automatically. Finally, the automation concept is demonstrated in a practical use case that illustrates the associated automation potential of RPA.

Frederic Meyer, Sven Hinrichsen, Oliver Niggemann

Conference Proceedings

Quality Function Deployment Implementation using Digital Twins Paradigm

Considering the Information Technology continuous innovation and upcoming technological trends, industries are now more eager to utilize inventive technologies to adopt and efficiently function in today's competitive business environment. Technologies such as big data, IoT and now digital twins are now being widely applied through a broad spectrum of different industries and have already had a game-changing impact. Technologies such as digital twins despite coming the extra mile in recent years still hold a more promising future. Digital twins will emerge as one of the key tools in many industries, especially in manufacturing. This paper takes a closer look at how the retail industry is utilizing digital twins to better implement quality function development of a product. With the proposed framework, Quality function developments can be improved to collect data from customers through social networks and boil down the data of the voice of the customer through product development process. These Voice of the Customer items will continue to trickle down into other stages of product development and deployment, including component definition, process planning, and quality control. This study has established a connection among social media data analytics and links it to QFD framework. Using social media data, the emotions of the customer can be viewed in real-time what people are saying about the product. This not only helps in creating a better product it also enriches the customer experience. To clarify the capabilities of the proposed idea, an illustrative case is designed and explained for link of social data analytics tools with QFD through a digital twin enabled framework. This gives customers a chance to be integrated into the product development process and as a result, produce results in better satisfying customers' expectations.

Remmon Sarka, Omid Fatahi Valilai

Conference Proceedings

A Framework For Assessing The Impact Of Potential Disruptive Technologies In Business

Today's world prompts businesses with increased challenges in what competitiveness concerns. Challenges span from the need for a post-pandemic recovery to the hardship driven by world conflicts, growing energy prices, and inflation among others. With the resulting intense competition businesses look for news ways to innovate and gain a competitive edge on their arenas. Technology has been a major driver for business competitiveness, and the acceleration in the creation of new products and services only makes matters more difficult for most businesses. Business leaders and top management teams across industries have to manage finite resources and funds, while at the same time deal with tough choices on how to react on technological threats which may affect their businesses, sometimes with catastrophic consequences, as has happened by the effect of technological change over history. At other times some apparent technological advantage my prompt business leaders to choose among alternative technological paths. Such decision makers oftentimes lack a framing and pragmatic approach to assess such potentially disruptive technologies.This paper proposes an alternative framework for assessing the impacts of potential disruptive technologies across business relevant dimensions – the sort of competitive edge companies look for when searching for a competitive edge. This research followed a critical thinking approach supported by alternative analysis techniques. The framework proposed comprises five dimensions: strategic, operational, tactical, technical, and organizational. The strategic dimension considers political, economic, military, cultural, and legal factors as variables. The operational dimension evaluates performance, congruence, and opportunity. In the tactical dimension, the variables are secrecy, as well as tactics, techniques, and procedures. The technical dimension takes into account performance, maturity, and interconnectedness. Finally, the organizational dimension includes internal support, pacing gap, and cost as variables. Examples of historical disruptive technologies will be provided. By analyzing the impact of a specific technology on these dimensions and variables, the framework can determine whether the impact is null, moderate, high, or revolutionary. The framework that is suggested for evaluating the impact of potentially disruptive technologies serves as a valuable tool for informing policymakers, business and industry leaders, and supporting decisions concerning technology investment, capability development, and other strategic initiatives.

José Paulo Silva Bartolomeu, Pedro Água

Conference Proceedings

Emerging technologies for carbon reduction in building industry: Evidence from patent inventions

According to the "Global Building Construction Industry Report" released by the United Nations Environment Programme, the carbon emissions generated by building operations alone have reached about 10 gigatonnes in 2021. With its rapid and large-scale urbanization, China is one of the main contributors to the global carbon emission. Decarbonization thus became the central task for China's building sector. Emerging technologies, especially digital technologies, provide the potential for building decarbonization, which is possibly realized through the full life cycle of buildings. Yet, understanding towards a localized innovation of these technologies and how they engage carbon reduction remains far from clear. Moreover, due to the large scale and massive nature of buildings, threshold of business applications of these emerging technologies is high thus discussed insufficiently. Draws on literature and expert review, this research discloses the linkage of 14 specific emerging technologies and building decarbonization in a full life-cycle (the planning, construction, use/operation and demolition phases) of buildings. Yangtze River Delta, one of the fastest urbanizing and largest market for building sector in China, is selected for observation. With an OT-matrix and over thousand sorted patent inventions, it identifies that contribution of the emerging technologies to building decarbonization is most secondary. Quite a few general-purpose technologies (e.g., blockchain, IoT), which possibly disrupt the industry fundamentally, are almost vacant. State owned enterprises are the main actors in the technology innovation, followed by university and public research institutions. There is a mixed location of downtown, periphery and outskirts characterizing the spatial pattern of these technologies. The findings help to recommend policy makers, firm managers, professionals and researchers in accessing and developing disruptive technologies for low carbon building industry, and promote business application in this field.

Lingyue Li

Conference Proceedings

Sustainability Aspects of Logistics and Operation Fulfillment in Cloud Manufacturing Systems

The manufacturing business models have been recently revolutionized due to emerging technologies and theories like Cloud manufacturing and service-oriented paradigms. However, the requirements of the current globalized economy for environmental and sustainability aspects have been neglected. This paper aims to consider sustainability as a key element in emerging paradigms like Cloud manufacturing and propose a model to minimize the negative environmental impacts in terms of considering energy, natural resources, and CO2 emissions. Moreover, it tries to concentrate on aspects like quality, environment, logistics, and service to create a measurement for companies to transform from product-oriented manufacturing to service-oriented manufacturing. Considering the recent studies on Cloud manufacturing systems and their contributions toward environmental aspects, an evaluation model has been proposed for sustainable Cloud manufacturing systems with a focus on global logistics. The role of different stakeholders inside Cloud manufacturing business models in respect of the evaluation model is discussed.

Noushin Mohammadian, Xiaotong Fan, Omid Fatahi Valilai

Conference Proceedings

An organizational and operational capability and maturity assessment for SMEs in emerging markets towards the ESG criteria adaptation

SMEs are considered the backbone of every economy forming nearly 95% of the private sector globally. As they are mostly family businesses, start-ups or specialized enterprises, they operate mainly locally or regionally with a direct impact to the society, the, employment and the national economy. On the other hand, due to their limited size and operations they cannot afford the cost and effort needed for long term planning and strategy development that can secure the value, volume, reputation and recognition needed to attract investments. The ESG criteria can be considered as a privilege system primarily for the large-scale organizations and the Multinational Enterprises whose financial and human resources can be easier allocated on ESG activities that return serious financial and reputational benefits. Research indicates that more than 90% of the investors invest only in companies with high social and sustainable profiles. The message from investors and consumers is that if companies cant show any sign of changing their business models, they wont be able to sell. The same applies at country level. Finland for example does not offer any business opportunities to any company that does not have a solid and proven sustainability strategy and track record. This trend, for clients and investors, to consider only Green (sustainable) or Pink (Social) products and companies for their purchases and investments, drives all types of organizations towards that adaptation of the ESG criteria. However, and since such a strategy requires investments, resources, funds and time that only Multinational organizations can provide, SMEs are left out from any opportunity to develop, grow, and compete. This paper highlights this ESG discrimination among the SMEs and MNEs and intends to bridge this gap by identifying, in a smaller scale, activities that reflect the ESG criteria and can be implemented by the SMEs at organizational and operational level. Such an approach provides SMEs the opportunity to record, report and receive credit, visibility and recognition for their sustainable, social and ethical governance efforts and actions, that can potentially enlarge their customer base and attract the investments needed to further develop themselves. The proposed approach is based on an assessment that creates an SME ESG roadmap framework for the SMEs to initially identify their ESG awareness and maturity before adopting any ESG related strategy and commitment. The assessment highlights the SMEs capability and maturity to adopt such a mid-range strategy and align their operations with the ESG criteria on a smaller scale. The results of the assessment formulate an achievable ESG related strategy for each SME, identify the key ESG activities to be implemented, indicate their order of execution, and predict a performance score upon the completion of the proposed strategy. This score can be utilized by SMES to receive social, reputational and financial recognition for their contribution to the local and regional society and economy. To secure the relevance of the SMEs ESG oriented activities with the actual ESG requirements, the proposed approach has been developed after studying several ESG reporting and scoring methodologies such as the Refinitiv, FTSE Russel, BHI, and others, and extractive the most relevant ESG requirements and metrics that can be implemented and measured with the abilities of an SME.Due to the significant variations of the SMEs operations, the proposed framework is targeted primarily to SMEs in emerging markets where the economic development and a structured business environments can help such a novel approach in SMEs strategic management and leadership.

Haseena Alkatheeri, Evangelos Markopoulos, Hamdan Hamdan Al-qayed

Conference Proceedings

Traceability in Fast-Moving Consumer Goods Industries by Application of Blockchain Technology and Smart Contracts

Blockchain and generally decentralized technologies will be used quickly in all industrial fields. Fast-Moving Consumer Goods (FMCG) is one of the areas that has attracted a lot of attention from different perspectives, both in terms of marketing and in terms of contributing to environmental sustainability through the reduction of CO2 production. This study attempts to propose a suitable and near-to-optimal supply chain network for FMCG by using the critical advantages of blockchain technology, especially traceability. With the help of blockchain technology, information can be transferred to this network with greater transparency, traceability, and security. Moreover, the smart contract will provide the possibility of autonomous contract execution among the stakeholders in the supply chain. The smart contract eliminates payment delays, error risks, and the complexity of a traditional contract while maintaining the authenticity and credibility of supply chain interactions.

Mohammad Yaser Mofatteh, Kiran Basavaraju, Akshay Palani, Vamsi Sai Pidikiti, Manoj Kandahalli Raju, Omid Fatahi Valilai

Conference Proceedings

Motion Capture Body Tracking and Functional Safety in Dynamically Controlled Theatre Automation Systems

Live theatrical performance is an ever-evolving art form in which visionary theater makers are incorporating evolving technologies into performances to connect and engage modern audiences. Recent developments in theatrical motion control systems are enabling vibrant and adaptive control through dynamic automation. Traditional theatrical motion control systems use a set path motion profile to produce predictable movements of scenery and people through space and time. New dynamic control systems utilize an external generated set point parameter to specify the desired motion. This flexibility enables a DJ to control the movement of flown digital chandeliers above a dance floor with their regular beat control or for Alice to control her flown decent as she tumbles down the rabbit hole by changing the position of her arms. Putting the control of the equipment into the hands of the performers is a significant leap in evolution stage automation control.To accomplish the motion tracking of performers on stage, the research team developed a unique set-up of Microsoft Kinect sensors to monitor the stage environment. The skeletal models of up to four performers were captured and transmitted via an ethernet network to the video game engine. The main benefit of this tracking method is that it allowed for both traditionally costumed performers and regularly dressed audience members to be captured by the system. Most motion capture systems in entertainment require the use of custom body suits which can disenchant and distract audiences. Our system maintains the traditional relationship between costume and character while collecting the necessary interactivity data.The natively 3D nature of the video game environment is optimally suited to handle the interaction between performer and the digital environment. Using the skeletal tracking models from the sensor system, the video game engine allowed the performers to dynamically interactive with the stage environment. They could open doors, swat away birds, and flap their wings to fly away. The added benefit of the system was that it allowed members of youth young audiences to be called onto stage to further the narrative with their actions. The resulting system enables a new performance methodology with exciting new options for theatrical storytelling, educational training, and interactive entertainment. This evolution of control adds risks beyond those present in deterministic systems.Dynamic control of entertainment automation systems requires strong conformance to functional safety principles to mitigate the risks to affected personal and environments. Functional Safety is the mitigation of unacceptable injury risks through the implementation of one or more automatic protection functions (often called safety functions). In traditional theatre environments, safety functions have historically been limited to “Emergency Stop” functions which halt all motion when an operator presses “the big red button”. As systems become more complex and utilize dynamic control, theatrical automation control systems need to utilize a functional safety evaluation process to better protect persons and the environment for systematic and random failures in the systems. Industry experts develop best practice procedures to address safety concerns which are written into documents called standards.The presenter conducts research at the intersection of entertainment and engineering, has actively participated in the development of numerous American national standards with the Technical Standards Program of ESTA (Entertainment Services and Technology Association), and is a dual certified functional safety engineer (TÜV Rheinland and Underwriters Laboratories). This presentation will go through the functional safety considerations required to implement dynamic control per national and international standards using examples from realized performance projects led by the presenter.

Daniel Lisowski

Conference Proceedings

The Impact of Blockchain on Future Business Models within the Renewable Energy Sector

Blockchains, or distributed ledgers, are innovative information and communication technology (ICT) solutions that are emerging within various sectors and industries across the globe. This distributed ledger technology (DLT) is already widespread in certain sectors, mainly in the banking industry, often through corresponding banking, or syndicating and peer-to-peer (P2P) loans. Outstandingly, blockchain technology has the capability to enhance the transparency and authenticity of transactional processes throughout the whole supply chain. Another significant benefit that Blockchain technology provides, mainly coming from its transparent and decentralized nature, is the capability to decrease the information asymmetries among the collaborating partners. Through e.g. the digitalization of transactional mechanisms, decentralization of authority, Internet of Things (IoT) and asset management enabling as well as smart contracting, the improvement of the business's day-to-day operations is firmly forecasted. Importantly, the digitalization of the energy and other sectors will cause major alterations in current structures, and thus, it will require business model innovation. It is claimed that the decentralized nature of blockchain, mainly due to a reduction of middlemen could revolutionize current market structures and supply chains.Importantly, blockchain application is systematically growing across different industries, for instance in healthcare, voting systems, manufacturing, supply chain management, or luxury goods. It has also gained the attention of the energy industry, where digitalization is already visible in solutions such as smart meters and smart grids, electric e-mobility, vehicle-to-grid (V2G), energy cryptocurrencies and tokens, etc. This has resulted in the introduction of a novel concept of the Internet of Energy (IoE) in the academic literature. This literature analysis serves to determine the impact of blockchain on the imminent business models based on the renewable energy sector. The outcomes of this curiosity study provide numerous theoretical and managerial implications that can foster the widespread blockchain technology diffusion in global energy systems.

Oskar Juszczyk

Conference Proceedings

A Bi-Objective Approach for Determining Optimal Order Picking Planning Strategy with Ergonomic Load Evaluation

The main concern in many warehouse management systems is to arrange picking strategies for only time and cost considerations. However, the central operation in warehouse systems is order picking which involves highly physical load due to lifting and handling works. Therefore, load balance should be an integral part of order-picking planning strategies for a successful warehouse management system. This study focuses on determining order picking strategy by assigning orders to the pickers to minimize load imbalance and the total cost of order-picking operations. Ergonomic risk values of picking orders from the shelves are obtained by digital human modeling (DHM) via JACK software. The values for the ergonomic risk of the orders are then used to determine the load of each picker based on the assigned orders. The study is conducted in a warehouse working as a retailer of furniture and home decoration items. The main point of the study is to observe the ergonomic risks in terms of lower back compression force (LBCF) and integrate the results of ergonomic risks into a bi-objective mathematical model to determine an optimal order-picking strategy. The developed bi-objective model solves the order assignment with minimum picking cost and minimum imbalance ergonomic load among pickers. The study evaluates different order assignment strategies such as first come first serve (FCFS), highest ergonomic load order (HELO), lowest ergonomic load order (LELO), longest picking time order (LPTO), and shortest picking time order (SPTO). The results are used to construct a non-dominated set of solution alternatives in order to observe the impact of the order assignment strategy on the objective functions. The developed quantitative approach is used to evaluate the current strategy (FCFS) and compare it with the alternative strategies (HELO, LELO, LPTO, and SPTO). Finally, the suggestions for implementing the real-life numerical case are presented.

Rifat Gurcan Ozdemir

Conference Proceedings

From unsafe acts to system resilience - how emerging technologies in the O&G industry reach new safety frontiers

This study explores an historical evolution of the O&G industry, which has heavily relied on technological innovation to meet the operational challenges of its production chain. However, safety developments have sometimes failed to keep up with the technological evolution of this industry. In the beginning, its operations were marked by wild exploitation and numerous accidents, maintaining this scenario where there was the perpetuation of linear safety concepts, for increasingly complex workplaces. Traditional views of safety, such Safety-I, fails to capture the complexity and variability of real-world operations of the entire O&G production chain. To deal with complexity, evolved approaches of safety, such as Safety-II, recognizes that variability and trade-offs are inherent in complex sociotechnical systems and that people are an essential part of creating safety. Furthermore, Resilience Engineering is discussed, shifting the safety management from human error and accidents to system resilience and its own ability to cope with and adapt to disturbances. Embrace the complex reality of the work, grounded by evolved approaches of safety, provides a more comprehensive and effective way to assess, manage, and provide solutions in today's workplaces, ensuring an integration between productivity and safety.

Josue Franca, Erik Hollnagel

Conference Proceedings

QHS Methodology for Business Intelligence Model, Talent Management and KPI's in the Foreign Trade Supply Chain

The supply chain in foreign trade involves goods storage systems, with quality management systems in comprehensive service logistics, to ensure trust in the relationship with customers; the training of executives specialized in processes of opening accounts, review and storage of goods, as well as the follow-up to the suggestion of customer service become business intelligence strategies, in the face of the challenges of standardization of services where customer satisfaction becomes KPIs of Quality, Service, Cost and Delivery Time. The QHS Methodology is applied with the strategy of intervention and systemic integration of the different levels of authority and management of the learning curve to develop standards of good practices in the management of specialized talent in the different positions that make up the structure of the business axis of Warehouses and Logistics Services towards the integration of the corporate approach to operation.

Manuel Ignacio Garcia Rios Acero, Rodolfo Martinez Gutierrez, Jose Carlos Gonzalez Villa

Conference Proceedings

Proposition of an utilitarianism and fair objective function building method based on values and socio-economic consequences for data-driven decisions

In this short article, we propose a method to setup the objective function of machine learning binary classifier used in data driven decision. The goal is to take fair decisions aligned with an ethical value system and based on the long-term consequences of prediction errors for all stakeholders.The proposed method is based on human in the loop with an ethical committee to define the appropriate setup of the objective function, depending on the context of the decision. The setup parameters are of three categories: the fairness criteria, the ethical values and the weights associated to socio-economic long-term consequences of prediction errors.

Christian Goglin

Conference Proceedings

Design of an mHealth application for optimizing preoperative physical function

Limited physical reserve capacity in older people might be a risk factor for further functional decline and complications after surgery (Griffiths et al., 2014). A shift in cancer care in Sweden toward standardized and enhanced care processes, has led to that time between diagnosis and surgery has been shortened. Therefore, it has become important to focus on the effects of a short exercise program with high intensity and frequency. Recent qualitative studies have shown that patients with cancer need personalized support to perform preoperative exercises and that they prefer to do it at home or close to home (Beck et al., 2020). It is also important with a design that is tailored to the patient's needs, and goal setting, performance feedback, self-monitoring and reminders are all known facilitators for motivation and adherence to physical activity interventions (Michie et al., 2011).Development of the application: In a previous study, physiotherapists visited patients in their homes and supported them in conduction physical exercises during their preoperative phase. In the next step we developed a digital application consisting of, among other things, exercises, support and motivational features.The detailed features of the application were defined together with users during a co-creation process in workshops. Two workshops were conducted together with five patients. During the first workshop the participants discussed experiences from the previous intervention, factors they deemed relevant for adhering to the protocol and motivational aspects. During the second workshop the participants gave input on features and functionalities. One workshop was held together with five physiotherapists. In these workshops, experiences with the previous intervention, support needed for the patients and functionalities and interface for remote support were discussed. Further meetings and workshops were also conducted iteratively during the development phase.Content and interaction with the application: The specific aim of the application is to support the creation and tailoring of exercise programs with high intensity and frequency. The application consists of two parts, one used by the physiotherapists and one used by the patients. Physiotherapists are able to create individual exercise programs by selecting exercises from an exercise library, and then choosing settings for the exercises (e.g., numbers of sets and repetitions) based on a patient's needs and abilities. New types of exercises can be created by the physiotherapist and added to the library. The application allows the physiotherapist to monitor the patient's progress (based on data reported by the patient) and the exercise program can be adjusted if needed. The application also provides support for conveying a sense of presence and encouragement to the patient by allowing physiotherapist to write comments and to give the patient ”likes” on reported exercises, which will then be visible in the patient's part.The patient part of the application allows patients to see which exercises they are supposed to do each day, and to report to which extent the exercises have been completed. During reporting, the application will ask the patient to input data about how and when the exercise was performed (e.g., number of sets and reps, time of day, etc), and how the patient experienced the effort. All reported data are automatically gathered in a training diary section of the application, giving the patient access to the whole training history for later inspection. Any comments or likes sent by the physiotherapist also appears in the diary. The application includes different features for supporting and increasing the motivation to conduct the exercises. For example, rewards in the form of medals are given based on how well the patient follows the exercise program. Also, information about why this kind of training is important for improving the recovery after the surgery is provided in a theory section, to further strengthen the motivation to follow the exercise program. In the workshops patients had expressed the importance of this kind of information since it will be a reminder of how they can contribute to the best outcome as possible.ReferencesGriffiths R et al. Peri-operative care of the elderly 2014 Association of Anaesthetists of Great Britain and Ireland. Anaesthesia 2014;69:81-98. Beck A et al. Investigating the experiences, thoughts, and feelings underlying and influencing prehabilitation among cancer patients: a qualitative perspective on the what, when, where, who, and why. Disabil Rehabil. 2020 May 13:1-8.Michie S et al. A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: the CALO-RE taxonomy. Psychol Health 2011;26:1479-98.

Marie Sjölinder, Olov Ståhl, Elisabeth Rydwik, Simon Torikka

Conference Proceedings

Detection of abnormalities in imaged lung sounds based on deep learning

Despite the increase in respiratory diseases, the number of respiratory specialists is decreasing. The shortage of respiratory specialists has made the COVID-19 pandemic more serious. The pandemic has revealed the difficulty of controlling transmission, diagnosing, monitoring disease status, and responding to symptoms of infectious respiratory diseases. The global outbreak of the new virus infections has reminded us of the fragility of the conventional healthcare system.The most effective examination in the examination of respiratory disease is auscultation. However, features of abnormal sounds the disease brings are too obscure for doctors who are not specialists in respiratory to distinguish abnormal sounds from normal ones. Furthermore, due to aging, we would suffer from difficulty in hearing high-pitched sounds, which obliges even specialists often make mistakes in diagnosis. Diagnosis by auscultation depends on subjective judgment and the skill of the specialist. Today, when specialists are in short supply, information technology is expected to support even non-specialists to be able to diagnose respiratory diseases with high accuracy based on objective criteria. Utilizing the technologies, we should prepare for new pandemics.Specialists diagnose respiratory diseases by listening for peculiar sounds from the auscultatory sounds of patients who are suffering from lung disease. The study proposed in the paper transforms lung sounds collected by auscultation into a spectral image using the short-time Fourier transform. If auscultatory sounds contain disease-specific sounds, specific features should also appear in the spectral image of lung sounds. Deep learning techniques for analyzing images have made remarkable progress.Images can provide objective judgment criteria even to non-specialists. Analysis of images allows both specialists and non-specialists to diagnose objectively, unaffected by hearing loss due to aging. Doctors have accountability for patients on diseases. Images have comprehensive explanatory power for patients.Only a short-time Fourier transform of the spectral image of auscultatory sounds does not sufficiently highlight features specific to respiratory disease. The proposed method converts auscultatory sounds from the lung into a spectral image that emphasizes the frequency region of the sound recognizable to humans. The study refers to it as a mel-spectrogram, which facilitates finding disease features. The proposed method detects disease-specific features appearing in mel-spectrograms with Yolo, an object detection technique based on deep learning. The proposed method has discriminated auscultatory sounds obtained from actual patients with an accuracy of 0.7 in the F1-Score.Deep learning analysis of images provides evaluation criteria that are objective and independent of the skill of doctors. This study will enable non-specialists in respiratory medicine to examine whether persons are suffering from respiratory diseases, which would eliminate the shortage of specialists. This is diagnostic support for nonspecialists to address the explosion of patients due to respiratory infection outbreaks in the pandemic. It contributes to preventing the collapse of health care.

Shogo Matsumoto, Naoya Wakabayashi, Hiromitsu Shimakawa, Humiko Harada

Conference Proceedings

Analysis of Clothing Features Improving Self-Esteem through Measuring Stress According to Activity Contexts

In general, it is known that people's mental moods can be affected by changing their clothes.Though low self-esteem and mental disorders related to it have become a social problem in recent years, a simple way to change clothes may contribute to improving depressive symptoms. This study targets to improve self-esteem by changing clothing.There have already been a lot of studies to improve self-esteem. They include the use of social networking sites focusing on praise and the development of interactive technologies to improve young people's self-esteem. However, no method has been proposed to objectively judge whether people spend a daily life with themselves satisfied.Stress values are constantly changing. Their means and variances vary with activities. It implies there is a suitable stress value for each of them. We want to engage in some activities initiatively and are obliged to do others. The former has intrinsic stress while the latter an extrinsic. Even in the same activity, some people want to do it under high tension, while others want to do it in a relaxed manner. The paper introduces activity contexts classified with 2 dimensions related to stress. One dimension shows whether they are intrinsic or extrinsic, while the other presents whether the stress value is appropriate. The paper proposes an experimental method to discover the features of clothing that can improve self-esteem through the analysis of data collected from an activity tracker. Appropriate stress levels are considered to differ from person to person. The proposed method records stress values per subject and activity context, to calculate the appropriate stress value from the mean and variance of the stress values. The method regards items of clothing that bring long-lasting suitable stress values as ones that increase the self-esteem of the users and improve their performance. If the characteristics of clothing that improve self-esteem can be objectively identified from sensor data, a change of clothing into identified one can help reduce feelings of hopelessness and depression caused by low self-esteem. This method uses a multidimensional emotional scale of clothing to represent the characteristics of clothing. The experiment is carried out by collecting data using four questionnaires on the multiple affective states generated by dressing, the activity context, Rosenberg's self-esteem scale, and the apathy scale. The stress values, heart rate, and activity intensity are also collected from an activity tracker. The analysis is mainly based on the sensor data from the activity tracker. It reduces the effort on the subjects during the experiment.Sensor data on stress values from activity trackers are used as an indicator related to self-esteem. The stress state appropriate to activity status and clothes is predicted by a random forest model constructed from real data. As a result, it is found that people wearing clothing that makes them feel 'fulfilled' according to their assessment of self-esteem are more likely to be in an appropriate state of stress.The result is expected to play an effective means in alleviating symptoms of low self-esteem and depression.

Yumi Kirii, Humiko Harada, Hiromitsu Shimakawa

Conference Proceedings

Intelligent Moxibustion Instrument Based on Five-tone Therapy

In the background of great health, “health care” has become a trend. Against this background, this thesis aims to explore the research and development of intelligent moxibustion instrument design based on five-tone therapy.Method: Firstly, the function, application, and development of the five elements of music therapy are detailedly analyzed. Secondly, the function of moxibustion therapy and the current status of research on related products are discussed. Finally, the experimental application of the combination of five-tone therapy and moxibustion therapy is investigated, and the feasibility of the combination of the two therapies is analyzed in order to better meet the needs of users.Result: It is concluded that the combination of five-tone therapy and moxibustion therapy makes the treatment more effective, and the intelligent moxibustion instrument is feasible which basing on five-tone therapy. At the same time, the application of emerging technologies such as graphene and infrared heat therapy has good development prospects.Conclusion: With the development of the Internet, big data, and artificial intelligence, the integration of five-tone therapy into intelligent moxibustion products is a development trend. The combined treatment of the two therapies makes the operation convenient, comfortable, economical and safe. And it improves the shortcomings and deficiencies of traditional Chinese medicine treatment, and has wide clinical promotion and use value. In the future, efforts should be made to explore the function and scope of the application of Chinese medicine five-tone theory and traditional Chinese music in disease treatment and health care, and highlight the advantages of Chinese medicine five-tone therapy in this regard, so as to make it one of the important tools applicable to the regulation of subhealth. Meantime, moxibustion therapy should be combined with modern science and technology to further improve the efficiency of treatment, and make it environmentally friendly. The moxibustion instrument based on five-tone therapy will develop towards safe and multi-functional, Intelligent and personalized, user-centered and cultural-oriented. In this era of wisdom, Chinese medicine is slowly being combined with modern intelligence to find a connection between traditional and modern combinations.

Tianfeng Xu, Li Xu

Conference Proceedings

The Effects of Happy and Sad Dynamic Digital Art on Relieving Stress

Experiencing psychological stress due to the demands of modern life is common, but engaging with innovative digital art has the potential to alleviate this stress and provide a source of relaxation. Moreover, the interactive and dynamic nature of digital art offers diverse and distinctive experiences. The aim of this article is to determine if the process of transferring dynamic digital art images while playing happy and sad music can have an impact on an individual's stress level. For the experiment, two congruent audio-visual digital art videos were used as stimuli to assess their potential stress-relieving effects. A total of 24 participants were invited to participate and were divided into 3 groups. To induce a stress response in the participants, the Trier Social Stress Test was employed in the experiment. Following this, two separate groups were shown videos with different emotional tones, namely joy and sadness. The third group was the control group. The study assessed changes in participants' stress levels before and after the experiment using two tools: the State-Trait Anxiety Inventory (STAI) and Empatica E4. According to the study, both happy and sad videos were effective in reducing stress levels. The findings of this research could inform the development of digital art as a potential tool for stress management and emotional intervention.

Qiurui Wang, Jun Hu, Zhenyu Liu, Caihong He

Conference Proceedings

Diabetes Diagnosis Using Plantar Thermogram Based on DenseNet

In Japan, the number of diabetics is rapidly increasing due to changes in lifestyle and social environment. In the early stages of diabetes, patients have few subjective symptoms and the disease may be left untreated for a long period of time. However, if metabolic abnormalities in diabetes persist over a long period of time, the likelihood of developing complications increases. Therefore, it is important to complete the diagnosis of diabetes as early as possible. The use of plantar thermography images is expanding as one way to determine diabetes. However, conventional techniques have not been evaluated to take into account the difficulties of acquiring images in actual use environments, such as out-of-focus or low-resolution cameras. This evaluation is essential in a practical diabetes detector. In this method, we created various simulated images assuming realistic usage environments and devices, and evaluated their impact on diabetes determination accuracy using Recall, Precision, and F-measure. The diabetes determination method uses DenseNet201, a convolutional neural network specifically designed for image classification. As a model, training is performed using only the source image, either single-foot images or both-foot images. The dataset consists of plantar thermogram images of 122 diabetic and 45 non-diabetic patients published by Hernandez et al. Due to the small amount of training data, the training was augmented with image processing such as rotation and reduction. For the original image, the Recall and F-measure for the single-foot image were 96.4% and 87.1% for the original image, and 100.0% and 78.9% for both-foot images, respectively. Considering the F-measure, the classification with a single foot as input data is relatively more accurate. Furthermore, even at 87.5% reduction, there was no effect of reduced resolution on the accuracy of diabetes determination, indicating that focusing has a significant effect on the accuracy of plantar thermography images.

Ono Ayaka, Hironori Uchida, Yujie Li, Yoshihisa Nakatoh

Conference Proceedings

Comparison of maximum hip abductor torques from patient-specific multibody simulation models with isometric and isokinetic force measurements

Muscuolskeletal simulations have become an important tool to simulate biomechanical properties. However, adaption of the models to patients or test persons is relevant in order to obtain realistic results (e.g. hip joint moments or muscle forces). It is particularly important to correctly reproduce the patient-specific maximum isometric muscle forces of the individual musculotendinous structures. The purpose of this work is to determine the extent to which gluteal muscle adaptation has an impact on the maximum hip joint moment during hip abduction.Based on MRI images volumes of the gluteal muscles were determined. These were used to calculate the muscles' maximum isometric force via the physiological cross-sectional area and the specific muscle tension. Since the values of the specific tension differ greatly in literature, several models were created. The models were investigated regarding their maximum hip joint moment and compared, first, to a marker-based scaled generic model and, second, to isokinetic and isometric force measurements using a dynamometer.It was shown that both, the models and the muscle strength measurements, show a maximum in the lower area of hip abduction and decrease sharply with increasing abduction. The models with a lower specific tension were much closer to the measured maximum hip torques. Higher values for the specific tension and the model without patient-specific information on the musculature were above the strength measurements. However, all models are clearly above the measurements with increasing abduction.It can be concluded that the gluteal muscles should be simulated with rather lower values of the specific tension.

Christopher Fleischmann, Irina Leher, David Scherb, Marius Kollerer, Jörg Miehling, Sandro Wartzack, Stefan Sesselmann

Conference Proceedings

What are the key components and contributing factors for effective feedback system for training programs within a field of business administration?

Digital transformation creates opportunities for easy result delivery and system implementation that clearly identifies motivation and drawbacks for everyone involved. To create an effective and engaging feedback system that helps monitor training programs and can be applied in various organizations – lecturers from the Department of Management of BA School of Business and Finance tested a new feedback method system with the intention to find the key components and contributing factors that also measures the performance of the quality of an educational products, organization goals and performance of participants (students) and lecturers involved in the process. Online survey methods, e-mail marketing tools and classical statistical methods in combination with machine learning algorithms were used. The main purpose of the feedback collection was to ensure high-level engagement in response collection - that demonstrates problems and positive aspects for a product of educational programs in the field of business administration and finance studies which are both relevant for entrepreneurial studies and knowledge gaining within any organization.The article is based on statistical methods and analyses contributing factors that managed to collect more than two-thirds of quality feedback responses which is a higher rate than usual rate in organizations involved. Overall, 197 respondent answers were analysed from three educational institutions with similar educational programs, with the same two lecturers performing at 11 different study group courses. As a result – both way two (lecturer-participant) or even three-sided (lecturer-organization and organization-student) feedback system can be widely integrated and applied in both private and public sector educational and commercial institutions for a purpose – to monitor progress towards the goal reach whether it is the entrepreneurial intention, evaluation of skills, quality or a practical use of a knowledge gained.Conclusions involve aspects of – what makes an educational product valuable in the eyes of a customer and target audience. Also - why the feedback is crucial and how it benefits the overall monitoring of the goal reach for the organization. In combination with digital transformation opportunities – the system can be implemented in any organization for the process evaluation of in-house or outsourced training programs objectively.Keywords: Feedback system, Digital Transformation, Entrepreneurial education, Experiential learning, Goals, Entrepreneurial intention, Business administration

Eduards Aksjonenko, Airita Aksjonenko

Conference Proceedings

Training for Digital Forensics and Incident Response

The work of an digital forensics expert is far more extensive and varied today than it was just a few years ago. Especially after hacking attacks on organizations, experts in DFIR (Digital Forensics and Incident Response) come into play. In this paper, we present a learning platform that enables people to learn DFIR from scratch. To achieve this goal, the content of the learning platform was defined, evaluated and prepared with the help of experts from industry and government. For this purpose, expert interviews were conducted, which were subsequently evaluated. The results of these interviews were incorporated into initial scenarios that were implemented in individual modules on the learning platform Ilias, with a distinction being made between the basics and the main DFIR part. In the basic part, an introduction to IT forensics is offered, which is supplemented by further technical modules. This includes training in the use of the Linux operating system, which is frequently used in digital forensics, as well as the acquisition and analysis of RAM iand hard disk images. In the main part, the focus is to apply the learnings from the basic sections and to enhance them with incident related knowledge for DFIR projects, in which digital forensics experts gather and analyse evidence on various systems of the attacked organizations by searching and gathering so-called IoCs (Indicators of Compromise) from log files and other sources. Once the analysis part is complete, and all evidence has been collected, cleanup, recovery and restart of systems may take place, which is handled in the last section of the main training module.

Marko Schuba, Tim Höner, Sacha Hack

Conference Proceedings

Modularized Platform for an Embedded Systems Case Study: Concept and Design

This paper presents the concept and design of a hardware platform for an information technology workshop aimed at first-year electrical engineering students. The workshop provides students with their initial exposure to hardware-oriented programming and project management in a software engineering environment. The platform is centered around a Tiva C LaunchPad embedded on the control board of a remote-controlled vehicle. The hardware design of the remote vehicle is modularized into three boards: the control board, battery management board, and power management board. Additionally, a remote-control interface has been developed. The hardware platform leverages various capabilities of the Tiva C LaunchPad, including GPIO, ADC, PWM, and UART, although the I2C capabilities are not utilized in the workshop.Students work in groups of three to gain valuable project management experience. While each student is responsible for developing an individual hardware-related class, these classes are utilized for group tasks. To prevent complete group failure in case of one student's inability to finish their class, example classes are provided as usable libraries. The organization of responsibilities within the group is left to the students, and a project plan and Gantt chart timeline are mandatory.The hardware design adopts a modular structure that effectively separates main functions and power levels. The battery management board hosts the main fuse and an emergency shutdown relay, connected to a reed switch. It facilitates the connection between the batteries and the power management board. PWM signals from the control board on the power management board actuate two 12V brushless DC electric motors. Additional connections to the control board include a 5V power supply, a proportional measurement of the battery voltage, and control over the revolution speed of the drives. The control board, which houses the Tiva C LaunchPad, is also connected to ultrasonic sensors, an ESP8266-Module, and the power control board. The remote-control interface, featuring another Tiva C LaunchPad, facilitates human-machine interactions through an 8-bit display, a joystick, and navigation buttons. The remote control is powered by a 5V power bank.The software architecture also follows a modular approach, leveraging object-oriented programming principles. Seven different classes instantiate hardware-related functionalities. Additionally, four hardware-independent classes are employed. While all the functions of the remote-controlled vehicle are consolidated in one hardware-independent class, three are dedicated to remote control operation: Steering, responsible for reading joystick input and mapping it to commands; Display, enabling user output through an interactive menu; and Remote, serving as the central class that brings together low-level and other hardware-independent classes.In conclusion, this hardware platform offers first-year electrical engineering students a practical and comprehensive introduction to hardware-oriented programming and project management. The workshop provides students with hands-on exposure to industry-relevant technologies and a collaborative learning experience. The platform's integration of software and hardware components promotes a holistic understanding of systems engineering principles.

Vitus Lüntzel, Florian Schade, Martin Sommer, Eric Sax

Conference Proceedings

Facilitating Active Listening Using Video-Conferencing: Success Factors, Challenges and Implications for Soft-Skills Training

While active listening as a basic attitude and practice has been broadly applied and researched in face-to-face settings, its practice in video-conference mediated format is far less investigated. To fill this gap, this paper investigates online active listening and open sharing in an academic course on Communication and Teamwork. The research objective is to find out, how active listening can be acquired in online settings and which features are perceived as most valuable from the perspective of the participants and the facilitator. This paper takes a participatory research approach including a thematic analysis of students' reflections on active listening, their ePortfolios, and their self-evaluations. In a nutshell, the vast majority of students reported significant advances in active listening and open sharing, attributing them to features such as the constructive atmosphere in the meetings, the high relevance of the themes and online resources, and the active participation in break-out rooms, exercises, and group discourse. Nevertheless, participants tended to miss the rich real social contact with their peers! Implications for further research and practice on soft-skills training are derived.

Renate Motschnig

Conference Proceedings

An exact solution approach for prioritised and nonprioritized trains scheduling problem

We deal with a new decision problem, namely, the problem of scheduling prioritized trains and nonprioritised trains in a railway network. The difference between these two types of trains is the no-wait constraint, which should be satisfied by the prioritized trains. However, the nonprioritised trains may remain on the current section until a section on the routing becomes available. Our objective is to find a feasible scheduling that minimizes the total tardiness. It has been showed that this problem is NP−hard, and it can be considered as a job shop scheduling problem with blocking and no-wait constraints. A mathematical integer programming formulation is given, and numerical experiments are provided for evaluating the proposed approach. To the best of our knowledge, we are the first who deal this trains scheduling problem with total tardiness criterion, which is the main contribution in this paper.

Zineb Lissioued, Samia Ourari

Conference Proceedings

QHS Methodology for Business Intelligence with CRM in Warehouse Services and Foreign Trade Logistics

Business-oriented companies in the foreign trade supply chain that involve the phase of Merchandise Warehouses and Logistics Services as an added value; They generate, due to their highly specialized nature of the context of global trade, security control implications through risk control systems and integral security of all the processes of the services of the value chain. For the purposes of this study, a research proposal is made through an eclectic methodological proposal combining the QHS methodology and elements of the Business Intelligence methodology, to analyze the information variables of various sources of information of a company; With a multidimensionality approach to find correlation of success in the achievement of operational performance indicators, productivity, and customer satisfaction levels, under a systemic approach.

Jorge Vicente Villa Garcia, Rodolfo Martinez Gutierrez, Rodolfo Martinez Solis, Grecia Arisbeth Hernandez Castañeda

Conference Proceedings

Estimation of Gait Conditions Using Acceleration and Angular Velocity Sensors

The worldwide epidemic of the Corona Virus Disease 2019 is forcing many people to stay indoors, indirectly causing more people to gain weight. As a result, people's awareness of the movement grew. The most popular form of simple exercise is walking, and many people use wearable devices to record their movements. Existing wearable devices do not take into account the wearer's walking speed or the road condition, resulting in poor calorie counting accuracy. In this study, we use acceleration and angular rate sensors for gait state estimation. We create a device using an Arduino Uno and a 9-axis sensor module and experimented with the device attached to the waist, thigh, and ankle of the subject. Based on the features obtained here, the objective is to minimize the computational process in the system. We focus on the "x-axis," "y-axis," and "z-axis" of each sensor, and verify what characteristics were observed in various walking conditions. Experiments were conducted on three patterns of "walking," "fast walking," and "running" in three road conditions of "level ground," "uphill," and "downhill," and the feature values were compared. The experiments reveal that the gait state is mainly represented by the y-acceleration and x-angular velocity. Experimental results also confirm the validity and reliability of the proposed method.

Shinji Hirano, Hironori Uchida, Yoshihisa Nakatoh, Yujie Li

Conference Proceedings

QHS Methodology for Management and Finance Models in Foreign Trade Supply Chain Business

In the business world of the foreign trade supply chain, models of administration, finance and budgeting systems are strategies to ensure mechanisms of the administrative process; Planning, organization, control and direction are factors that must be monitored with performance indicators, human talent management is a key pillar of success. The risks involved in financial management and budgets are sensitive services, which require attention with actions of prior inspections of the merchandise to ensure that the items that are imported agree with the invoice and request. Given the nature of operational complexity, the QHS Methodology is applied with a systemic integration approach of good practices from all sectors involved in combining strategies to strengthen the administration of operational and managerial knowledge management in an organization.

Angel Agustin Mendoza Marmolejo, Rodolfo Martinez Gutierrez, Rodrigo Gonzalez Villa

Conference Proceedings

How the Ones in Need Solve Financial Problems in Times of Crisis? The Implication for Government Support Programs

After the COVID-19 pandemic ended the war between Ukraine and Russia resulted in further price increases and a decrease in the quality of living of many Europeans. Many groups of citizens must be able to survive on meagre resources — despite being located thousands of kilometers from the war-zone. The two most affected groups are senior citizens and single parents who oftentimes do not have sufficient savings. The government provides financial support (e.g. housing allowance) to those in need after their successfully filling out application forms and proving their crisis situations. These are reviewed for eligibility by the Labor Employment Office. There are several problems inherent in this bureaucratic procedure. Among these are: complex jurisdictional language, external reference requirements, and lengthy forms. All these force — willingly or unwillingly — the individuals to either avoid or fail the application process. In order to investigate statistics aspects of the avoidance aspect of this state of affairs, we collected data from Czech citizens via an online questionnaire at the end of 2022. The questions were specifically aimed at understanding the potential applicants' mechanisms of dealing with their financial crises. We queried respondents' ratings to nine queries about their financial strategies (taking out a loan, use of savings, etc.) and two about their income. All responses were categorical variables.We constructed a contingency matrix and performed a correspondence analysis. This method shows associations, replacing the often-times used erroneous approach of looking for correlations (which do not exist for categorical variables). Furthermore, we can find an a priori unknown number of associations and the fraction of statistical noise in the contingency matrix. We use a clustering algorithm ('spectral' clustering) to find the number of possible associations and construction of concave hulls to aid in analyzing these.We find: (a) the associations explain 91.9% of the square of the Frobenius norm of the contingency matrix; (b) nine queries associate (in four clusters) for certain response categories; (c) two queries do not associate (one is independent of response categories); and (d) one query associates with only one response query.The implications of these associations are as follows: (a) all respondents intend to decrease their outlays; (b) those who earn between 20 and 30 thousand CZK are hesitant to ask for government support; (c) the participants would rather not borrow money from family, bank, nor sell their valuables; (d) the rejection of possible non-bank loans associates with the rejection of selling a property; (e) reliance on savings does not associate with any other query, nor does total household income — nor does finding an extra job. Application of our findings are twofold. First, we see that the strongest statistical signal does not provide support for an association between personal or family income and the proffered solution of government support. Second, the associations we found indicate a crucial and ominous rejection of the Czech government's strategy and expectations. Specifically, we suggest a remedial strategy of matching the application process with the linguistic accessibility of low-income citizens.

Hermann Prossinger, Nikola Geciova, Miroslav Horvath, Jakub Binter, Eliska Cempirkova

Conference Proceedings

Mahalanobis Distance-Pattern Approach to Body Coordination in Motion

Today, our world changes drastically. Yesterday, however, changes were smooth, so we could differentiate and predict the future. Today, changes become sharp. So,we cannot predict the future. Yeseterday, our world was closed with boudnary , but todayour world becomes open. yesterday, materials or products were hard so we could apply mathemacial approaches and control them/. Today, materials are getting softer and softer with the progress of material engineering. When things were hard, we could understand what it is and how we should handle it with our eyes alone. But today, we need to interact with them directly. To cope with such drastically changing real world, we need to coordinate all parts, Our current world is the Industrial society, which is based on quantitative and reasonalble evaluation/ In other words, it is based on Euclidean approach which is interval scale and cardinal based. But human needs shifts from material to mental or from product to emotion. And Maslow pointed out "Self-Actuatlization" is our final need and Deci and Ryan proposed Self-Determination Theory and we get the highest satisfaction and feeling of achievement, when we do the job we wish to accomplish and in our own way. They also pointed out this is very important for our growth. The Industrial Society is getting close to its end and now we need to design and develop the next Society. In a word, our world is changing quicklly to the world of "Self". How we can enjoy our life in our own way becomes cruciallly important. As materials are getting softer and softer, we need to develop a tool to deal with physically soft world. The world focusing on musculoskeltel system and processing externally obaservable movement is going out.We need to consider how our internal body parts such as muslces move to respond to the radicallly changing Real World. In short, we need to shift from Digital to Analog. We need AnalogIntelligence, which is the next AI. To achieve such a goal, our instinct plays a very important role. Therefore, we developed a Mahalanobis-Distance approach to support our instinct in orderfor it to fully coordinate our Motor (Internal Movement) movents.

Shuichi Fukuda

Conference Proceedings

Occupational psychosocial risks identification and assessment at Labour Offices in the Czech Republic

Psychosocial risks at work can be defined as a set of risks resulting from the employee's interaction with the work environment, the nature and organization of work and interpersonal relationships both inside and outside the workplace. Data collection was provided through an online questionnaire survey in December 2021 in 5 selected Labour Offices in the Czech Republic. A special questionnaire was prepared and tailored to the needs of workers exposed to demanding communication with clients. This questionnaire survey was done after the pilot study to ensure the adequacy of the questions, comprehensiveness of the contents, and clearness of instructions. The questionnaire was divided into the mandatory part with Demographic data (7 questions), Work with the client (10 questions) and Resilience (10 questions). Optional areas of the questionnaire covered Communication with superior and team (9 questions), Nature of the work (8 questions), Work organization (9 questions), Job evaluation (5 questions), and Job change, digitalization and unexpected crises (4 questions). A total number of 1168 questionnaires were included for further analysis. The study group consisted of 93% women and 7% men. The biggest age group of respondents was between 50 to 64 years (33%). The results showed the highest satisfaction of employees in the area of communication at the workplace, whereas employees were most dissatisfied with work changes. For 58% of respondents, communication with the work team and superior impacted their job satisfaction. If there was a conflict or escalation of communication when dealing with a client at the counter at the Labour Office, only 1.7% of respondents stated that they had equipment at the workplace place to signalize and monitor the potentially dangerous clients. Our results demonstrated several very problematic areas of psychosocial risks at the workplaces of Labour Offices.Acknowledgements:This result was financially supported by institutional support for the long-term conceptual development of the research organization for the years 2018–2022 and it is a part of the research task 10-S4-2021-VÚBP “Possibilities for intervention measures for employees exposed to demanding communication with clients in public administration with a focus on employment offices”, solved by the Occupational Safety Research Institute in cooperation with the National Institute of Public Health in the years 2021–2023.This research was supported by the Ministry of Health of the Czech Republic - RVO(National Institute of Public Health - NIPH, 75010330)

Vladimira Lipsova, Karolina Mrazova, Kateřina Bátrlová, Tomas Navratil, Martin Stepanek, Sergey Zacharov

Conference Proceedings

Industry 4.0 Technologies Implementation in Automotive Sector

Nowadays, the topic of technology implementation is gaining more importance. Industry 4.0 technologies can bring significant benefits to companies, especially improvements to their competitive position as well as to their value chains and business processes. New challenges and opportunities are arising nowadays, especially with the transition to the Fourth Industrial Revolution, known as Industry 4.0. Emerging and disruptive technologies are at the center of the transformation to Industry 4.0. In this context, the automotive sector, which is often considered a leader in innovation, plays a crucial role. The paper presents the results of research that was aimed at examining the current attitude of selected companies in the automotive sector and their perception of the necessity of implementing Industry 4.0 technologies. To gather the data, structural interviews were conducted with 22 companies in the automotive sector, which were mostly large-sized companies with international operations. The paper also discusses the current trends and challenges connected to Industry 4.0 in the automotive sector.

David Smolka, Zuzana Papulova

Conference Proceedings

Innovative Personal Protective Equipment: Advantages and Disadvantages of Applying Artificial Intelligence

Personal Protective Equipment (PPE) plays a crucial role in ensuring the safety and health of workers in various industrial areas. With the advent of Artificial Intelligence (AI), new opportunities for improving the effectiveness and efficiency of PPE have arisen. In the proposed paper, will be examined the potential applications of AI in PPE, and will be evaluated the advantages and disadvantages of applying AI to PPE.In the introductory section, an overview of AI and its potential applications in PPE will be provided. Than we will examine examples of how AI has been industrialized in the production of PPE, including the use of sensors and advanced algorithms for monitoring worker health and safety. We argue that AI can be a powerful tool for improving the performance of PPE and reducing the occupational risks such as work-related injuries and illnesses.In the central section of the paper, will be evaluated the advantages and disadvantages of applying AI to PPE. We will discuss the benefits of using AI to enhance the precision and accuracy of PPE, as well as its potential to reduce the workload and costs associated with traditional PPE. However, will be also highlighted some of the potential drawbacks of AI in PPE, such as the risk of relying too heavily on technology, neglecting other important aspects of worker safety and also ethic implications.In the last section of the paper, we will provide solutions for overcoming the limitations of AI in PPE. We argue that a balanced approach is needed, one that combines the strengths of AI with other approaches to worker safety, considering also ethic aspects. We suggest that future research should focus on developing hybrid systems that integrate AI with other technologies, such as wearables and augmented reality, to create more effective and user-friendly PPE.In summary, the paper proposed wants to provide a comprehensive analysis of the potential benefits and drawbacks of applying AI to PPE. We argue that AI has the potential to revolutionize the field of worker safety, but caution that a balanced approach is needed to ensure that the benefits of AI are realized without compromising other important aspects of workers' health and safety.

Alessandro Ledda, Davide Giordani, Maria Rosaria Fizzano

Conference Proceedings

Industry 4.0 Adoption – A Case of Manufacturing Companies

The paper discusses the topic of Industry 4.0 as one of the key trends that are shaping the current business environment as well as the whole society. Industry 4.0 is often represented by the latest technical innovations and new technologies. Many experts and researchers have already pointed out the significant benefits of Industry 4.0 adoption in terms of lower costs, improved efficiencies, increased yield, mass customization, and most importantly, new revenue and business models. However, the level of adoption of Industry 4.0 can vary across industries and companies. There are still differences in the companies' approaches to adapting to the technologies and technological progress connected with Industry 4.0. In our research, we focused on manufacturing companies from various industries and studied their perceptions of the current state of Industry 4.0 in respective industries and its effect on competitiveness. We used structural interviews to gather the data on the sample of 47 companies.

David Smolka, Zuzana Papulova

Conference Proceedings

Overview of intervention measures for the prevention of psychosocial risks at workplaces of Labour Offices in the Czech Republic

In December 2021, an online questionnaire survey was conducted at 5 selected branches of the Labor Office in the Czech Republic focused on the analysis of psychosocial risks at work. Based on the findings from this survey, the problematic areas were defined and specific intervention measures were applied based on their evaluation. These measures started in September 2022. They were focused on two levels: building psychological resistance (resilience) provided in the form of online seminars: "Supporting positive coping mechanisms and increasing resistance to stress", "Sleep hygiene", "Active psycho hygiene and coping with demanding clients" and special seminar for managers "Psychological support and basic intervention for your subordinates". From December 2022 to March 2023, group and individual psychotherapy were conducted for a much smaller group of employees under the guidance of a psychotherapist.

Vladimira Lipsova, Karolina Mrazova, Kateřina Bátrlová, Martin Stepanek, Tomas Navratil, Sergey Zacharov

Conference Proceedings

Methodologies For Determining Tariffs For Intermodal Cargo Transportation

The article presents an analysis of tariffs for international freight traffic along the route Nur-Sultan station (Republic of Kazakhstan) - Mazare-Sharif station (Republic of Afghanistan). The freight charge is determined according to three existing methods for determining the freight charge: based on the Rail-Atlas and Rail-Tarif software package; Uniform Transit Tariff (UTT); International Transit Tariff (ITT). Calculations convincingly show the lowest tariffs for freight transportation, their availability for a wide range of railway customers. Moreover, the advantages of low-price tariffs are given in a tabular format, which creates convenience for users of railway services.

Zhaken Kuanyshbayev

Conference Proceedings

Exploring the Role of City Environment in Meeting Emotional Needs of Individuals

The influence of city environments on individuals' emotional states and overall welfare is considerable. This research aims to examine the correlation between city environments, dynamic requirements, and the experience of city ambience. Researchers can contribute to developing emotionally supportive and sustainable cities by investigating how city environments can meet or hinder individuals' emotional needs. The central focus of this study pathway revolves around comprehending the emotional needs within city contexts. The emotional needs that individuals strive to fulfil within city environments and examine the variations in these needs among different demographic categories and cultural contexts. city planners and designers can enhance their ability to address the diverse emotional experiences of city residents by acknowledging and understanding these emotional needs. An integral aspect of this field of study pertains to the impact of city design on individuals' emotional well-being. Researchers can analyze the impact of the physical characteristics of city environments, including their layout, architecture, and amenities, on individuals' emotional experiences. This entails examining design elements that foster positive emotions and those that may elicit negative emotions or emotional strain. The comprehension of the impact of city design on emotional well-being enables city planners to construct environments that foster positive feelings and mitigate negative emotional states. The influence of social connections on the perception of city environments is significant. The impact of social relationships and community engagement on individuals' emotional experiences within city environments is examined. Researchers can inform the establishment of inclusive and cohesive city communities by investigating factors contributing to a sense of belonging, connectivity, and social support. The examination of social networks and engagement holds the potential for facilitating the cultivation of positive city emotions and fostering enhanced well-being within individuals.Another crucial area of study pertains to the impact of natural elements on the city environment. The impact of integrating natural elements, such as green spaces, water features, and natural lighting, on enhancing individuals' mental well-being within city environments is investigated. Gaining insight into the influence of nature on emotional experiences can facilitate the integration of natural elements into city designs by city designers, thereby enhancing positive emotions, reducing stress levels, and fostering overall well-being. Furthermore, an analysis will be conducted to explore the impact of technology on the emotional state of city environments. This research domain explores the effects of digital technology and smart city solutions on individuals' emotional encounters within city environments. The objective is to ascertain the potential of technology in enhancing positive emotions, providing emotional support, and meeting emotional needs within city environments. This knowledge can potentially contribute to advancing technological interventions to improve city well-being and quality of life.This research domain proposes utilising a mixed-method methodology for collecting both quantitative and qualitative data pertaining to individuals' emotional encounters within city environments. This approach encompasses the use of surveys, interviews, observational studies, as well as innovative data collection instruments. The findings of this study can be utilised by city planners, architects, legislators, and city developers to create emotionally supportive, livable, and sustainable cities. This research result provides a scholarly contribution to the field of city design and development by examining the relationship between city environments, emotional requirements, and the overall emotional well-being of individuals residing in cities. The comprehension and resolution of individuals' emotional requirements within city environments can potentially foster cities that are more inclusive, vibrant, and emotionally fulfilling for all residents.

Amic Ho, Ruth Chau

Conference Proceedings

The Role of Visual Aesthetics in Emotional Response

This study aims to examine the impact of visual aesthetics on emotional response in design and art as well as the potential for computer technology to optimise aesthetic design choices for optimum emotional impact. Through an examination of prior research and investigation into the potential for computer-generated designs to optimise emotional impact, the paper emphasises the repercussions of these findings beyond the design industry, including ethical concerns. The study demonstrates that by analysing vast amounts of data and identifying patterns in emotional responses, artificial intelligence systems can generate designs optimised for specific emotional outcomes. By leveraging computer technology’s capacity to optimise aesthetic ratings for emotional impact, designers and researchers may be able to create more engaging, memorable, and effective designs. However, one must consider ethical concerns, such as prejudice, impartiality, data privacy, and security. To ensure the responsible and beneficial use of computer technology in visual design, the study identifies five key areas for future research: context, cultural and contextual aspects, personalization, ethical frameworks and norms for computer-generated designs, and real-world outcomes (such as sales and customer engagement). This study aims to shed light on the significance of visual aesthetics in emotional response as well as the potential for computer technology to revolutionise design decision-making to optimise emotional impact.

Amic Ho

Conference Proceedings

Enhancing User Experience: Exploring the Interactions and Visualisation of Data Through Bullet Points and Typographic Design

This study aims to examine the impact of bullet points on data comprehension and establish a visual hierarchy. Additionally, it includes a comprehensive analysis of prior research on the effectiveness of bullet points in the context of data visualisation. The importance of typography in establishing a visual hierarchy is underscored, alongside an analysis of different typographic styles and their impact on the emotional aspects of user experience. This study examines case studies that illustrate the successful application of typographic design in data visualisation, specifically focusing on using bullet points. Enhancing user engagement through bullet points, exploring interactive elements for visualising data, and examining the effects of different typographic approaches are delved. This study comprehensively examines best practices and practical recommendations for developing emotionally appealing data visualisation bullet points. Moreover, the utilisation of typographic design to convey data insights by employing principles of data-driven typography is examined. This study examines the application of data-driven typography in obtaining intricate information through bullet points and its impact on emotional responses and user comprehension.

Amic Ho

Conference Proceedings