Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications

AHFE International

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

Human Interaction and Emerging Technologies (IHIET-AI 2023): Artificial Intelligence and Future Applications

book-cover

Editors: Tareq Ahram, Redha Taiar

Topics: Artificial Intelligence & Computing, Human Systems Interaction

Publication Date: 2023

ISBN: 978-1-958651-46-9

DOI: 10.54941/ahfe1002922

Articles

HCD methodologies and simulation for visual rehabilitator’s education in oMERO project

The work presented originates in the context of designing for individuals with visual impairment, in the specific target refers to children from two to seven years of age. The study was conducted with the contribution of the UniGe DAD (Department of Archite- cture and Design) research group as part of the oMERO project, an Erasmus+ project funded by the European Community (2020–2023), with the aim of creating a curricu- lum for training the profession of visual rehabilitator for children. The article illustrates a case study carried out using the simulation technique at the University of Genoa’s Center for Simulation and Advanced Training. The approach intended to be applied to this course is innovative, involving the immersive and experiential participation of students and the adoption of the most advanced training technologies in the field of simulation. Expert designers, physicians, ophthalmologists, psychologists and visual rehabilitators were involved to proceed with the implementation of the experiment, resulting in a multidisciplinary and interdisciplinary study. The ultimate goal is to pro- vide students with standardized criteria for assessing and appropriately intervening in the living spaces of the child with visual impairment. The preliminary phase involved the simulation of a home environment, specifically the setup of a child’s bedroom. The SimAv setup is based on a film set. Equipped with the most advanced techno- logy, it allows the recording and creation of digital content and the configuration of environments, such as the arrangement and number of furnishings and the variation of ambient brightness, fundamental elements to ensure the autonomy of simple and basic actions, provided in the educational modules. Specifically, the bedroom was set up with standard elements, recreating a real context. The front door and a win- dow were also simulated in the room. The placement of the various elements in the room was designed according to the needs of visually impaired and blind children, and the experimentation was divided into two moments characterized by two set- ups. The first set-up involved dazzling lighting and the selection of objects that were difficult to distinguish, then the environment was modified through the use of contra- sting elements, visual markers, and appropriate lighting through dimmable lights. The experiment was carried out by students from different European countries who parti- cipated in the two courses wearing glasses to simulate visual impairment. In addition, students were asked to complete certain tasks during the experiment. At the end of each route, the participants filled out an accessibility evaluation form through which they defined the level of difficulty of the tasks and made suggestions to improve the existing layout in terms of placement or choice of furniture, materials, lighting, color contrasts, pathways and tactility. Through this experimentation, the data collected allowed the research team to understand the possible modifications to be made to the environment and to identify the elements that could make the experiment reproducible in different home settings in order to define a protocol for adapting the spaces to the needs of the target audience.

Isabella Nevoso, Niccolò Casiddu, Annapaola Vacanti, Claudia Porfirione, Isabel Leggiero, Francesco Burlando

Conference Proceedings

Designing a Digital Crown-Mapping Application for Pedestrian and Cyclists

Walking and cycling as active mobility have often been forgotten in research and planning in sub-Saharan Africa and only in recent years national and local authorities as well as international agencies are putting more effort on this topic. There are efforts to develop walking and cycling policies and infrastructure in cities like Nairobi and Kampala. However, these new infrastructure projects are minimal in scope, have design inadequacies that make them unusable or unattractive, are not wide enough to meet walking space standards, and are in places that do not serve the majority of the people who need to access them. To further promote active mobility in sub-Saharan Africa while building on existing activities, combined efforts of applied research and continuing education are required to better understand walking and cycling needs in an African Context. The promotion of active mobility can build on existing applied research activities in sub- Saharan Africa as well as transferable research activities in Germany, prior introduced by Hausmann et al. 2017. Nevertheless, there is still a need to better capture the requirements of the pedestrians and cyclists and to illustrate their needs.

Waldemar Titov, Carl Gerlach, Thomas Schlegel

Conference Proceedings

On the way to hybrid intelligence: influence of the human-system interaction rate on the human cognitive performance

IntroductionHybrid job and learning create new opportunities and set new requirements to control a human-machine interaction. It is important to keep in mind that modern and future participants of these activi-ties can include the artificial intellect (AI-actor) as well. One of the critical features of their interaction could be the rate of the information exchange, because an AI-actor can accept and produce tasks in a quite stable rate, in contrast with a human-actor whose performance quality can very in time. As a result, their interaction needs to be adjusted in many cases from viewpoint of complexity and rate. It is supposed that the process of the information task flow should correspond an individual or moderate rate, in the best case. But according to our preliminary data (Burov, 1990, 1996), the moderate rate (even individually adapted) of perceptual and cognitive task flow was accompanied by a higher physiological strain than slow and fast ones. Because the cognitive component of the mental work becomes more and more significant both for a job and for a teaching/learning, it is useful for adaptive systems’ design to clarify if the free (“auto”) and moderate rates have the same and/or similar influence on a human performance quality (reliability and speed) and health consequences. GoalTo carry out the comparison analysis of the speed and reliability of cognitive activity by subjects performing computer tasks at a free and fixed pace, considering the physiological "cost" of such activities. Discussion of ResultsThe methodological basis of our research are models and methods for assessment a human ability to cognitive work using the computer system for psychophysiological research developed by authors. The survey included cognitive test task performance, blood pressure and heart rate before and after the test performance, as well as electropuncture diagnostics (EPD) after Nakatani (including 3 stress-points) for each subject. 47 subjects participated in experiments, 4 times per month (three times performing tests in the fix pace, one time in the free pace, each test session in a week). The duration of each test session was 3 continuous hours. Variation of the cognitive test task performance (accuracy and reliability) over the research period were studied and compared with changes of psychological and physiological indices, namely heart rate, blood pressure, vegetative stress index after Bayevsky as well as stress indices after Nakatani. It has been revealed strong increase of the stress by physiological and EPD indices and deterioration in activity (task performance time, reliability) in test sessions with fixed pace. Individual and inter-dividual variations are considered.Significance of the Proposed PresentationThe results can be applied to optimize a human and digital system interaction accounting a hu-man cognitive and psychophysiological limitations in interaction pace. The optimization goal can be to adjust their interaction pace to achieve maximal general performance in short- and long-term per-spective.

Oleksandr Burov, Evgeniy Lavrov, Svitlana Lytvynova, Olha Pinchuk, Kateryna Horska, Oleksii Tkachenko, Natalia Kovalenko, Yana Chybiriak

Conference Proceedings

Human-Centered Design of Voice Communications: Gender Aspects

Perceiving the transmitted speech is a task that puts certain amount of cognitive load on the human brain. The degree of this load depends on several factors, e.g., the loudness of the perceived speech, the type and intensity of background noise, the quality and accent of the speech, familiarity with the topic of the message, etc. This load also varies between the native and non-native language (of the listener). Different levels of such load are manifested in longer duration workloads (e.g., during a work shift) by different levels of overall fatigue, which affects the decrease in the worker's action or decision error rate when performing other concurrent tasks (the so-called parallel-task paradigm). For technologies used in speech transmission or synthesis, e.g., in telecommunications, radio communications, and machine to human communications, the above implies a strong need to optimize the coding of human (or synthetic) voice to minimize listening effort during communication. Listening effort (LE) can be assessed by subjective tests following, e.g., ITU-T P.800 Recommendation, along with listening quality (LQ) as specified in P.800. A natural (but nowhere explicitely mentioned) requirement is that male and female voices are transferred with similar LQ and LE parameters; in other words, the transmission technology, including coding algorithms, frequency filters, or sampling rates, should not privilege one gender over the other to maintain similar working conditions and opportunities for all.The subjective test laboratory has performed gender analysis for all subjective test projects since 2018 to see how (mis)balanced the transmission quality between male and female speakers is. The identified misbalance can affect many professionals that deploy distant voice communication in their daily duties – think of female airport approach control dispatchers or other professionals (policewomen) who are principally handicapped by technological aspects of their job - worse voice transmission quality means higher listening effort is needed and may lead to consequent (subconscious) discomfort of their communication partners, or even intelligibility issues. Of course, this fact is not surprising for narrow-band or even old analog AM transmissions (as still used in AIRCOM). It can only be used as an argument to upgrade communication means to a suitable digital format. Unfortunately, some contemporary wide-band or even full-band digital communications also show statistically significant differences between quality of transferred male and female voices. The detailed results will be presented, including interesting systematic language dependencies (English, German, Mandarin).In the conclusions, suggestions for future codec designs considering the human-centric gender-balanced requirements are proposed. These include the minimum frequency response of the future coders, granularity of the perceptual frequency scaling, etc. Also, suggestions for gender neutrality of original (studio quality) recordings used to prepare the speech samples for the subjective tests are included.

Jan Holub, Yann Kowalczuk

Conference Proceedings

Framework of Future Industrial Worker Characteristics

The ways of working are changing in the manufacturing industry due to new technologies and the merging of physical and virtual environments (e.g., Industry 4.0 [1], Metaverse [2]). Already, work tasks are changing from physical and routine tasks towards intellectual and social activities which often include the use of ICT tools [3]. The pandemic has changed attitudes and ways of working towards hybrid arrangements and therefore, expectations related to flexibility in work may become more pertinent also for manufacturing workers [4]. Novel technologies are being developed to support the industrial worker in the future [5], which can be called augmentation or empowerment of workers [6-8].The World Manufacturing Forum has identified the top ten skills that will be needed in future manufacturing work [9]. In our study, we wanted to add understanding of the skills and characteristics needed in future industrial work and present the results in a format that would support designers of technological tools to consider the perspective of future workers. Our goal was to create a framework of worker characteristics that could guide the design of technological tools to assist workers in work tasks requiring new skills and characteristics. To understand the transformation of work and to create a framework, we conducted a literature review and 10 expert interviews, focusing on the ways emerging technologies are expected to change the nature of industrial work. Based on the results, a framework of future industrial worker characteristics (FIW) was created. The applicability of the framework was tested by applying it in a European research project that develops software solutions for the context of modern, flexible, and data-rich manufacturing. Altogether, 19 novel software solutions that are being developed to support industrial work were mapped using the characteristics of the framework. The mapping experiment provided understanding of the relevance of the worker characteristics and the ways to support them in practice.According to the FIW framework, future industrial work will require smarter operations, which emphasizes worker capabilities in terms of mastering complexity, solving problems, making proactive decisions, and considering sustainability. Transforming work requires resilience that can be strengthened by capabilities such as creativity, the ability to lead oneself, flexibility, and continuous learning. Being interactive will be a vital part of work and can be fostered by communication, collaboration, supporting inclusiveness and interculturality, as well as sharing a safety-oriented mindset and work practices. In addition, health and well-being will have a central role in the future work. A healthy worker can be characterized as feeling motivated, balanced, capable, and focused.The FIW framework can be used by designers and industrial companies to guide the design and acquirement of novel technology solutions to support the characteristics of future industrial work, and in general, to increase understanding on transformation of industrial work from the perspective of worker skills and characteristics. In the future, it would be good to apply the framework in other research cases and industrial contexts to find out the possible development needs and ways to embed the framework in the design or evaluation processes.REFERENCES[1]Henning Kagermann, Wolfgang Wahlster and Johannes Helbig. 2013. Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0: securing the future of German manufacturing industry. 82.[2]Sang-Min Park and Young-Gab Kim. 2022. A Metaverse: taxonomy, components, applications, and open challenges. IEEE Access [3]Eurofound. 2018. Wage and task profiles of employment in Europe in 2030. [4]Gartner 2023. 9 Future of Work Trends for 2023. Available: gartner.com/en/articles/9-future-of-work-trends-for-2023 [Accessed Feb 15, 2023].[5]David Romero, Johan Stahre, Thorsten Wuest, Ovidiu Noran, Peter Bernus, Åsa Fast-Berglund and Dominic Gorecky. 2016. Towards an operator 4.0 typology: A human-centric perspective on the fourth industrial revolution technologies. CIE 2016: 46th International Conferences on Computers and Industrial Engineering. [6]Eija Kaasinen, Franziska Schmalfuß, Cemalettin Özturk, Susanna Aromaa, Menouer Boubekeur, Juhani Heilala, Päivi Heikkilä, Timo Kuula, Marja Liinasuo and Sebastian Mach. 2020. Empowering and engaging industrial workers with Operator 4.0 solutions. Computers & Industrial Engineering 139, 105678.[7]Roope Raisamo, Ismo Rakkolainen, Päivi Majaranta, Katri Salminen, Jussi Rantala and Ahmed Farooq. 2019. Human augmentation: Past, present and future. International Journal of Human-Computer Studies 131, 131-143.[8]Francisco Betti and Thomas Bohne. 2022. Augmented Workforce: Empowering People, Transforming Manufacturing.[9]The World Manufacturing Forum. 2019. Skills for the Future of Manufacturing.

Päivi Heikkilä, Susanna Aromaa, Hanna Lammi, Timo Kuula

Conference Proceedings

Optimal Explanation Generation using Attention Distribution Model

With highly automated and Autonomous Vehicles (AVs) being one of the most prominent emerging technologies in the automotive industry, efforts to achieve SAE Level 3+ vehicles have skyrocketed in recent years. As new technologies emerge on a daily basis, these systems are becoming increasingly complex. To help people understand - and also accept - these new technologies, there is a need for explanation. There are three essential dimensions to designing explanations, namely content, frequency, and timing. Our goal is to develop an algorithm that optimises explanation in AVs. Most of the existing research focuses on the content of an explanation, whereas the fine-granularity of the frequency and timing of an explanation is relatively unexplored. Previous studies concerning "when to explain" have tended to make broad distinctions between explaining before, during or after an action is performed. For AVs, studies have shown that passengers prefer to receive an explanation before an autonomous action takes place. However, it seems likely that the acclimatisation that occurs through prolonged exposure to and use of a particular AV will reduce the need for explanation. As comprehension of explanations is workload-intensive, it is necessary to optimise both the frequency, i.e. skipping explanations when they are not helpful to reduce workload, and the precise point in time when an explanation is given, i.e. giving an explanation when it provides the maximum workload reduction. Extra mental workload for passengers can be caused by both giving and omitting an explanation. Every explanation that is presented requires cognitive processing in order to be understood, even if its content is considered to be redundant or if it will not be remembered by the addressee. On the other hand, skipping the explanation can cause the passenger to actively scan the environment for potential cues themselves, if necessary. Such an attention strategy would also impose a significant cognitive load on the passenger. In our work, to predict the mental workload of the passenger, we use the state-of-the-art attention model called SEEV (Salience, Effort, Expectancy, and Value). The SEEV model is dynamically used for forecasting the likelihood of the direction of attention. Our work aims to generate an optimally timed strategy for presenting an explanation. Using the SEEV model we build a probabilistic reactive game, i.e., 1.5-player game or Markov Decision Process, and we use reactive synthesis to generate an optimal reactive strategy for presenting an explanation that minimises workload.

Akhila Bairy, Martin Fränzle

Conference Proceedings

Exploration of Intercultural Mechanism of Language through the Interaction with Sensitive Qualities of Artistic Objects

Through the study of 346 artistic products, related to digital paintings from the Medieval period, the relationship between the intercultural mechanism of contemporary language and the qualities of paintings were studied. In this sense the tool developed by Wingfield, C., & Connell, L. (2022) was used, in which the semantic similarity based on user experience was analyzed. In relation to the qualities of artistic object the tetrachoric coefficient of darkness was considered to analyze as one of fundamental sensitive factors of artistic work, so the variables were reduced to the dichotomy: darkness of the digital work in RGB system and concepts based on experience. Likewise, a classification of 57 relevant topics of digital works were obtained. The results suggest the existence of a low relationship in the dichotomy: darkness of image - concept based on experience; However it was observed that as the closeness of the concept increases in relation to the Middle Ages, there is less tendency to find works with a prominent darkness in the digital image., Which suggests that the formation of contemporary concepts related to the Middle Ages are not dependent on the darkness of the work. The intention of these studies lies on exploring the relationship of the intercultural mechanism of language based on semantic similarity -proposed by Wingfield, C., & Connell, in groups of contemporary users and the interaction with sensitive qualities of objects created in ancient times.

Jorge Gil Tejeda, Lorena Olmos Pineda

Conference Proceedings

Blinking, Beeping or Just Driving? Investigating Different Communication Concepts for an Autonomously Parking E-Cargo Bike from a User Perspective

While autonomously parking e-cargo bikes offer the potential to enhance users’ comfort and time efficiency at sharing-stations, it is important to ensure a safe and useable interaction. External human machine interfaces (eHMIs) provide a possible solution for highly automated systems to communicate relevant information and to ensure system transparency. We conducted a laboratory study investigating three different communication concepts for autonomously parking e-cargo bikes: (1) a visual eHMI, (2) an auditory eHMI, and (3) a baseline condition. Participants (N = 36) watched videos of an autonomously parking e-cargo prototype and assessed each concept regarding user experience, acceptance, perceived safety, and trust. Results revealed a clear ranking of communication concepts with the visual eHMI rated to be most suitable followed by the auditory eHMI, whereas ratings for the condition without eHMI revealed considerable concerns for all aspects. Our findings suggest important implications for designing user interfaces for self- parking e-cargo bikes.

Isabel Kreißig, Tina Morgenstern, Josef Krems

Conference Proceedings

Application of Double Skin Facade to Improve the Thermal Comfort Level in an Experimental Chamber

In this work a DSF system (Double Skin Facade) is used to improve the thermal comfort level that the occupants are subjected in an experimental chamber. The DSF system, build with three unities, is equipped in a south facade of the experimental chamber. The study, made in winter conditions, uses the solar radiation to heated the air, injected in the occupied space with 6 people, to improve the thermal comfort conditions. The experimental chamber is build with wood and isolating material. The DSF system is build with two glass façades, equipped with 15 lamellas. This system, subjected to solar radiation, is connected to the interior with a duct system connected with two ventilators. The numerical study consider a software that simulates the building and the DSF thermal response. The numerical model, that considers buildings with complexes topologies, uses energy and mass balance integral equations for the opaque surfaces, transparent surfaces and internal air. The software also considers the solar radiation simulator, the radiative and convective coefficients evaluation, the glass radiative properties and the thermal comfort and internal air quality simulator. In accordance with the obtained results the thermal comfort level, using the PMV (Predicted Mean Vote), during the occupation time, in general, is in accordance with the international standards.

Eusébio Conceição, Maria Inês Conceição, Maria Manuela Lúcio, João Gomes, Hazim Awbi

Conference Proceedings

The Future Impact of Digital Assistants on Aviation Safety Culture

In the coming decade, Artificial Intelligence-based Digital Assistants are likely to appear in operational aviation contexts, including the cockpit and air traffic control Ops room. Current scenarios for such AI support include advising flight crew during mid-flight emergencies, and executing routine air traffic duties in the Tower to reduce complexity and controller workload. The concept for Digital Assistants goes beyond today’s Machine Learning-based tools, which largely offer information to human operators. Instead, the notion is of an AI-based ‘colleague’ that can engage in dialogue with its human counterparts. This in turn leads to the notion of a Human-AI Team and raises a host of questions about how such a team can and should function to optimise system performance and safety. One question in particular concerns how working with a Digital Assistant, and even potentially relying on one in safety critical scenarios, will affect the team’s, and the parent organisation’s safety culture, since safety culture is seen as high in the industry, and valuable in assuring passenger and crew safety. In the European air traffic network, safety culture is measured regularly in different countries using a standardised 50-item scientifically validated questionnaire. This questionnaire has been applied to the Digital Assistant concept to see which facets of safety culture might be affected. The results of this analysis have identified six high-level concerns, but also six instances where the Digital Assistant could potentially reinforce or improve safety culture, providing new ‘safety affordances’. Although the current work’s focus is on aviation, the safety culture issues raised here may also pertain to other domains including health care, the energy sector, space and defence systems.

Barry Kirwan

Conference Proceedings

Visual Instance Retrieval for Cultural Heritage Artifacts using Feature Pyramid Network

Digitized photographs are commonly employed by archaeologists to assist in uncovering ancient artefacts. However, locating a specific image within a vast collection remains a significant obstacle. The metadata associated with images is often sparse, marking keyword-based searches difficult. In this paper, we propose a new visual search method to improve retrieval performance by utilizing visual descriptors generated from a feature pyramid network. This network is a convolutional neural network (CNN) model that incorporates additional modules for feature extraction and enhancement. The first module encodes an image into regional features through spatial pyramid pooling, while the second module emphasizes distinctive spatial features. Additionally, we introduce a two-stage feature attention to enhance feature quality and a compact descriptor is then formed by aggregating these features for searching the image. We tested our proposed method on benchmark datasets and a public vast collection of Thailand’s ancient artefacts. Results from our experiments show that the proposed method achieves 77.9% of mean average precision, which outperforms existing CNN-based visual descriptors.

Luepol Pipanmekaporn, Suwatchai Kamonsantiroj

Conference Proceedings

Efficient Inductive Logic Programming based on Predictive A*-like Algorithm

Various machine learning (ML) techniques have been developed widely over the last decade. Especially, deep learning (DL) contributes to ML for creating a lot of structured data such as tables from unstructured data such as images and sounds. The results have led to a lot of successes in engineering, but most of their decisions and actions are hard to be explained or verified. On the other hand, as a perfectly explainable ML approach, i.e., inductive logic programming (ILP), has been used in data mining. ILP, which is based on the first order predicate logic, is one of the symbolic approaches that is useful to deal with structured data and the relations between them. In a practical sense, we can add the results generated by ILP into given background knowledge, and make the knowledge database rich. Thus, ILP becomes more important for data mining than before, and we can extract meaningful relations between the structured data. However, contrary to DL, it is not easy for ILP to perform a learning process efficiently, because we cannot make ILP processes uniformly executable in parallel on GPU. One learning process corresponds to an inductive prediction process, where training samples correspond to positive and negative examples. In the process, ILP explores hypothesis candidates while calculating a cover set that is a set of examples deduced from each candidate. Notice that from the finally obtained hypothesis, the positive examples should be deduced, and the negative ones should not be deduced with the background knowledge. The cover set is known to be uniformly calculated in relational operations, which are executed on GPU or a relational database management system (RDBMS) such as SQL. Since modern RDBMSs can not only manage memory operations safely but also execute SQL in parallel utilizing GPU. Thus, we can partially execute ILP in parallel. But the overhead of launching the procedure for each cover set calculation is heavy and we cannot ignore the significance of the total overhead. In order to mitigate this problem, we propose an extension of the algorithm for searching a hypothesis in Progol, which is one of the most popular ILP systems. Progol uses A*-like algorithm for searching a hypothesis. The algorithm incrementally refines each hypothesis candidate through adding a literal to it, calculating its cover set in order to check whether it satisfies the condition as a hypothesis. In our approach, our algorithm simultaneously performs several refinements with high possibility as a hypothesis. We call it predictive refinement. Even though the refinements may include redundant ones because the same hypothesis may be found earlier, the predictive refinement reduces a lot of overhead cost for launching the procedure of cover set calculation. Thus our algorithm can generate a hypothesis more efficiently than the conventional search algorithm. We have extended Progol to implement the predictive refinement and cover set calculation of generating hypothesis candidates on PostgreSQL. We have successfully demonstrated that our extended Progol works significantly well to obtain practical experimental results.

Moeko Okawara, Junji Fukuhara, MUNEHIRO TAKIMOTO, Tsutomu Kumazawa, Yasushi Kambayashi

Conference Proceedings

Personalized Learning Path (PLP) – "App" for improving academic performance and prevention of dropouts in India

Personalized Learning is an evolving trend in many schools in the United States and globally. However, an earlier study showed that personalized tutoring positively affected students' achievement. A tutor can quickly and competently evaluate students' capacities and needs and suggest appropriate instruction, resulting in students' academic performance. Studies have found that digital tools in education are efficient, such as digital tutors, digital assessments, and student-centric curricula can support student achievement similar to what is done by skilled human tutors. A PLP App developed with AI, specifically to address issues relevant to India, is presented in this paper that provides precise help to students from across the spectrum who need additional support in understanding any subject and concepts and wish to improve academic performance. This PLP App helps teachers identify gaps in knowledge and understanding of subjects among students and support them with technology-enabled tools to bridge the gap. This is done using Coherence maps between different levels of learning in concepts in specific subjects, which address gaps in learning that cannot be easily addressed in any other manner by both students and teachers. It doesn't just tailor learning, keeping the differences among learners in mind; it also shifts the weight of students' progress from the teacher and divides it between the students and teachers. The PLP App considers the conditions of Learning, such as the motivation of the student, the associated feelings of autonomy, ability, and relevance of the Learning. Setting goals and receiving feedback are essential parts of the learning process. The learning path created by the Coherence maps is a concrete, visualized, and easily understandable list of goals designed to guide students from their current level of knowledge to a higher level of competence. Self-assessment and peer review, coupled with the learning path, help students better understand their skills and increase their sense of autonomy and ownership in Learning. Students should have personal learning paths to encourage them to set and manage their academic goals. The data relating to each student is captured on an ongoing basis by the PLP App to ensure all student performance data is recorded in the system to provide most accurate understanding of the level of knowledge. The PLP software also supports teachers' plans and students' preferences by keeping past track records. Observation and monitoring of benchmarks allow the teacher to assign additional content to the student for better performance. The drop-out of students from schools in India has many reasons. They include understanding the subject or content, personal reasons, economic reasons, and many other reasons. However, it has been established by earlier studies that a significant part of the reason for drop-outs is a failure in specific courses, such as Mathematics and English. The PLP App at least addresses the understanding of the subject content, which should at least reduce the drop-outs due to failure in specific courses.

Jagannath Kallakurchi, Pradipta Banerji

Conference Proceedings

Modeling and implementing program activities to support the implementation of new technologies in the small and medium-sized enterprise sector

The article is part of a doctoral dissertation, the aim of which is to implement the Policy for the Development of Artificial Intelligence from 2020 in Poland by modelling and implementing program activities to support the implementation of new technologies in the small and medium-sized enterprise sector (SME), along with their cyclical monitoring and validation. The doctoral thesis assumes that the realization of the goal will be carried out through the collection and production of a set of good practices that will support and facilitate the implementation of solutions based on artificial intelligence for SME, as well as their popularization in this group, which will fill the implementation gap (lack of addressing the needs of this target group) and the research gap (description of program mechanisms addressing the problems of policy implementation). For this purpose, a platform provided by the Global Partnership on Artificial Intelligence in the form of a website is being used and adapted in Polish market, where an entrepreneur will be able to easily validate his or her level of maturity and can see what technologies are adequate for implementation in his or her enterprise. The conceptual work on the portal identified three main challenges facing SMEs: the difficulty in finding trusted AI suppliers, the lack of knowledge in AI, and the lack of identification of business topics and strategies where AI could be implemented in the organization. By using the portal and describing a specific way to validate suppliers, which will also be the subject of this article, SMEs can count on programmatic support in applying AI to business operations. During the implementation of this tool in Poland, the author of the publication focused on entrepreneurs who do not use technologies or the possible implementation of technologies raises many questions (for example, of a legal nature), and thus blocks the possibility of possible implementation. The article will indicate how AI solution providers are added (assessment list), how SMEs can find out their level of implementation, as well as what recommendations for changes to the portal have come from each side so as to ensure the best possible functioning of this portal in the Polish market, thus addressing the research and implementation problem of the PhD.

Sylwia Stefaniak

Conference Proceedings

Tutorial: Conceptualizing intelligence amplification in human-centred AI applications using the design canvas

Designing applications that enhance the cognitive abilities of their users is complex and requires involvement of stakeholders from different disciplines. The intelligence amplification design canvas aims to ease and support initial design processes. Currently, a step-by-step tutorial for practitioners is lacking. Extending earlier work regarding the organization of a design canvas workshop, the objective of this paper is to provide such a tutorial. Leveraging the comprehensive design approach for intelligence amplification from earlier work, participants of this tutorial will detail a self-defined idea or existing application using the 13 elements of the intelligence amplification design canvas in four short iterations. Following its four design principles, participants use the intelligence amplification design canvas to emphasize and define human-centred design aspects, the embodiment in the form of a software agent, the use of data driven approaches and computational intelligence, and incorporation of human in the loop. This way, the tutorial contributes to the initiation of new human-centred AI projects as well as the analysis and improvement of existing applications. Furthermore, this tutorial aspires to form a group of researchers and practitioners to collaboratively develop and evaluate human-centred AI applications and case studies. The tutorial can be planned as a half-day or full-day session depending on the target audience. The tutorial requires a room for 4-8 pairs of workshop participants, a large screen or beamer, and laptop for the tutorial presentation. The intelligence amplification design canvas can best be printed on A3 paper for each participant and can be filled in using a pen or post-its. The target audience of the tutorial includes, but is not limited to practitioners, researchers, and students active in the fields of computer science, information systems research, systems design and engineering and human-computer interaction.

Jean Paul Sebastian Piest, Maria Eugenia Iacob, Marcel Johanna Theodoor Wouterse

Conference Proceedings

VOXReality: Immersive XR experiences combining language and vision AI models

In recent years, Artificial Intelligence (AI) technology has seen significant growth due to advancements in machine learning (ML) and data processing, as well as the availability of large amounts of data. The integration of AI with eXtended Reality (XR) technologies such as Virtual Reality (VR) and Augmented Reality (AR) can create innovative solutions and provide intuitive interactions and immersive experiences across various sectors, including education, entertainment and healthcare. The presented paper describes the innovative Voice-drive interaction in XR spaces (VOXReality)* initiative, funded by the European commission, that integrates language and vision-based AI with unidirectional or bidirectional exchanges to drive AR and VR, allowing for natural human interactions with XR systems and creating multi-modal XR experiences. It aligns Natural Language Processing (NLP) and Computer Vision (CV) parallel progress to design novel models and techniques that integrate language and visual understanding with XR, providing a holistic understanding of goals, environment, and context. VOXReality plans to validate its visionary approaches through three use cases such as a XR personal assistant, real-time verbal communication in virtual conferences, and immersive experience for the audience of theatrical plays.* Funded by European Union (Grant agreement ID: 101070521)

Apostolos Maniatis, Stavroula Bourou, Zacharias Anastasakis, Kostantinos Psychogios

Conference Proceedings

Human like programming using SPADE BDI agents and the GPT-3-based Transformer

Programming an application requires multiple people with skills and experience in that field. It will also take a lot of time with multiple steps before achieving the final result of an application. Today, developers are assisted by various tools, software, or applications based on Artificial Intelligence (AI) such as OpenAI's ChatGPT. These AI that automatically generates source code helps developers to develop applications much faster. However, although code generators are numerous and very helpful, we are not yet at the stage where we can generate a fully functional application, but just generate pieces of source code. And we don’t know yet how to understand textual descriptions of Software Requirements to generate an application directly. Or where to find data to train an AI capable of generating a functional application from textual descriptions. Therefore, we created a new architecture composed of virtual intelligent agents called SPADE BDI to create virtual developers. The virtual intelligent agents were responsible for keyword extraction, Software Requirements synthesis, and source file creation. Then we used a transformer based on pre-trained GPT-3 for source code generation. This transformer is orchestrated by a virtual intelligent agent. To solve the problem of training data, we collected and created a new dataset called WSBL. The data came from several projects developed with the Laravel Framework over 4 years. The result allowed us to have a functional application directly from a textual description. Each intelligent virtual agent played a role like a developer by analyzing textual of Software Requirements and then generating source code. With a 15% reduction in time to develop an application compared to brute development. Our new architecture allows for processing textual descriptions (Software Requirements) step by step using intelligent virtual agents named SPADE BDI and source code generation is done by a transformer based on pre-trained GPT-3 to have a directly functional application

Alain Josué Ratovondrahona, Hanitriniaina Marielle Rakotozanany, Thomas Mahatody, Victor Manantsoa

Conference Proceedings

Data Analysis for the Projection of Flexible Composite Materials to Naval Transport Scenarios

Accidental spills of oil or other types of hydrocarbons represent a problem of utmost importance, but, in the situation where a multi-criteria approach to the phenomenon is desired, it is necessary a quickly intervention for mitigate the effects of their spread, and for isolation, collection, transportation and storeage for reprocessing. In case of oil recovering, trapped oil can be pumped out to holding tanks (shuttles) for transporting to shore. The functional characteristics required for naval transport are represented by the: operational in strong sea currents oil spill recovery (min. 4bf), transport and storage (at min. 2kt); rapid response in an emergency (possibility to be used in max. 1 h in conjunction with oil spill recovery equipment: vessel, booms, skimmers etc). Although it could be considered that the tear resistance on the longitudinal and transversal system for any composite structure including a textile matrix based on woven structure, could be influenced by the physical-mechanical characteristics of the textile reinforcement (the nature of the raw material and the diameter of the threads), in the situation of usage the flexible elements (narrow fabrics) to join the panels, the correlation between the above mentioned parameters could be made only by mathematical approaches. This assumption is based on the fact that in the textile field, the mechanism of deformation of threads and implicitly of planar structures is not fully explained (as in the field of constructions). The paper presents the analysis of the data collection, with the help of multiple regression, each of the 6 dependent variables (tear resistance values assessed according to three accredited methods in longitudinal and transversal systems) being modeled with the help of 5 independent variables (resistance to maximum force breaking strength, knot resistance, loop for two types of sewing thread and the breaking resistance of composite material fabrics). For the 3500 values obtained as a result of the experiments carried out, the initial hypotheses were related to: i) the experience matrix (u observations for q variables) is fixed, it is not stochastic, and the number of experiences is greater than the number of variables and ii ) the matrix of measured values for the independent variables has linearly independent columns, so it forms a basis of a q-dimensional space. The main problems followed were related to the model parameters, measurement errors, adjustment precision and the choice of the prediction model. The built probabilistic models explain between 55-80% of the variation of the dependent variable, so it would be indicated to introduce additional variables (e.g. for composite material with 45/55% PES/p-aramida matrix) of the type: pattern of the fabric, yarn density in warp and weft, coating thickness. Additionally, the values obtained for the t test identified the importance of the predictors placed in the multivariate regression equations.

Alexandra - Gabriela Ene, Carmen Mihai, Mihaela Jomir, Constantin Jomir

Conference Proceedings

Numerical study of the airflow around the occupant using confluent jets system

In this paper the numerical study of the airflow around the occupant using confluent jets system is made. This study uses a software that considers a coupling between Computational Fluid Dynamics and the Human Thermal Modelling numerical models with the inputs from the Building Thermal Modelling numerical model. The coupling of numerical models is used to evaluate the human temperature distribution, using the Human Thermal Modelling numerical model, the airflow around the occupants, using the Computational Fluid Dynamic numerical model, and the room surrounding temperatures, using the Building Thermal Modelling numerical model numerical model. In this numerical work, developed for winter conditions, the airflow around the occupants and inside the space are evaluated for a confluents jets ventilation system, build with one exhaust and one inlet ventilation systems. The study is made inside a virtual chamber, occupied with two virtual manikins and equipped with one tables and two chairs. The air velocity, air temperature, Draught Risk, carbon dioxide concentration and air exchange rate field around the occupants and inside the space are evaluated.

Eusébio Conceição, Maria Inês Conceição, Maria Manuela Lúcio, João Gomes, Hazim Awbi

Conference Proceedings

Comparison in virtual reality based on efficiency for product assembly

Virtual Reality technology (VR) can be used for manufacturing training within a reduced space to allow trainees to manipulate objects in a simulated environment. Based on the information obtained from this recreation exercise, the production planning team can implement the proper adjustments prior to the beginning of an assembly. During a Project Evaluation and Management course, five students from Tecnologico de Monterrey created a VR space with pieces for assembly in a laboratory, designed with the previous user experience from the students. The main objective of this study was to test the effectiveness of a drill pump assembly process to analyze the assembly time. The study included 44 third-year undergraduate engineering students, 22 females. After the VR study, a statistical test was performed to analyze the results, which indicated that the group of students reduced the cycle time by 67% after two times compared to the first tryout. In addition, no significant differences were observed in the assembly time between the male and female students.

Gabriela G. Reyes-Zárate, Eduardo Caballero Montes, Jorge A. Gonzalez-Mendivil, Uziel Hernández Espejo

Conference Proceedings

Assistive VR platform design for Telemanipulation at the Super Fragment Separator Facility

An assisted remote manipulation (ArM) platform has been defined for the Super FragmentSeparator (Super-FRS) main tunnel and hot cell at the High Energy Physics (HEP) Facilityof Anti-proton and Ion Research (FAIR). The designed platform positioned within a VirtualReality (VR) based framework ensures dynamic collaboration and effective humaninteraction to assist with Remote Handling (RH) operations. To visually stimulate operatorassisted intervention in harsh environments, enhanced interaction based on syntheticvision has been adapted with simultaneous localization and mapping (SLAM) techniquesinterlinked with virtual layers representing a three dimensional manipulation of RHmaintenance tasks. The proposed platform also included a sequence mapping toolevaluated with RH task variables specific to the sequence space analyses of pathplanning, motion check, and collision detection performed in both real and virtual RH taskenvironments. Further assistance was envisaged from multimodal feedback categoriesthrough force feedback, in this case, a backpropagation algorithm was tailored to define aforce limit and to send feedback signals to the operator every time the actual patternexceeded the desired output pattern. Overall, the ArM platform ensures the application ofbest engineering practices to RH needs as a basis to maximize information gathering andsharing driven by continuous improvement initiatives.

Angelo Compierchio, Phillip Tretten, Solomon Oyelere, Chris Karagiannis

Conference Proceedings

Simulation-based Prediction Model to Optimize Contact Pressure of Knitted Fabrics for Wearable Garments

This paper proposes a simulation-based contact pressure (CP) prediction model for prototyping electronic textile (e-textile) wearable devices for health monitoring. This study uses a CLO 3D garment simulator, and knit fabrics are investigated in different weights and polyurethane contents. The first phase presents a comparative analysis of simulated and experimental stress. Based on the understanding of simulated stress, the CP model is developed by modifying Laplace’s law and using the simulated stress. The CP model is validated using a pressure sensor to compare the actual contact pressure. The developed CP model helps garment designers and engineers select the appropriate material and product size to achieve the target pressure required for ECG health monitoring in their decision-making.

Seonyoung Youn, Kavita Mathur, Caitlin Knowles, Beomjun Ju, Busra Sennik, Jesse Jur

Conference Proceedings

Prevention of Work-Related Musculoskeletal Disorders supported by Artificial Intelligence

In the industry 4.0 era, industrial production is designed to be more efficient, more flexible, and with higher quality. Besides, it is characterized by greater automation and computerization. However, in the industrial field, workers are still involved in many jobs requiring them to lift and move heavy items and other production activities that expose them to the associated risk factors for developing work-related musculoskeletal disorders (WMSDs). In physical ergonomics, studies have shown potential for preventing WMSDs through artificial intelligence (AI). In this regard, this literature review aims to establish the current state of art regarding the use of AI to reduce the risk of developing WMSDs. A literature review was carried out in two databases, and through the combination of keywords, 188 articles were found. Twenty-eight papers were retrieved and analyzed based on dimensions related to WMSDs risk factors, ergonomic criteria, and AI applications.

Firdaous Sekkay

Conference Proceedings

Virtual Reality to Improve Technical Teacher Presenting and Speaking Skills

ContextFear of public speaking (glossophobia) is one form of anxiety. People may struggle to speak in a classroom, meeting, and in other group settings. This can make it very difficult for sufferers to communicate verbally to express their knowledge and thoughts. As a result, glossophobia may hamper the sufferer’s ability to further own academic, social or career opportunities.Purpose/approachThe aim of our study was to share experience with a teaching program based on VR to help future teachers improve their presentation and speaking skills. Our study followed a descriptive mixed research design. Participants of 5 groups, each of 5 members went through the regular course of speaking and presentation skills or through a course based on VR. Several characteristics of an individual speech were measured by VR: eye contact, speed of speech, use of crutch words, speech pausing, clarity, loudness, monotony and word repetition. Reduction of glossophobia was measured by a questionnaire and through personal interviews.Actual research outcomes -Interviews with teachers (6 trainers)Pros: high motivation, visible progress, more self-assurance, better performanceCons: cost of equipment, need of technical support-Interviews with course participants (25 future teachers)Pros: felt like being in „real“ classroom and with „real“ students, enjoyment, new experience, emotions, enthusiasm, fun, loss of fear,Cons: made me tired, had to share the equipment with other students, lost my concentration-QuestionnairesClear reduction of glossophobia as measured by self-report of future teachersConclusions VR is eligible to be used in different environments, and many applications successfully apply it to improve learning. Our findings indicate that VR applications are more likely to lead to certain benefits such as increased motivation of users.

David Vaněček, Dana Dobrovská

Conference Proceedings

Development of an Interaction Concept to Illustrate the Energy Transformation on an AR-Surface

Augmented Reality (AR) enables new forms of interaction and knowledge transfer for users. This paper describes a novel approach to visualize information of energy transformation on an AR-Surface. Aiming to provide a playful tangible interaction method with real data for citizens, especially for those locally effected by the changes in future energy production facilities; we analyzed which bifacial aspects can be drawn from the two novel interaction and visualization methods. Therefore, we projected databased information on the AR-Surface so that users were able to interact with the displayed information by placing or moving our own designed tangibles on the surface. In our user study, the participants interacted with a data set on renewable energy production. Through the tangible interaction, the user receives important information, e.g. about renewable energies and their performance. As an outcome of the study, we showed that the use of tangibles offers many advantages, such as fast and easy interaction on an AR-Surface as well as an improved user understanding. The gained insights will help for further implementations and visualizations in the field of AR combined with simple communication of energy topics.

Swenja Sawilla, Waldemar Titov, Mathias Trefzger, Nicola Fricke

Conference Proceedings

Safety and security analysis of Connected and Automated Vehicles: A methodology based on Interaction with stakeholders

Connected and Automated Vehicles (CAVs) are becoming global phenomena and making their way into our society. With the increase in vehicle system automation and connectivity levels, reliance on technology increases, which reduces the human influence on vehicle dynamic driving tasks. This development significantly transformed the nature of human-vehicle interaction design from control to supervisory control. The final goal of CAVs is to enable driverless rides (SAE L 4 – 5), where various stakeholders (passengers, service providers, and insurers) will interact during the post-development phases of the vehicle life cycle. CAVs are susceptible to safety and cyber security attacks where a successful attack could lead to various safety, operational, financial, and privacy losses. This paper aims to propose a methodology for safety and security analysis of CAV interaction with various stakeholders and is aligned with automotive cyber security standard ISO/SAE 21434 TARA. This standard provides the guideline to perform risk management for vehicles, considering the vehicle system level only; whereas the prescribed methodology will complement standard ISO/SAE 21434, performs safety and security analysis based on the CAV - Stakeholders interaction model and investigates the impact of cybersecurity incidents on various stakeholders. The paper presents the methodology which builds upon knowledge combining the known techniques from safety and security domains. The research results in developing an interaction model, and identifying interaction assets, their vulnerabilities, and threats. Furthermore, it performs an attack consequences analysis to demonstrate the impact of the attack on various stakeholders. The developed methodology can be applied to any post-development phase of the CAV life such as operation, maintenance, and decommissioning.

Shahzad Alam, Giedre Sabaliauskaite, Hesamaldin Jadidbonab, Jeremy Bryans

Conference Proceedings

On-Site and Remote Crowdsourcing of Accessibility Data for People with Mobility Impairments: A Case Study in Zurich’s District 1

Collecting accurate accessibility data systematically for pathways is a time-consuming task that typically requires expert knowledge. However, it is a prerequisite to enable reliable and trustworthy accessible routing. The development of Capture & Go, a mobile application to report barriers for people with mobility impairments, facilitates the on-site collection of crowdsourced accessibility data. Several other mapping tools contain accessibility data, although they have not been developed explicitly for this purpose. In contrast to Capture & Go, they allow data collection to be performed remotely. Using quantitative and qualitative approaches, we analyzed several such applications and examined their efficiency in capturing barriers in a case study of District 1 in Zurich. The remotely collected data was compared to the data of the barriers captured on-site using Capture & Go. Overall, the remote tools were less efficient than Capture & Go in terms of effort, coverage, and accuracy of the barriers, as well as usability.

Lina Witzel, Sophy Chhong, Hans-Peter Hutter, Alireza Darvishy

Conference Proceedings

The Course Glancer - Leveraging Interactive Visualization for Course Selection

Lifelong learning requires the consistent and continued development of one’s knowledge, skills, and competencies. However, due to the extensive choice of courses offered at today’s institutions of higher learning, students face a risk of choice overload in their selection of (elective) courses. As current findings in choice overload literature do not refer to student samples in educational settings nor do they consider the use of interactive visualization formats, the use of interactive visualization in higher education organizations seems a promising way to support course selection that fits educational needs. All the more as previous visualization approaches to overcome table-based visualizations or online course catalogues primarily aim at communicating curricular content and structure to different university stakeholders, while disregarding students. We thus introduce our work-in-progress on an interactive visualization tool called the Course Glancer. The Course Glancer supports students’ decision-making ability when confronted with a variety of learning offers while taking electives of a bachelor’s degree program in business administration. The tool provides support for gaining an overview on all available courses and their categories, and for rapidly comparing course alternatives. In doing so, it can help to clarify course preferences and finally to foster students’ confidence of not having overlooked an important course option. This is in line with Shneiderman’s information-seeking mantra as a must-have for effective cognitive processing: Overview first, zoom and filter, then details-on-demand. We use this mantra in connection with Norman’s usability principles of discoverability, affordances, feedback, constraints, mapping, and consistency. An example of how we use constraints is that course comparison is limited to juxtaposing two courses only. This functionality considers latest evidence from using eye-tracking studies that revealed that human beings tend to distribute their attention in an unbalanced manner and focus mainly on the two options that seem the most promising alternatives. To enrich the empirical research on choice overload, we plan to focus on psychological effects in the use of the Course Glancer. These include subjective, moderating factors (e.g., decision style) and behavior-related measures. The latter refer to subjective states (choice satisfaction, decision regret, decision confidence) or behavioral outcomes (e.g., choice deferral, option selection). Beyond these, group-related effects should also be analyzed in future research, for example, if interacting with our tool can stimulate information exchange processes within expert groups of higher education organizations (e.g., in the context of accreditation procedures or curriculum planning).

Christian Spletter, Martin Eppler

Conference Proceedings

Operationalising ontologies for competence management in the industry

With the increasing availability of digital resources for on-the-job training, competence management in the industry requires new tools to identify training opportunities for the continuous development of the skills of employees. Our emphasis is to determine which digital courses or further learning resources suit the actual employee’s competence in combination with the skills and knowledge she or he aspires to achieve. In this paper, we describe the role of ontologies and, in particular, the ESCO ontology for the development of suitable profiles for learners, learning goals, and learning resources. We describe the matching processes operating on these profiles in order to identify the training opportunities that match best the learner’s capacity and aspirations.

Kurt Englmeier, Pedro Contreras

Conference Proceedings

Identification of airspaces with increased coordination effort based on radar data

Artificial intelligence (AI) systems can be beneficial in various disciplines such as medicine, space travel or air transport. The Project “Collaboration of aviation operators and AI systems” (LOKI) of the German Aerospace Center (DLR) aims to develop guidelines for a human-centered design of communication and also collaboration between users and AI systems. The Project focusses on areas of activity in air traffic management where operators work together collaboratively. To identify the potential for AI support of air traffic controllers as well as pilots, information about the coordination effort of aircrafts for air traffic controllers in the European airspace is needed. The aim of this paper is to identify areas of increased coordination effort for air traffic controllers based on four-dimensional radar data. Here, AI could be advantageous for air traffic management.For this purpose, we used flight tracking data from a network of ADS-B receivers. The data includes all flights in the upper European airspace in September 2019 and has a resolution of one data point per minute. First, the data was pre-processed and visualized. Afterwards three criteria for detecting possible communications between pilots and controllers were applied to the data. The first criterion examines the frequency of climbs and descents in the course of a flight. The second one analyses the changes in flight direction in the flight trajectories. The third criterion identifies aircraft that fall below a minimum vertical and lateral separation between each other. The Python programming language and various data science libraries were used to apply the criteria to the data. The result is a spatio-temporal cadastre with entries of possible controller communication which shows that relatively large areas with a high coordination effort for air traffic management controllers exist in Europe. These areas are mostly located in Central Western Europe and UK, but also in Spain, Portugal and Russia, inter alia. In reality, the coordination effort is probably even higher than in this model. Against this background, it is reasonable to conclude that the potential for using AI in air traffic management is rather high and that the use of AI can be beneficial for ATM operations in Europe.

Sören Holzenkamp, Martin Jung

Conference Proceedings

Bulgaria's Digital Transformation

For over three decades, Bulgaria has been advancing the level of technology in the country. The strategy has evolved from e-government into digital transformation. In the beginning, the country’s e-Government program was focused primarily on developing and upgrading infrastructure elements and main systems. However, the existing regulatory framework was able to accommodate e-Government, but it did not stimulate it. In addition, difficult to achieve high efficiency achieve high efficiency due to a lack of a systematic approach to e-Government development. Some agencies had progressed significantly in implementing electronic administrative services, but in general, e-services were limited.The government forged a strategic framework to implement e-government, and a new e-government agency was established to guide the process. Tis strategy has been successfully implemented: the government has gone paperless, citizens have mobile access to government services, and schools receive curriculum materials electronically. e-Government system, part of an end-to-end solution to provide e-Government services The main components of Bulgaria’s e-Government infrastructure include portals, networks, eIdentificatin/e/Authorization, and knowledge management. The legal framework includes legislation, freedom of information, data protection/privacy, e-commerce, e-communications, and e-procurement.Bulgaria has obtained significant benefits from this program. In particular, it has contributed to a tangible reduction of the administrative burden on citizens and business. Going paperless by itself has saved hundreds of tons of paper and humdreds of thousands of dollars annually. In addition, government processes have been optimized, and systems are more reliable and secure.The program continues with Digital Bulgaria 2025. This program has a vision beyond government operations and seeks to bring the benefits of digital technology to all sectors of the economy and society. The goal is to create an environment to foster the widespread use of information and telecommunications technologies (ICT), along with new technologies for businesses and citizens. Continued progress in e-government is an important part of the program, as well as modernizing education, improving the digital ICT skills of the workforce, and increasing the number of highly qualified ICT specialists. Significant benefits are expected from the implementation of this strategy.It encompasses achievements so far and the new European strategic and programming guidelines for achieving a smart, sustainable and inclusive digital growth. The goal is widespread implementation of intelligent solutions in all areas of the economy and society, and modernizing information and communications technologies (ICT

Linda Bower

Conference Proceedings

The Mixed Reality Passthrough Window: Rethinking the Laptop Videoconferencing Experience

The growth in remote and hybrid work has resulted in an increased demand for collaborative, videoconferencing experiences that offer a more seamless and immersive transition between virtual and physical environments. The Mixed Reality Passthrough Window (MRPW) addresses this demand by introducing a new paradigm for the integration of augmented/mixed reality into laptop design. The design is characterized by two screens, situated back to back, with two mounted cameras, facing in opposite directions. This creates the effect of looking through a window, upon which virtual content can be augmented and overlaid. This configuration allows local users sitting around the laptop to more easily interact with remote users, who appear on both sides of the Mixed Reality Passthrough Window, giving the sense that all users are sharing the same space in the round. Additionally, these features create affordances for the outward facing screen to serve as a site for presentations (e.g. slide decks) and other sharable content.

Ian Gonsher, Yumeng Ma, Ivan Pineda-Dominguez, Matthew Lee, Yuxin Han

Conference Proceedings

Internet of Things (IoT) based Drowsiness Detection and Intervention System

This study aimed to develop a non-intrusive smart monitoring system that could identify and prevent drowsy driving, reducing the risk of accidents. The study developed a system that uses video processing to measure the Euclidean distance of the eye and an eye aspect ratio (EAR) in order to detect drowsiness. The system employed face recognition to accurately identify the driver's eye aspect ratio. An Internet of Things (IoT) module used for remote assessment of the driver's drowsiness response in real-time. If the driver is in a drowsy state, the system sends an alert/warning to the driver and relevant authorities. In addition, if a crash occurs, the system sends a warning message with the location of the collision. The system was tested on 20 participants, achieving an overall eye detection accuracy of 99.98% (with glasses), 99.89% (without glasses), and a drowsiness detection accuracy of 98.05% (with glasses) and 99.05% (without glasses). This system has the potential to be implemented in a variety of driving applications, where expensive technologies are often difficult to adopt.

Amandeep Singh, Siby Samuel, Jagmeet Singh, Yash Kumar Dhabi

Conference Proceedings

Prevention of Cyberbullying in Social Media: Perspective of Female Entrepreneurs in Bangladesh.

In recent years social media is a very popular platform for any kind of business. During the pandemic, it became even more trendy for small business owners who run businesses from home. Particularly in developing countries like Bangladesh where socially and culturally women face a lot of obstacles to doing business. The number of female entrepreneurs in Bangladesh is growing day by day as this is an opportunity for them to earn and support their families. Initially, they prefer social media for their business platform because there is no need for business premises, and it is easy to target a large number of customers in a short period of time. While the prospect of female entrepreneurship is bright for this country, they are encountering cyberbullying on social media by some ill-minded people. This paper aims to find out how female entrepreneurs in Bangladesh experience and can prevent cyberbullying on social media. This is exploratory research. Qualitative data were collected through an online semi-structured interview method by using open-ended questions. Data were analysed thematically based on different codes and themes by using NVivo 12 software. The result shows how female entrepreneurs get cyberbullied on social media in this country. It also recommends some preventive actions that female entrepreneurs can exercise to protect themselves from cyberbullying while operating their businesses on social media.

Mohammad Rashed Khan

Conference Proceedings

Can ChatGPT Help College Instructors Generate High-quality Quiz Questions?

ChatGPT is getting increasing attention in both academic and professional settings. Since its release, there has been a discussion on how services such as ChatGPT may change education. Many teachers have shared that they use ChatGPT to help them generate assignment prompts, questions, and lesson plans in various subject areas. Mixed opinions have been shared with regard to the quality of materials created by ChatGPT. While some teachers believe that the materials are of reasonable quality, others worry that ChatGPT may not always generate accurate or reliable information and may reproduce biases and stereotypes that exist in the data it was trained on. In this study, I explore the research question of whether ChatGPT can really replace teachers in generating high-quality assessment questions. Specifically, I compare ChatGPT-generated questions with instructor-written questions that have been used in two classes at a public research University in the US. The preliminary results show that although ChatGPT can produce logically sensible questions, the quality is not always comparable to instructor-written ones. The ChatGPT-generated questions are not specific to student misconceptions and do not align with the learning objectives instructors have in mind, which often leads to such questions being relatively obvious and easy to answer. I further discuss the capabilities and limitations of ChatGPT in generating high-quality assessment questions. This study provides insights into how we may leverage advanced AI tools such as ChatGPT to support education.

Kai Lu

Conference Proceedings

Comparative Analysis Methods in Optimizing Corticosteroid Therapy in Patients with Covid-19 and Diabetes Mellitus

Background: The method of comparative analysis is one of the most common in science where optimal choices are required. Despite the fact the method is empirical, under the conditions of epidemics such as Covid-19, it is one of the most affordable in assessing the effectiveness of the therapy. Patients with diabetes having coronavirus infection are included in the risk group which required steroid therapy. In patients with diabetes, excessive usage of Exogenous corticosteroids creates insulin deficiency which leads to hyperglycemia and the risk of developing coma. Purpose of the study: сompare the effectiveness and safety of using corticosteroids in patients with Covid-19 and diabetes prescribed "by standards" and "method of calculation". Method: Diabetic Patients with novel coronavirus infection were screened (n = 107).All patients were divided into 3 groups.In group 1(n=35) patients received dexamethasone at a dosage of 0.1 mg/kg once a day in the morning intravenously; in group 2(n = 38), patients received dexamethasone 20 mg twice daily intravenously in the morning and evening (more than 0.2 mg/kg/day) and in group 3(n = 34) patients received dexamethasone 0.1 mg /kg once a day in the morning intramuscularly. Comparative analysis were carried out according to the criteria: the period of intoxication, glycemic variability, CRP, leukocyte counts, D-dimer, and transaminases. For analysis STATISTIC 10,0 computer program was used (Matematica®, Matlab®, HarvardGraphics®) StatSoft). Results: In all the groups after therapy it was noted redistributive leukocytosis.In patients receiving high therapeutic dose (group 2) initially suppressed production of leukocytes is activated and reaches the normative indicator (p&lt;0.001) and the indicators are comparable to the data of group 3(p&lt;0.001)in which patients received glucocorticoids at a lower dose (0.1 mg/kg/day) intramuscularly. The most significant decrease in D-dimer levels was in patients with a dosage of dexamethasone at the rate of 0.1 units/kg once a day intravenously by 80.9%(P &lt;0.0001);intramuscularly by 73.2%(P&lt;0.00001)and with intravenously at a dose of more than 0.2 units/kg there was a decrease in the level of D-dimer by 67.9% (P &lt;0.00001). Decrease in CRP (cytokine storm relief rate) did not differ significantly between the groups, which eliminates the role of inexpedient usage of dexamethasone in dosages of more than 0.2 units/kg/day.Fasting blood glucose in patients in group 3 increased by 22% (P&lt;0.0002); in group 1 only by 12% (P &lt;0.05)and in group 2 by 32% (P &lt;0.0001). In all the groups, an increase was observed in postprandial glucose, and in group 2 to the level of developing ketoacidosis and required emergency intervention by increasing the dose of insulin. Conclusion: For patients without diabetes, the dose of dexamethasone is prescribed in accordance with standards (average dose) regardless of body weight and concomitant diseases. In patients with diabetes are required to determine the dose of dexamethasone individually at the rate of 0.1 mg /kg body weight per day. This method reduces the risk of adverse outcomes and ensures the achievement of positive dynamics of clinical and laboratory parameters which ultimately reduces mortality and shortens the recovery time.

Ikram Ghouri Mukarram Mohammed, Irina Kurnikova, Maiorov Vladimir, Iuliia Verzina, Tatiana Meleshkevich, Evgeniya Tavlueva

Conference Proceedings

Quantitative assessments in evaluating the effectiveness of arterial hypertension treatment: new technologies

Background. In the practice of clinical research, it is traditionally accepted to evaluate parameters that characterize the degree of impairment or loss of the function of an organ or system, and not their preservation. A fundamental change in the approach distinguishes a new trend in modern medicine, which makes it possible to assess the degree of preservation of functional resources, which was the basis of this study.Study purpose: To develop a method for dynamic quantitative assessment of the severity of arterial hypertension and evaluate the relationship between a qualitative indicator of arterial hypertension and a quantitative indicator.Instruments and Data Collection Procedure. Index of adaptive aptitude (IAA) (patent for invention No. 2342900 "Method for eavaluation of the functional reserves of the body", author - Kurnikova I. A.). using automated assessment (certificates of official registration No. 2007614560 and No. 2007613898).IAA=0.011(P-P)+0.014(S-S)+0.008(D-D)+0.009(W-W),Where: P - actual heart rate (b/min.); P* - ideal pulse rate (beats/ min.); S - systolic blood pressure, actual average per day (mm Hg); S* – ideal systolic blood pressure (mm Hg); D - diastolic blood pressure, actual average per day (mm Hg); D* - ideal diastolic blood pressure (mm/Hg); W - body weight at the time of examination (kg); W* - ideal body weight (kg); H - patient's height at the time of examination (cm).Assessment of daily heart rate variability on the Valenta system, equipped with a program for computer processing of spectral analysis indicators.Results:- 143 patients with arterial hypertension (AH) were examined. The relationship between a qualitative indicator - the severity of AH and quantitative indicators - rehabilitation potential, the numerical value of which is PAS, the circadian index (CI) as an indicator of increased sensitivity of the heart rate to sympathetic stimulation, and the LF/HF vago sympathetic balance coefficient, which increases with hypersympathatic tone, was considered. Statistical analysis of the surface plot using the weighted least squares distance allowed this relationship to be clearly demonstrated. Quantitative analogue of the Framingham arterial hypertension severity scale (AHSS) in a specific patient (certificate for invention №. 201152181)AHSS = 119,31 + 2,22× (CI) - 2,03× (IAA) - 1,33×(2×(CI)) + 2,72×(CI)× (IAA) + 7,06×(IAA)where: AHSS less than 120 - normal. Mild AHSS = 121 – 130 points; average severity of AHSS = 131 – 140 points; severe AHSS - 141 points or more. The effectiveness of rehabilitation is good with AHSS less than 120, satisfactory - with 121 - 130; unsatisfactory - more than 131.For illustration, the data of 54 patients are presented. Observation group "1" - patients with AH (BMI<25), mean age - 49±1.9 years (19 people). Observation group "2" - patients with metabolic syndrome (BMI>25; HOMA index> 2.5), mean age - 50±1.7 (35 people). All patients were assessed for the severity of hypertension according to the WHO criteria and the AHSS index at the beginning of the study. Normal value was achieved in 41.8% in 1st group during treatment, in 47.1% there was a decrease in the severity of AH according to AHSS. In group 2, in patients with metabolic syndrome during treatment, it was possible to normalize blood pressure in 55.8%, and to obtain satisfactory results in 35.9%.Conclusion. Developed mathematical modeling methods, a quantitative analogue indicator of the severity of arterial hypertension - AHSS allows you to dynamically monitor the effectiveness of treatment and evaluate the achieved result based on a quantitative assessment within the severity indicated by the classification. The effectiveness of the rehabilitation of patients with hypertension is considered sufficient if the AHSS decreases below the value of 120 units or one level from the baseline

Irina Kurnikova, Ramchandra Sargar, Alexi Pavlov, Zhanar Baisenbaeva, Natalia Zabrodina, Maria Zavalina

Conference Proceedings

Engaging Students through Conversational Chatbots and Digital Content: A Climate Action Perspective

In this case study, we report experiences deploying a conversational chatbot as a pre-class and post-class engagement tool for undergraduate students enrolled in sustainability-related courses aimed at educating them about the severity of climate change and the importance of climate action by offsetting one’s carbon footprint (e.g, by planting trees or mangroves in SEA). The intitiative supports the university’s sustainability efforts in general and our new sustainability major in particular aimed at helping students to achieve sustainability-related learning outcomes with reference to climate change and climate action (SDG 13), one of the 17 Sustainable Development Goals established by the United Nations in 2015.Climate action means stepped-up efforts to reduce greenhouse gas emissions and strengthen resilience and adaptive capacity to climate-induced impacts, including: climate-related hazards in all countries; integrating climate change measures into national policies, strategies and planning; and improving education, awareness-raising and human and institutional capacity with respect to climate change mitigation, adaptation, impact reduction and early warning… (https://www.sdfinance.undp.org/content/sdfinance/en/home/sdg/goal-13--climate-action.html).Related teaching and learning challenges we have observed in our classes include climate change ignorance / indifference, lack of confidence in calculating one’s own carbon footprint, not knowing why personal climate action is important and how it can contribute to active decarbonisation etc. to mitigate climate change. Several research studies have underlined the potentially positive effect of Chatbots on students’ learning in educational institutions ranging from primary schools to IHLs. “Conveniency”, “satisfaction”, “engagement” and “motivation” have been highlighted in previous studies as benefits of using conversational pedagogical agents (= “Chatbots”) in teaching and learning (Smutny & Schreiberova, 2020; Martha & Santoso, 2019; Satow, 2017; Fadhill & Villaforita, 2017; Pereira, 2016; Kim & Baylor, 2007).Conceptually, the ongoing project relates to the study of technology-mediated learning in general and chatbot-mediated learning in particular Winkler & Söllner (2018) have highlighted the advantages of chatbot-mediated learning (CML) in educational settings with regard to positive learning outcomes that include learning success and student satisfaction. Chatbot-mediated learning (CML) has enabled learners to take on a proactive approach in creating an individualized learning experience in the context of large-scale lectures and massive open online courses (MOOC) where individualized support was lacking. Chatbots play an essential role in T&L by supporting teachers to create interactive learning experience when teachers are not physically present, monitoring results and performance, and disseminating regular reminders to check on homework and encourage students in their learning efforts (Clarizia et al, 2018). Research also observed that the use of chatbots helped to facilitate better communication and interaction between students and teachers as well as amongst students (Clarizia et al., 2018; Tamayo et al., 2020). CML also helped to bridge the gap in distance learning by assisting students during the revising process during time away from school (Tamayo et al., 2020).A key intent of the ongoing project is to build a chatbot that can effectively educate and engage students with regard to the concept of ‘carbon footprint’ (which refers to the total amount of greenhouse gases such as carbon dioxide and methane that are generated by our actions) and to make them appreciate the importance of reducing one’s own carbon emissions (= footprint) to avoid a 2℃ rise in global temperatures and to (actively) combat climate change.By using Google’s DialogFlow as brain (and T&L tool) of the chatbot, we argue that bot building workshops integrated into a learning course do act as a teaser for learners to review and internalise relevant climate change and carbon footprint related learning content (e.g., by using relevant personas/avatars such as The Doubtful Debbie, The Alarmed Ali, The Concerned Chris, The Disengaged Devi etc), enabling students to appreciate the urgency of concrete offsetting opportunities provided by new tech start-ups such as Handprint. Bots can also feature topic-related learning tests in support of relevant learning outcomes.

Thomas Menkhoff, Benjamin Gan

Conference Proceedings

Public's Perspective on Civil Drones: Reasons to support and oppose

Drone technology is prevailing in the mainstream market with its promising innovative potential across different application scenarios. While the technological capacity of drones is explored and developed, many have addressed the societal perceptions and reactions towards its use. Recent literature inclines towards more neutral if not positive perception by the general public. This paper, performed within a European Union project ADACORSA, explores the most relevant concepts for drone technology acceptance and presents a detailed overview of the survey-based research conducted in 2022. Data was collected from a total of 601 participants across Europe and ADACORSA partner countries largely from Germany, Austria, France, Greece and Turkey. To make the survey as accessible as possible, participants could take the survey in 16 different languages. The performed risk analysis showed highest level of concerns related to security/privacy in terms of misuse and invasion of private spaces. Safety and privacy concerns are perceived as equally risky. Benefits analysis on the other hand revealed general public anticipates greater economic advantages but significantly lesser societal and environmental benefits. Apart from emergencies and humanitarian aid, and purposes to facilitate services that benefit society, industrial applications curtailed most support from the general public. Highest opposition was established for hobby/recreation-related drone use, primarily from individuals who have never used a drone. The objective of this paper is both to understand general public’s acceptance towards the use of drones and to provide a nuanced overview to drone operators of which purposes are perceived as reasonable and are accepted by the general public.

Vaishnavi Upadrasta, Rodney Leitner

Conference Proceedings

New technologies sustainability: monitoring and evaluation of results of interventions for the promotion of cultural heritage and the human landscape

The relationship between the development of technologies and the history of the cultural and agricultural landscape is linked to the concepts of "cultural landscape", understood as a space in continuous construction that changes with the change of individual, collective, social and cultural relationships of the inhabitants of the territory, or of the "cultural inhabitants", citizens who are producers of culture, rather than users. A vision of the "future as an open place" emerges, understood as a place of usability and sharing of all human, material and immaterial productions.Technologies, within a similar perspective, are presented as the historical evolution of téchne, whose degree of development today allows an extension of the level of human action.This study, in agreement with the scientific literature based on the use of recently developed digital models, demonstrates that the mainly agricultural territory of Basilicata, historically the site of complex social relations, has created a traditional rural society in which the concept of neighborhood and the spatial connotation also had the symbolic value of sharing knowledge and practices, relationships based on inclusiveness and sustainability. The diffusion of 5G technology is generating important cultural transformations. What used to be the neighborhood community in Matera (IT) - also following the activities launched with the CTEMT project and the social consequences of the Covid-19 pandemic - is now becoming a virtual community for sharing knowledge and practices , beliefs and values, including the use and management of cultural heritage, which takes place through the network, and therefore using applications that promote a transformative intervention of the landscape, such as to make it functional to human needs, and, at the same time, sustainable with respect to the perpetuation of ecosystem relationships.The diffusion of 5G technology, is generating important cultural transformations. What in the past was, in Matera (IT), the neighbourhood community - also as a result of the activities launched with the CTEMT project and the social consequences of the Covid-19 pandemic - now becomes a virtual community, sharing knowledge and practices, beliefs and values, including the use and management of cultural heritage, occurs through the network with the use of applications that promote accessibility and sustainability in both the urban and agricultural landscape. As argued by the International Union for Conservation of Nature (IUCN), the attention to the dynamic conservation of the landscape should not be placed so much to the "culture itself" or to the "nature itself" but rather to the relationship between these two dynamic components has been established, but also from the holistic mentioned many times, attentive to the values of identity and comforted by the knowledge and decoding of the intangible heritage, from which we deduce the active role, shared social behaviours, the mechanisms of transmission of knowledge and transgenerational awareness also thanks to the complex and fascinating universe of uses, traditions, rituals and rites that are an important tool of conscious management of the landscape and its culture. The conscious use of artificial intelligence is the concretion of the virtuous relationship between Humanism and technologies. For the biodiversity it is a support to the recognition of the species, in particular of the native ones, and it allows people to recognize themselves culturally and find into the biodiversity a collective and cultural belonging to the community and to the landscape. Therefore, thanks to the use of new technologies biodiversity becomes an historical-anthropological archive of knowledge and practices of a territory, and new technologies a powerful tool for the conservation of the cultural heritage.

Paola Dantonio, Costanza Fiorentino, Vincenzo Nunzio Scalcione, Francesca Vera Romano, Francesco Toscano

Conference Proceedings

Human Machine Interaction and Security in the era of modern Machine Learning

It is realistic to describe Artificial Intelligence (AI) as the most important of emerging technologies because of its increasing dominance in almost every field of modern life and the crucial role it plays in boosting high-tech multidisciplinary developments integrated in steady innovations. The implementation of AI-based solutions for real world problems helps to create new insights into old problems and to produce unique knowledge about intractable problems which are too complex to be efficiently solved with conventional methods. Biomedical data analysis, computer-assisted drug discovery, pandemic predictions and preparedness are only but a few examples of applied research areas that use machine learning as a pivotal data evaluation tool. Such tools process enormous amounts of data trying to discover causal relations and risk factors and predict outcomes that for example can change the course of diseases. The growing number of remarkable achievements delivered by modern machine learning algorithms in the last years raises enthusiasm for all those things that AI can do. The value of the global artificial intelligence market was calculated at USD 136.55 billion in 2022 and is estimated to expand at an annual growth rate of 37.3% from 2023 to 2030. Novel machine-learning applications in finance, national security, health, criminal justice, transportation, smart cities etc. justify the forecast that AI will have a disruptive impact on economies, societies and governance. The traditional rule-based or expert systems, known in computer science since decades implement factual, widely accepted knowledge and heuristic of human experts and they operate by practically imitating the decision making process and reasoning functionalities of professionals. In contrast, modern statistical machine learning systems discover their own rules based on examples on the basis of vast amounts of training data introduced to them. Unfortunately the predictions of these systems are generally not understandable by humans and quite often they are neither definite or unique. Raising the accuracy of the algorithms doesn't improve the situation. Various multi-state initiatives and business programs have been already launched and are in progress to develop technical and ethical criteria for reliable and trustworthy artificial intelligence. Considering the complexity of famous leading machine learning models (up to hundreds of billion parameters) and the influence they can exercise for example by creating text and news and also fake news, generate technical articles, identify human emotions, identify illness etc. it is necessary to expand the definition of HMI (Human Machine Interface) and invent new security concepts associated with it. The definition of HMI has to be extended to account for real-time procedural interactions of humans with algorithms and machines, for instance when faces, body movement patterns, thoughts, emotions and so on are considered to become available for classification both with or without the person's consent. The focus of this work will be set upon contemporary technical shortcomings of machine learning systems that render the security of a plethora of new kinds of human machine interactions as inadequate. Examples will be given with the purpose to raise awareness about underestimated risks.

Anastasia-maria Leventi-peetz

Conference Proceedings