bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Human-Machine Interface for Truck Platooning Using Driving Simulator
Authors: Sugimachi Toshiyuki
Published: November 2024

Environmental and energy problems as well as countermeasures of the driving burden of truck drivers are critical issues in the logistics industry in Japan. As a solution to these problems, concerns regarding autonomous truck platooning of heavy-duty trucks are heightened globally. The actual operation of truck platoon systems in which trucks are unmanned is considered in limited traffic environments, such as expressways. The lead truck driver should confirm the safety of not only his/her truck but also those of the trailing truck(s). This study designs and evaluates a Human-Machine Interface (HMI) for the driver of the leading truck in an unmanned truck platoon using a driving simulator (DS). The HMI was assessed through a combination of objective evaluation of driving behavior, biometric data, and subjective feedback gathered via a questionnaire. The results demonstrated that the driver of the leading truck could effectively change lanes using the proposed HMI, and the inclusion of a bird’s-eye view significantly improved driver acceptance.This study proposes an HMI that incorporates mirror image displays and a bird’s-eye view as in-vehicle HMI components.1.Mirrorless Image Display:When the driver of the leading truck in a platoon checks the safety of the surroundings, it is crucial to visually confirm the side mirrors and rear monitor. The position to be displayed by the camera in the platooning is considered, and the image display is adapted to the safety confirmation of the drivers in the platoon.2.Bird’s-Eye View Display:In addition to the selected mirror images, this study proposes a bird’s-eye view that facilitates understanding the positional relationship with other trucks when confirming safety. In this study, the DS is used to measure the driving behavior of the participants. Biometric measurements are also taken to assess psychological burden. Furthermore, a questionnaire is conducted as a subjective evaluation, and a comprehensive assessment is made by integrating these results with the objective evaluation of driving behavior. The effectiveness of the proposed HMI was demonstrated through the DS experiment results.
Enhancing User Satisfaction and Accessibility in VR: A Comparative Analysis of Different User Interfaces
Authors: Sowell Faith , Rodarte Daniel , Yang Yiran , Deb Shuchisnigdha
Published: November 2024

In recent years, virtual reality (VR) technologies have improved and become more affordable, leading to an increased adoption of VR in healthcare, manufacturing, education, and other industries. To facilitate further growth, human factors engineers and software developers must work hand in hand to ensure that virtual reality technologies are easy to use by as many populations as possible. This research investigates how different user interfaces can improve a VR user’s experience, with accessibility incorporated into the design. Three interaction modes were tested: traditional VR headset controllers, hand tracking, and gaze interaction. All three interaction modes were tested in a CNC Hybrid Machine training simulation similar to those used in industry. The simulation was created using the Unity game development engine for the Meta Quest 3 VR headset. The satisfaction of the participant with each interaction mode was indicated using presence, usability, and mental workload surveys given after each interaction mode experience. The results of the participants’ surveys indicate that participants liked using controller mode the best. Gaze tracking was the second favorite because of its simplicity, ease of learning, and seamless multitasking with it. Hand tracking was the least favorite due to difficulties interacting with objects. Future development to improve hand tracking technology in the Meta Quest 3 could improve users’ interaction experiences.
Design of fire escape system for children based on VR technology
Authors: Wang Aijun
Published: November 2024

Fire is one of the disasters that threaten people's lives and property safety, and mastering correct fire escape skills can greatly reduce the casualties caused by fire. Most of the traditional fire escape education is carried out in the form of fire escape drills, lectures, etc. Although it has played an educational effect to a certain extent, it can't build a safe and experiential interactive platform for people. In view of this, the design scheme of fire escape system based on VR technology is proposed, and the process and framework of the system are given at the same time; the key technologies in the platform are discussed and researched; and the logical idea and realization method of the interactive function using C# language in Unity 3D are elaborated in detail.
User Experience of Virtual Reality in Healthcare Clinical Training
Authors: Zhang Lizhu , Xi Wang Cecilia
Published: November 2024

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

Virtual reality (VR) simulations have emerged as valuable tools for training and education, allowing learners to engage with realistic virtual environments. This study investigates a novel VR training simulation that integrates visual, audio, haptic, and olfactory cues. Participants (N=54) learned a specific sequence of interactions for operating the Super Soaker 5000 pump panel and were subsequently tested on their ability to replicate these steps. Demographic data and sense of presence questionnaires were collected. The research reveals intriguing findings. While the combined sensory conditions enhanced participants’ sense of presence, they did not significantly impact final pump panel test performance. However, an essential factor emerged: the amount of time spent during the learning phases significantly affected final test outcomes. These results prompt further exploration into optimizing training duration and refining the integration of sensory modalities in VR simulations. This paper discusses the study’s results, the implications for training effectiveness, and the need for future research. By understanding how sensory cues influence learning outcomes, educators and practitioners can enhance VR training experiences and better prepare learners for real-world scenarios.
Exploring Hand Dexterity in Spoon Handling : Impact of Handle Cross-Section on Dynamic Tripod Grip
Authors: Huang Yu-chen , Chang Johan
Published: November 2024

Spoons are among the fine tools frequently used by toddlers who transition from early power grips to refined dynamic tripod grips. Research on fine finger manipulations reveals that such operations are more stable when performed with relatively small finger flexion and pressure changes. Existing literature on pencil and chopstick handling shows that the cross-section of the handle affects fine manipulation, but there is limited research specifically evaluating such effects with regard to spoons. To design a spoon suitable for dynamic tripod grips and facilitate learning for toddlers with less mature manipulative skills, experiments were conducted with adults who exhibit stable dynamic tripod operations. This study synthesized spoon operation literature and movement processes to identify three specific tasks: Scooping, Cutting, Gathering. Following an analysis of commercially available products, six common cross-sectional shapes were selected. Thirty adults with normal hand function participated in the experiment, wearing flexion and pressure sensors to assess the impact of handle cross-section shapes on operational efficiency, finger stability, and finger pressure. Results indicate that hexagonal and pentagonal shapes offer the best operational efficiency. No significant differences in finger stability were observed among the six shapes, and circular shapes allowed for better performances in finger pressure. Overall, the combined evaluation suggests that circular, pentagonal, and hexagonal shapes are preferable, providing a foundation for product development in this field. The applicability of these findings to toddlers can be further validated through future experiments.
Optimizing speech elicitation tasks for machine learning-based depression assessment
Authors: Bauer Jonathan , Gerczuk Maurice , Schuller Bjoern , Berking Matthias
Published: November 2024

THEORETICAL BACKGROUND: The field of machine learning-based speech analysis may provide unobtrusive, time-efficient and cost-effective ways of automated depression assessment. Systematically optimizing speech elicitation tasks may further improve the accuracy of this approach. We hypothesized that machine learning-based depression classification would perform better if trained on recordings of individuals reading anti-depressive statements with the instruction to intone them as convincingly as possible compared to readings of anti-depressive statements without instructions regarding intonation.METHODS: To test this hypothesis, we recruited a sample of 48 clinically depressed individuals, 48 sub-clinically depressed individuals, and 48 non-depressed individuals. Participants from each group were randomly allocated to either the experimental or the control condition. In both conditions, participants read aloud scripted anti-depressive self-statements. Participants in the experimental condition received instructions to heighten the prosodic expression of conviction in their voice, whereas participants in the control condition received no such instructions. Separate classification models aimed at detecting current depression were trained for each condition and with a selection of different machine learning methods. RESULTS: We found that models trained on data from the experimental condition were more accurate and reliable than those trained on data from the control condition. While the former models reached balanced accuracies between 65–76%, the latter only reached balanced accuracies between 36–61%.DISCUSSION: Our results suggest that features of speech elicitation tasks have substantial influence on model performance for automated depression classification. The present findings highlight that speech elicitation tasks including voice modulation instructions can improve the validity and reliability of machine learning-based depression classification.
Improvements in stress-detection technology to improve the quality-of-life of people with challenging behaviour
Authors: Hulshof Tim , Chorbadzhieva Mila , Smits Reon , Meinders Erwin
Published: November 2024

In this paper we present two improvements to the ongoing development of a sock garment with integrated sensors for the monitoring of physiological signals. These signals are used for stress detection in people with intellectual disabilities and dementia in a long-term care (LTC) setting. The improvements discussed in this paper are both aimed at improving the quality of the measurements and improving the quality of care, especially in the context of challenging behaviour. In this paper we briefly present the following two improvements:1.A new electrode configuration that allows for predictive maintenance of the garment-part of the system.2.A new user interface, particularly an online dashboard, providing a tool set aligned with the needs of behavioural scientists.
Preferences of Elderly People in Western Taiwan towards Smart Sportswear
Authors: Huang Ying-Chia
Published: November 2024

This study was designed to determine the preferences of 300 elderly people in western Taiwan, aged 55 to 85, with regard to smart sportswear. It employed non-random sampling, in the form of a structured questionnaire, and an independent sample t-test, a single factor variance analysis, a post hoc test, and a chi-square test of statistical analysis to analyze the responses to the 16 questions. The research datasets were categorized based on gender, age, and exercise duration. The findings revealed that half sleeve and three-quarter sleeve tops were more commonly chosen by women than men, while shorter tops and trousers were more commonly chosen by men than women. In terms of color, men and women preferred blue and red, respectively. The majority of the participants reported the knees and ankles to be the most commonly injured body parts. They preferred to wear loose-fitting garments, crew neck tops, ankle-length trousers, hip-length garments, and short sleeve tops. However, only 8.7% of participants had experience wearing smart clothing. Fifty-six percent of participants expected to pay between 33USD and 166USD for smart sportswear.
Measurement of motivation and qualitative effects of physical effort during two motor learning sessions with multifaceted variation of goals, methods, measures and tools – example of violin playing and safe fall
Authors: Waszkiewicz Elizabeth , Kruszewski Artur
Published: November 2024

The purpose of this case study is to argue empirically about the similarities and differences of the indicators used to evaluate the motor learning effects of new motor competencies with distinct goals and in radically different educational settings. During 14 sessions of remote teaching and improvement of violin playing during the COVID-19 pandemic, a less than 13-year-old boy in the last semester of a six-year first-level music school was observed. Two 22-year-old female students (Girl1 and Girl2) and a 21-year-old male student (Boy) were observed during 8 sessions of a safe fall course (a mandatory subject in a physiotherapy degree program). The effects of the adolescent violinist's effort were evaluated three times during the session (in the beginning, middle, and end parts). The music teacher arbitrarily adopted five kinesiological criteria for evaluating movement characteristics: accuracy, rhythm, range, force, tempo. He combined each individually with artistic effects according to a 25-point scale. The highest arithmetic means of the evaluation scores of the violinist's joint motor and artistic activities were found during the 5th session, when he declared a self-motivation of 5 points. The most positive health effects of exercise of Girl1 and Girl2 are furthermore documented by the highest number of sessions (8 and 7 respectively, representing 87.5% and 75% of the observations) during which exercise was qualified to the high intensity zone. Elements of measuring physical exertion and motor effects with a component of either artistic or prevention component during motor learning in the areas of instrumental music and motor skills related to human personal safety (safe falling, avoiding collisions, self-defence, skiing, etc.) can be mutually implemented to the benefit of public health in particular.
Psychological and physiological effects of industrial noise: An applied study in the BMS ELECTRIC company in Algiers
Authors: Aissa Bayoub , Houda Falahi Wahiba
Published: November 2024

This study aims to identify the impact of industrial noise on workers psychologically and physiological.The psychological effects were measured by the following indicators (Behavioral symptoms, Cognitive symptoms, Psychosocial problems and difficulties).As for the organic effects were determined by the following indicators (Physiological symptoms, Auditory symptoms).The study was applied to the workers of BMS ELECTRIC Company in Algiers. In order to achieve the objectives of this study, we relied on the descriptive approach, and a sample was selected that included 46 workers in the company (manufacturing and assembly) in both branches of Bir Khadem for females and Baba Hassan for males.As for the tools used to collect data on this study, they are observation, questionnaire, interview, and a noise-measuring "sonomater".After measuring and statistically analyzing the data, these results were obtained:The workers are exposed to industrial noise [85dB-113,4dB] that exceeds the permissible limit according to the standards of the American Occupational Safety and Health Organization (OSHA).There is a strong correlation (0.72) between psychological symptoms (behavioral, cognitive, social) and the overall noise level at the significance level (0.05).There is a medium correlation (0.59) between organic symptoms (physiological, auditory) and the overall noise level at the significance level (0.05).
Analyzing Large Language Model Behavior via Embedding Analysis
Authors: Dey Sourya , Robinson Michael , Sweet Shauna , Lauziere Andrew , Daugherty Jonathan , Burgess Caitlin
Published: November 2024

The usage of large language models (LLMs) as a generative artificial intelligence tool is becoming increasingly widespread, yet there is limited understanding of the mechanisms by which prompts in whole or in part influence their behavior, capabilities, and limitations. In this paper, the authors conduct a mathematical and topological analysis of token embeddings – the first step in the computational workflow of LLMs. This work shows that the subspace where token embeddings lie is a stratified manifold with varying local dimension, and in those cases where semantically related tokens are co-located on a submanifold, there are non-trivial implications for model behavior. These topological and geometric findings help to explain performance aspects of different LLMs such as why the Llemma model is more likely to overfit than the GPT-2 model, yet the latter does worse at mathematical queries than the former. To the best of the authors’ knowledge, this paper is among the first to conduct such research into the topological characterization of the token embedding space and analyze LLM behavior starting from first principles.
Developing Building Information Relational Database (BIRD) as A Knowledge-Management System Prototype for General Contractors
Authors: Liu Di , Preston Robinson , Freeman Adrienne , Liu Rui
Published: November 2024

The construction industry increasingly demands efficient, cost-effective, and customizable project delivery, yet existing digital integration through Building Information Modeling (BIM) encounters challenges, particularly in achieving seamless cross-department and multi-platform collaboration. Addressing these challenges, this research introduces a Building Information Relational Database (BIRD) aimed at enhancing data interoperability and supporting tailored project delivery for general contractors. Despite the advantages of BIM, general contractor and design-build firms face persistent communication and data-sharing gaps caused by fragmented workflows and limited practitioner input in technology development, which impedes innovation adoption. Current standards like CSI MasterFormat and UniFormat often fail to accommodate the comprehensive needs across a project’s lifecycle. Objectives of this study are to develop a BIRD prototype with knowledge management (KM) attributes—such as standardization, flexibility, traceability, and self-learning—while integrating practitioner-centered insights to guide development. Employing a practitioner-centered, qualitative approach, the research synthesizes industrial standards and project data to establish KM foundations, integrated with expert input through focus groups, and iteratively refines the BIRD prototype with real-world testing. Findings reveal an exemplary BIRD prototype that enhances data interoperability and cross-department collaboration, aligned with construction standards, and adaptable to various project demands. By embedding expert knowledge into system design, this study not only addresses platform discrepancies but also establishes a KM-driven development model, reducing adoption barriers and fostering a more user-centered approach to construction innovation, thereby contributing a flexible, practitioner-informed tool that is relevant for current and future industry applications.
The Impact of AI on Business Ecosystem Development
Authors: Shvetsova Olga
Published: November 2024

The positive effects of AI implementation on the business ecosystem are manifold. AI-powered technologies enhance productivity and efficiency, automate repetitive tasks, and optimize resource allocation(Floridi, L., 2019). Furthermore, AI algorithms enable businesses to gain valuable insights from large volumes of data, leading to improved decision-making processes and the identification of new market trends (Martin, R., & McCrae, D., 2020). However, along with the promising prospects, there are notable concerns surrounding the implementation of AI in the business ecosystem. Ethical issues, such as privacy infringement and data security, arise due to the vast amounts of sensitive information processed by AI systems. (Davenport, T. H., & Ronanki, R. (2018). Furthermore, the concentration of power in AI technologies within a few dominant players can lead to challenges related to market competition and access to AI-driven solutions.This study combines a comprehensive review of existing literature with case studies and expert interviews to provide a balanced assessment of the impact of AI on business ecosystem development. By analyzing real-world examples and industry cases (e-commerce trade company "Coupang", South Korea; "Amazon", US; etc), this research aims to shed light on the practical implications of AI implementation and identify strategies to mitigate potential risks and challenges. To evaluate the effectiveness of the framework, a prototype mobile application was developed and tested by a group of participants with visual impairments. The evaluation process included usability testing, task performance assessments, and user satisfaction surveys. The results demonstrated improved accessibility and usability for participants, highlighting the significance of the user-centered design approach in creating inclusive mobile applications.The findings of this study will contribute to the ongoing discussions surrounding the integration of AI technologies in the business ecosystem. The results will be of interest to policymakers, business leaders, and researchers, providing valuable insights into harnessing the potential benefits of AI while addressing the associated concerns.
Sick Building Syndrome and its Relationship with Work Stress as a Psychosocial Risk: A Shopping Mall Example
Authors: Aytaç Serpil , Bülbül Şahamet , Gizem Akalp Husre
Published: November 2024

Recently, buildings, residences, plazas, shopping malls, skyscrapers and towers that have been rising all over the world have begun to form our living spaces as smart structures where private, social and business lives are carried out. The fact that these closed spaces threaten the health of people living and working in them and cause diseases, has led to these buildings being called "sick building syndrome (SBS)". Sick building syndrome results in the health of people who spend time and work in these buildings being affected both physically and psychologically. The aim of this study is to reveal the symptoms of sick building syndrome and its effects on stress, which is a psychosocial risk at workplace. A cross-sectional study conducted in two randomly selected shopping malls in Turkey involved 268 employees. Research findings indicate that employees suffer from symptoms like dry throat, runny nose, eye irritation, headaches, muscle-joint pain and fatigue. Additionally, it has been observed that these symptoms intensify during peak weekend traffic Moreover, the sick buildings phenomenon increases the stress levels of employees' due to the conditions associated with enclosed spaces.
Non-contact physiological monitoring of heart rate, facial temperature, and respiration rate with thermal and RGB cameras
Authors: Causse Mickael , Amdouni Nourhen , Ginés Rodríguez , Hurter Christophe
Published: November 2024

In this paper, we evaluated a non-contact physiological measurement technique using a thermal camera and an RGB camera aimed at the participant's face. The thermal camera effectively measured the temperature of specific facial regions, such as the tip of the nose, which is related to stress and mental workload. It also accurately measured respiration rate, which is an important indicator of mental state. On the other side, the RGB camera successfully measured heart rate by detecting subtle color changes in the face. However, the thermal camera was not effective in measuring heart rate, possibly due to a lack of thermal sensitivity and image resolution. Overall, our results confirmed that using thermal and RGB cameras can be a practical and discreet method for monitoring an individual's mental state. Additionally, these cameras can monitor movements and detect states of medical incapacitation, such as loss of consciousness.
Is Virtual Reality for Retail Marketing Research? Research Opportunities and Methods
Authors: Eun Lee Jung , Kwon Wi-Suk
Published: November 2024

Despite of popularities of virtual reality (VR), there has been limited studies adopting VR to investigate consumer behaviors in retail marketing settings. Thus, the objective of this paper is to propose two key areas of opportunities for VR research in the retail marketing discipline: 1) research with VR as a tool to examine consumer behaviors in VR replicas of physical stores and 2) research for VR as a new retail marketing context to investigate virtual consumption behaviors within entirely virtual worlds. Further, this study proposes using advanced VR-comparable or VR-based behavioral tracking technologies to measure consumer behavior and experience by capturing immediate, unintentional, and natural human responses, such as eye movements, facial expressions, and head motions. These direct measures can provide deep insights into consumer emotions, attention, and reactions, potentially uncovering the nature and process of consumer behavior and experience that have not been discovered by self-report methods alone.
Research progress, hotspots, and trends analysis of sustainable landscape design based on bibliometrics
Authors: Dai Jiejun , Fan Chen Yi , Qian Cheng , He Mengrun , Sun Feiran , Liu Suwen
Published: November 2024

In order to systematically understand the research characteristics of sustainable landscape design in the international scope, grasp the current research hotspots of sustainable landscape design, and analyze the future development trend according to the current research hotspots. Taking Web of Science as the source of literature data retrieval, VOSviewe and CiteSpace were comprehensively used to conduct scientific literature metrology and draw the knowledge map from the aspects of annual output distribution, country, research institution, author, keyword clustering and reference co-citation of literature within the scope of retrieval. Visualization and analysis of research context. The results show that the annual number of publications and the overall trend of literature within the scope of search are increasing, and China and the United States are in the leading position in the research field, and the research hotspots mainly focus on: urban landscape design, ecological protection design, theoretical methods and design evaluation.
FP ONLY:Towards Enhancing Awareness on Sustainable Development: A Survey of the Types, Functional Uses and Project-Level Applications of Geosynthetics
Authors: Kwaw Somiah Matthew , Aigbavboa Clinton , Bentil John , Didibhuku Thwala Wellington , Kwadwo Boateng Henry
Published: November 2024

Though geosynthetics are sustainable materials in the development of sustainable civil infrastructures, there is a low level of awareness among key stakeholders in the construction industry. Hence, the low project-level applications of geosynthetics globally. This desk study enhances the awareness level of geosynthetics among industry stakeholders as it seeks to give a more comprehensive literature account of geosynthetics highlighting the main types, functional uses, and project-level applications of geosynthetics in the development of sustainable civil infrastructures. The study employed the narrative literature review approach. The outcome revealed applications of twelve (12) main types of geosynthetics in the development of thirty-one (31) sustainable civil infrastructures. Project-level applications of geosynthetics included highways, ponds, airfields, and retaining structures. The main types of geosynthetics included geotextile and geomembrane. Primarily, the functional uses of the geosynthetics included soil reinforcement, stabilization, and filtration. This study informs stakeholders in the construction industry of the available geosynthetics that could be employed in the development of sustainable civil infrastructures. Also, it provides a more comprehensive basis for future country-specific studies that seek to evaluate project-level applications of geosynthetics in the development of sustainable civil infrastructures.
Self-efficacy and self-regulation variation in different modes of work
Authors: Okkonen Jussi , Laine Mia , Oksa Reetta , White Edward
Published: November 2024

The paper brings about the findings of a survey conducted in two Ghanaian universities during autumn and winter 2023. Relatively large sample (n=201) helps to shed light on sense of self-efficacy and self-regulation as outcomes of different modes of work. The working hypothesis was that sociotechnical environments are challenging due to issues with information ergonomics especially from the perspectives of users. Moreover, as more work is done in sociotechnical environments spatially dispersed and even asynchronously sense of control and self-regulation are affected. There is also an underlying question about the balance between work and life. Mixed domains are the cause of conflicts in several ways. The paper presents also implications for enhancing work life balance among the people working extensively in soctiotechnical environments.
Technostress and the future of work at sea
Authors: Lagdami Khanssa
Published: November 2024

The maritime industry has experienced profound technological change since the 19th century. Advancements such as big data analysis, artificial intelligence, and the Internet of Things have enhanced the functioning of ships by modernizing operation systems and making them safer and more profitable. Nevertheless, other than intensifying the efficiency of these systems, modern technologies have also brought numerous challenges to maritime workers. For instance, research shows that the rate at which technologies are implemented in ships and the stress a seafarer is exposed to learn the functionality of new technologies has impactful adverse effects on the mental health of seafarers, termed as technostress. This paper focuses on analyzing the technostress phenomenon in the maritime industry. Mainly, it concentrates on determining the effects of technological stress on seafarers' mental health on board ships. In addition, the paper seeks to investigate the status of the international legislation on technostress. Finally, since the future of the maritime industry is assumed to rely entirely on the modernization of the operations through technological advances, this paper seeks to create awareness among the maritime stakeholders about the existence of the phenomenon of technostress and proffer intervention approaches. The results presented in this article were obtained from a research field study, considered as the first of its kind in the topic of technostress, that the author conducted on a Newly built Danish-flagged commercial vessel.
An Interactive Virtual Assistant for Flexible Just-in-Time Training
Authors: Taylor Glenn , Craighead Jeffrey , Menefee Kortney , Lebanoff Logan , Ballinger Christopher , Mcgee Stephen
Published: November 2024

Many situations call for a person to perform tasks in which they are not an expert, and for which the person does not need (or want) to become an expert, but still needs to perform the task in the moment. Simple examples might include home maintenance tasks like changing out a furnace filter or car maintenance tasks such as refilling the wiper fluid. Performing the task might involve consulting a manual or searching the internet for relevant material. However, even when useful content is found, it’s not always easy to refer to these sources while simultaneously performing the task. Looking back and forth between a manual and the thing that needs fixing, or turning pages or typing on a keyboard when hands are occupied with tools makes the process more difficult. It can also be challenging to visually relate a diagram in a manual to the actual system being worked on, especially for non-experts. To help address these challenges, we have been developing an Autonomous Virtual Assistant (AVA) that helps someone perform a task by walking them through step by step. AVA can be thought of as an interactive helper working over the user’s shoulder to help perform the task, using different modalities and tools including mixed reality to convey information. This work has focused on being flexible to the user and the situation, both in terms of providing helpful information to the user and getting input from the user. Given a procedure, AVA determines on the fly how to present information based on what resources are available and what content needs to be conveyed. With a mixed reality setting, this might include showing text or imagery on a virtual heads-up display, or overlaying 3D imagery on the physical object being worked on to help orient the user. To make mixed reality content readily available, the system allows for easy ways of aligning 3D virtual models to the physical objects being worked on. In a situation where speech might be the only modality available, the system will read procedure steps to the user, or help the user navigate to a needed item using speech alone. To suit the user’s situation, the system also affords the user different interaction modalities, such as touching virtual buttons, pointing to objects in the real world, or using voice only in a heads-up, hands-free manner. The user moves through procedure steps and related information and asks questions if they need clarification or more detail. Example interactions include initiating a session (“Okay AVA, start the wiper refill procedure”), requesting visual material related to a task (“What does that look like?” or “Show me that image”), or asking for more information on procedure step (“How do I do that?”). AVA uses the content and resources at hand to help the user complete the procedure. In this paper, we describe the motivation for AVA, the system design, its application in some real-world tasks, user feedback from hands-on evaluations, and future directions.
Improved teaching and education of engineering students using computational fluid dynamics
Authors: Alnaimat Fadi , Mathew Bobby
Published: November 2024

This paper studies the use of computational fluid dynamics (CFD) to enhance students' understanding as an effective educational and learning method. The improved educational method studies the impact of CFD implementation in course project on students' comprehension and performance in fluid mechanics course. Implementing the CFD method is increasingly essential specifically for Mechanical Engineering students, and it can also be applicable to variety of fields, including Science, Technology, Engineering, and Mathematics (STEM). One of the most important improvements of using CFD in course teaching is the strong comprehension and improved students’ performance related to the fluid movements, frictional affect, pressure and velocity variation. This was evident through the strong interactive teaching in classroom. The use of simulation related to the studied fluid flow case has proven to be effective in enhancing student attention and improving their understanding of fluid mechanics.
Education and Training Using Digital Twin in Hazardous Chemical Manufacturing Plants
Authors: Shin Jihoon , Son Juhyung
Published: November 2024

Manufacturing industries face significant challenges in equipping new employees with the requisite skills to operate complex machinery, especially in hazardous sectors like chemical engineering. Traditional on-the-job training poses substantial risks and is limited by space and budget constraints, making it difficult for educational institutions to replicate industrial environments adequately. The acquisition and customization of equipment to meet diverse industry demands are prohibitively expensive, exacerbating these challenges. In response, Digital Twin technology offers an innovative solution. By creating virtual replicas of physical environments, Digital Twins provide a virtually boundless digital space at minimal operational costs. This technology enables avatar-based interaction and collaboration, bridging the gap between theoretical learning and practical industry practice. New employees and students gain immersive experiences that facilitate a nuanced understanding of complex industrial systems, ensuring a smoother transition into real-world work environments. This paper delves into existing theories and literature on Digital Twin technology, focusing on its implications for education and training. We introduce DTLAB, a bespoke digital twin framework tailored for hazardous chemical manufacturing plants. Leveraging cutting-edge technologies, including Virtual Reality (VR), the Internet of Things (IoT), Robotics, Data Technologies (DT), and an AI Virtual Chat-GPT Trainer (AIVCGT), DTLAB creates a hyper-realistic training environment. Participants engage with virtual replicas of chemical plants, benefiting from seamless data exchange between physical and virtual workspaces. Additionally, we employ the AIVCGT approach to evaluate users' learning efficiency and engagement levels within digital twin simulations. This research highlights the potential of Digital Twin technology to transform educational practices, empowering individuals to thrive in an increasingly complex industrial landscape.
Meeting practical requirements for assessing competencies: A framework for a multi-dimensional, layer-based and dynamic model
Authors: Jansing Steffen , Schallow Julian , Danhausen Paula , Schulte-uebbing Nele , Hoeborn Gerrit , Deuse Jochen
Published: November 2024

With digitalization and automation, today's economy is undergoing fundamental changes. Organizations are facing increasing complexity and dynamism, coupled with demographic shifts that require changing workforce skills and organizational flexibility. To ensure a sustainable competitive advantage, it is necessary to efficiently deploy employees based on demand. In addition, a method for early identification and targeted development of future competencies within an appropriate forecasting horizon is required. Building on theoretical foundations, this paper examines the practical challenges of describing and assessing competencies. It also examines the interrelationships between competencies and between competencies and external factors. The paper categorizes competencies based on hierarchical level and task composition, and examines relationships between competencies and external factors. It proposes a novel multi-dimensional, layered, and dynamic competency model as a holistic approach to competency management and forecasting. Finally, this paper outlines steps for validating and implementing the model, and assesses its potential for practical application in organizations navigating the evolving digital landscape.
Advancing Perspectives: A Scoping Review of Artificial Intelligence Applications in Aviation Human Factors for Flight Crews
Authors: Flores Abner , Paselk Alexander , Mcandrew Ian
Published: November 2024

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

Growing awareness of environmental issues and the constant pressure to reduce greenhouse gas emissions have prompted the automotive industry to research and develop sustainable solutions. Battery electric vehicles (BEVs) are considered as a key element in reducing dependence on fossil fuels and minimizing driving-related emissions from road transport. While technological innovation is driving the adoption of BEVs, range in relation to driving and operating strategies remain a fundamental challenge. One solution to this challenge is the application of so-called “eco-tips” in vehicles, which enable and support optimal human-vehicle interaction and thus guide the driver towards more environmentally friendly driving and operating behavior. Therefore, modern eco-tips approaches focus on increasing energy efficiency and maximizing range by striving for an innovative, human-centered design. Moreover, contemporary vehicles feature advanced recuperation systems capable of converting kinetic energy into electrical energy, further enhancing their eco-friendly credentials. Eco-tips encompass a spectrum of recommendations, ranging from fundamental behavioral adjustments like anticipating traffic flow to sophisticated real-time suggestions leveraging technological innovations. Drivers are encouraged to refine their driving styles by adopting smoother acceleration, maintaining consistent speeds, and maximizing the use of regenerative braking mechanisms. Despite the strides made in integrating eco-friendly features into modern vehicles, there remains untapped potential for enhancing the effectiveness of eco-tips and ensuring their seamless adoption by drivers without causing distractions or compromising safety. This necessitates the exploration of innovative approaches, such as user-friendly human-computer interfaces and gamification strategies, to incentivize eco-friendly driving practices and extend the range of electric vehicles. In this context, this study undertakes a comprehensive analysis of the underlying objectives of eco-tips, delves into the rationale behind specific recommendations, evaluates the current state of their implementation across vehicle platforms, and proposes a novel approach for developing an advanced, holistic, and adaptive eco-tips system tailored to individual drivers’ preferences and driving habits. By leveraging insights from human-computer interaction research, the proposed eco-tips system aims to enhance user engagement, facilitate seamless interaction between drivers and vehicles, and contribute to the broader goal of fostering environmentally sustainable mobility solutions.
Evaluation of the Risky Behaviors of AV Rideshare Vehicles in San Francisco
Authors: Nemire Kenneth
Published: November 2024

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