bluuebunny/crossref_metadata_2025 huggingface dataset:
Cognitive-oriented Process Information Presentation for Augmented Reality Assisted Product Assembly
Authors: Wang Junfeng , Shi Ting , Xiong Hui , Wu Lei , Lin Yufan
Published: June 2024

The information assistance during manual assembly process of mass customization production is indispensable in order to assure the assembly quality. The complexity of searching information and difficulty of understanding information brings about cognition burdens of workers under the varied and lengthy assembly process, where augmented reality (AR) can be an effective instruction tool. The cognitive issues of AR based information presentation for assembly guidance were discussed in this paper. The work about complexity of manual assembly process was analyzed both on error prediction and AR based cognitive perspective of visual assets. A four levels hierarchical task analysis was conducted for assembly process with three kinds of assembly stages, i.e. selection, installation and inspection. Cognitive reliability and error analysis method was taken to identify the possible human assembly errors during three stages considering the human cognitive activity and function. In order to provide right information at right place and right time for decreasing the assembly errors, the often used visual assets, i.e. 3D model, 2D annotation, text and video, were discussed for conveying assembly instruction intention in AR scenario. From the authoring complexity and potential cognitive efficiency aspects, different information presentation styles for three assembly stages were described.
Evaluating the Impact of Prosthetics on Gait Symmetry in Unilateral Lower Limb Amputees
Authors: Shi Gaby , Lun Yick Kit
Published: June 2024

Gait symmetry is a primary criterion for assessing the rehabilitation progress of unilateral transtibial amputees with prostheses. This study aimed to examine the gait symmetry of dynamic kinematic and kinetic functions in unilateral transtibial amputees using prostheses during walking. Methods The study was approved by the University Ethics Committee and involved five (3 females and 2 males) unilateral transtibial amputees (age: (mean ± SD) 63.4 ± 7.7 years, height: 165.6 ± 6.4 cm; body mass: 69.4 ± 4.1 kg; years of using prosthetic foot: 30.8 ± 9.3 years). For collecting the kinematic and kinetic data, thirty-nine passive-reflective markers were placed on the participant according to the landmarks set of the plug-in full body model. An 8-camera motion capturing system (VICON, Nexus 2.0 Inc., Oxford, UK) and 2 force plates (AMTI, Advanced Mechanical Technology, Inc., Watertown, USA) mounted under the walkway were recorded 100 frames per second simultaneously. All the systems were calibrated before the experiment. Participants walked at their self-selected walking speeds. Based on their self-selected walking speed record, ± 10% range were calculated as the references for each participant’s fast and slow walking speed. Each participant repeated walking trials until a minimum of 5 “clean” foot force plate contact with both right and left limbs were acquired. The corresponding data from 5 gait cycles were selected to calculate the lower limb joints angles and vertical ground reaction force (GRF) during walk. Then symmetry index (SI) was calculated to provide a descriptive marker for the degree of symmetry between the intact and residual limbs. A value of SI less than 5% reflects good symmetry between the limbs, whereas increasingly positive values indicate the value for the residual limb was greater than that of the intact limb, while negative values denote that the intact limb value was greater. Results Normalized vertical GRF of two limbs increased with increased walking speeds. The corresponding SI was the largest when heel strike with slow walking speed (6.2 ± 0.8 m/s). Gait imbalance was observed during loading response and midstance (around 30% - 45% stance phase) when the walking speed was increased. While SI values of ankle angles were enlarged with increased walking speed, indicating more asymmetry of ankle angle between two limbs with their traditional prostheses when the walking speed increases. Conclusions The current prostheses can only support the basic daily activities for the unilateral transtibial amputees. The new design of prostheses should therefore focus on kinetic and kinematic parameters such as the symmetry between the residual limb and the intact limb, and energy saving for the amputees during high intensity activities.
Challenges in Applying Human Reliability Analysis in Systems Containing Artificial Intelligence
Authors: Rasmussen Skogstad Martin , Boring Ronald , Hayes Jan
Published: June 2024

Can we use the same methods to analyze human reliability, if actions, tasks, and interactions change? This paper discusses three challenges of using traditional static human reliability analysis (HRA) on systems that include AI-elements: 1) how to incorporate and include AI in the quantification of human reliability, 2) how to apply HRA to changing tasks and working conditions, and 3) how to include indirect effects to human reliability.
Design and Development of Large Language Model Applied to Fashion Analysis
Authors: Fan Yiming , Wang Yinan
Published: June 2024

Consumer preferences and intense market competition are characterized by dynamic due to the rapidly evolving fashion industry. However, existing trend analysis tools do not fully exploit large datasets, resulting in a lack of precision and timeliness in trend prediction, and often fail to grasp the complex nuances specific to the fashion sector. To address this research gap, this study aims to develop a cutting-edge, AI-driven model for fashion trend analysis and prediction, leveraging the power of big data and advanced machine learning technologies. A mixed method of qualitative and quantitative methods was conducted in this study. To be specific, the latest fashion trend data from WGSN including terncolor trends, fabrics and materials, and market analysis were used to collect data. These data were undergone thorough cleaning and preprocessing using NLTK. After that, the LLAMA2-7B model was selected for pre-training, which was then fine-tuned using LORA technology. Finally,the performance evaluation of the model was rigorously evaluated using an independent test set. Metrics including accuracy, recall, and F1 score were computed to assess the model's effectiveness. In addition, a manual evaluation was conducted, focusing on the specific analytical requirements of the fashion domain to ensure the model's validity and applicability. Furthermore, a user-friendly interface was developed, enabling both technical and non-technical users to easily utilize the model for fashion trend analysis and prediction. This study not only enhances the accuracy and efficiency of trend analysis and prediction but also offers valuable market insights and decision-making support for fashion designers, brand managers, and retailers. This advancement marks a substantial step forward in data analysis and prediction methodologies within the fashion industry, paving the way for new perspectives and approaches in future trend analysis and market strategy formulation.
Integrating Episodic and Semantic Memory in Machine Teammates to Enable Explainable After-Action Review and Intervention Planning in HAA Operations
Authors: Davis Eric , Schleisman Katrina
Published: June 2024

A critical step to ensure that AI systems can function as effective teammates is to develop new modeling approaches for AI based on the full range of human memory processes and systems evidenced by cognitive sciences research. In this paper we introduce novel techniques that integrate episodic and semantic memory within Artificially Intelligent (AI) teammates. We draw inspiration from evidence that points to the key role of episodic memory in representing event-specific knowledge to enable simulation of future experiences, and evidence for a representational organization of conceptual semantic knowledge via self-organizing maps (SOMs). Together, we demonstrate that these two types of memory working in concert can improve machine capabilities in co-learning and co-training scenarios. We evaluate our system in the context of simulated helicopter air ambulance (HAA) trajectories and a formal model of performance and skill, with interventions to enable an AI teammate to improve its capabilities on joint HAA missions. Our modeling approach contrasts with traditional neural network training, in which specific training data is not preserved in the final trained model embedding. In contrast, the training data for our model consists of episodes containing spatial and temporal information that are preserved in the model’s embedding. The trained model creates a structure of relationships among key parameters of these episodes, allowing us to understand the similarity and differences between performers (both human and machine) in outcomes, performance, and trajectory. We further extend these capabilities by enhancing our semantic memory model to encode not just a series of episodes, but labeled directed edges between regions of semantic memory representing meta-episodes. These directed edges represent interventions applied by the performer to improve future episodic outcomes in response to identified gaps in capability. These interventions represent the application of specific co-training strategies as a labeled transition system, linking episodes representing pre-intervention and post-intervention performance. This allows us to represent the expected impact of interventions, simulating improvements and skill decay, providing the machine with team-aligned goals for self-improvement between episodes to positively impact future teamwork.
Usability Heuristic Review of an Intelligent Tutoring System Framework
Authors: Sinatra Anne
Published: June 2024

The Generalized Intelligent Framework for Tutoring (GIFT) is an open-source intelligent tutoring system framework software (Goldberg & Sinatra, 2023; Sottilare et al., 2017). GIFT can be used to create tutoring on a topic of the author’s choice, and does not require knowledge of programming to do so. The tutor can be primarily based on slideshows, or it can be more elaborate and include interactive simulations that are incorporated into the software. As GIFT is a research project, the development over the years has mostly been associated with the immediate feature needs to support specific projects. A heuristic review of GIFT’s Authoring tools was conducted and documented in 2016 (Ososky & Sottilare, 2016). However, there are a number of recent features, such as the data extraction tools that were designed for functionality, but have not recently gone through a usability heuristic review. This paper includes an overview of the GIFT data extraction interfaces, and through a usability heuristic review discusses if they align to traditional usability principles such as Nielsen’s 10 usability heuristics (Nielsen, 1994). For those items and interface elements that are inconsistent with general usability principles, suggestions on how to improve them are provided and discussed. The lessons learned and discussed from this paper are applicable for those who are developing similar systems with usability in mind. References:Goldberg, B., & Sinatra, A. M. (2023). Generalized Intelligent Framework for Tutoring (GIFT) SWOT analysis. In Design Recommendations for Intelligent Tutoring Systems: Volume 10-Strengths, Weaknesses, Opportunities and Threats (SWOT) Analysis of Intelligent Tutoring Systems (pp. 9–26). US Army DEVCOM Soldier Center.Nielsen, J. (1994, April). Enhancing the explanatory power of usability heuristics. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems (pp. 152-158).Sottilare, R. A., Brawner, K. W., Sinatra, A. M., & Johnston, J. H. (2017). An updated concept for a Generalized Intelligent Framework for Tutoring (GIFT). GIFTtutoring. org, 1-19.
Enhancing Body Ownership of Non-Human Avatars in Virtual Reality through Multimodal Haptic Feedback
Authors: Wang Ziqi , Gao Ze
Published: June 2024

With the rise of virtual reality (VR) and an increase in avatar options, there is a need to enhance users’ sense of body ownership when embodying non-human avatars. This research develops an integrated system using multimodal haptic feedback to strengthen feelings of embodiment for avian avatars in VR. A user study evaluates the approach through retractable bands guiding limb movements and inflatable cushions simulating environmental flight conditions. Results demonstrate moderately positive overall usability, with variable individual responses. Spatial haptics augmented realistic wing simulations for over half of the participants. However, limitations exist regarding personalized interactions and simulating comprehensive tactile sensations. This pioneering work contributes an innovative methodology for prototyping and assessing bodily transformations in virtual environments. It advances avatar embodiment knowledge by focusing on replicating the motor experiences of avian flight. The findings underscore the nuanced interplay between multiple sensory stimuli in immersive environments. Further refinements to this system may build empathy and connections with the natural world.
Exploring Simultaneous Localization and Mapping(SLAM) Technology for Complex Equipment Maintenance with the Perspective of Human-Machine Collaboration
Authors: Lin Hsiao-fan , Su Yong-siang , Cheng Chao-tse , Wang Chao-hung , Su Kuo-Wei
Published: June 2024

The rapid development of Augmented Reality (AR) and Mixed Reality (MR) technologies across various industries has intensified the need for advanced maintenance solutions in the context of the digital transformation of Industry 4.0. Taking the forming machine equipment in Taiwan's metal centre as an example. The declining birth rates and labor shortages makes it challenging for experts to be present on-site for timely repairs, leading to prolonged downtime and additional costs due to production line halts. This study aims to propose an MR-based maintenance guide, enabling on-site technicians to conduct repairs using digital technology even in the absence of equipment experts. By using head-mounted MR devices, technicians can instantly see system alerts and access 3D visualized step-by-step guidance, significantly improving repair speed and accuracy. This approach also reduces the need for expert travel, thus saving time and resources. More importantly, integrating Simultaneous Localization and Mapping (SLAM) technology ensures precise alignment between virtual and actual machine imagery, enhancing the accuracy of maintenance instructions and focusing on a human-centered experience. This technological innovation is not only applicable to forming machine equipment but can also be extended to other complex equipment maintenance fields requiring specialized knowledge. With the maturation of MR technology, this maintenance strategy is expected to become more prevalent in the future, promoting Industry 4.0's digital transformation in manufacturing.To achieve these goals, a systematic methodology was developed. Initially, the scope was defined, and the overall research process was planned during the preparation phase. The literature review phase involved an in-depth investigation into the development of head-mounted MR devices in various settings and the exploration of their application possibilities. Literature about remote collaboration was also reviewed to understand the technical requirements and limitations of this mode. Therefore, SLAM testing with Microsoft HoloLens2 in an indoor factory setting was conducted to evaluate its effectiveness in aligning virtual and physical machinery models. Finally, system development and testing were undertaken using Unity3D and Microsoft's Mixed Reality Toolkit (MRTK) to implement the MR device functionalities on-site. Overall, this methodology aims to comprehensively consider the application of digital technology in industrial maintenance to enhance efficiency and accuracy.This research has yielded several significant findings, including valuable perspectives on SLAM technology. It also sheds light on the performance capabilities of HoloLens 2 in industrial environments, particularly regarding system operation processes.
Harnessing Growth-Mindedness to Enhance Organizational Effectiveness
Authors: Lenchner Jonathan , Topol Anna , Sabath Mariusz , C. Anderson Laura
Published: June 2024

We consider the organizational and individual benefits of implementing activities focused on increasing employee growth mindedness within a global Fortune 500 organization, with the objective of enhancing organizational effectiveness and employee retention. Growth Mindset Theory, pioneered by Stanford psychologist Carol Dweck, focuses on promoting an environment of continuous learning and openness to growth and change. Mindset theory, more broadly, posits that there are two essential mindsets, or frameworks, from which we operate: a “fixed mindset” where one believes that ability is predominantly innate and a “growth mindset where one believes that ability is in large part learned. We examine the dynamic of instilling a growth mindset within an organization, and the activation effect of injecting growth mindset-focused activities within a larger employee engagement initiative.Selected ReferencesCaniëls, M. C., Semeijn, J. H., & Renders, I. H. (2018). Mind the mindset! The interaction of proactive personality, transformational leadership and growth mindset for engagement at work. Career development international, 23(1), 48-66.Cutler, S., Xia, Y., & Beddoes, K. (2022). A Growth Mindset for Peer Review: Guidelines for writing constructive peer reviews. Conference Proceedings Hawaii International Conference on Education. https://par.nsf.gov/biblio/10378438Dweck, C. S. (2019). The Choice to Make a Difference. Perspectives on Psychological Science, 14(1), 21–25. https://doi.org/10.1177/1745691618804180Dweck, C. S (2016). Mindset: The New Psychology of Success. How We Can Learn to Fulfill Our Potential. Ballantine Books, New York.Dweck, C. (2014). Talent: How companies can profit from a "growth mindset". Harvard Business Review, 92(11), 7.Dweck, C. S., & Hogan, K. (2016). How Microsoft uses a growth mindset to develop leaders. Harvard Business Review, 1–4.Fulmore, J. A., Fulmore, A. L., Mull, M., & Cooper, J. N. (2023). Reducing employee turnover intentions in the service sector: The connection between human resource development practices and employee engagement. Human Resource DevelopmentQuarterly, 34(2), 127–153.
Development of food bank data visualizations using eye tracking
Authors: Jiang Steven , Ivuawuogu Henry , Milad Javadi Amir , Hamilton Mikaya , Davis Lauren
Published: June 2024

Food banks are key players in the fight against hunger. The complexity of the food bank operations data makes decision-making very challenging. Data visualization can allow food bank operations managers to quickly and easily understand the data and make evidence-based decisions. However, poorly designed visualizations could be confusing and/or misleading. This study uses eye-tracking technology to understand how users interact with various food bank data visualizations and use eye-tracking data to better design those visualizations. The findings of this study will have an impact on improving the effectiveness and efficiency of the food bank operations.
Industry and Academia Collaborative Learning: The CSULB and ISSIP AI Collab Pilot Program
Authors: Satterfield Debra , Chang Jen-mei
Published: June 2024

This paper is an analysis of the case study of an industry-academia collaboration between the International Society of Service Innovation Professionals Academic/Industry Collaboration (ISSIP AI COLLAB) and a senior UX design course at California State University, Long Beach. The ISSIP AI Collab Pilot Program was launched in Fall 2023 with four participating academic partners; San Jose State University, California State University, Long Beach, Pennsylvania State University, and the University of Washington. The pilot program included both graduate and undergraduate participants from programs ranging from service systems engineering to design. The ISSIP AI COLLAB program is designed to engage ISSIP institutional members with faculty and students from leading educational institutions in value co-creation and exploration of the capabilities of generative AI in an analysis of historical service systems. This case study discusses the design of an academia and industry collaboration course including teaching strategies, course management, project scope, and deliverables from the CSULB and ISSIP AI COLLAB project, “Harms and Benefits Analysis of Historical Service Systems Innovations Using Generative AI.” (https://issip.org/ai-collab-offering-participating-universities/). This case study discusses the course description, project definitions, scope, and evaluation strategy of the ISSIP AI COLLAB Pilot Program.
On the use of Verb for Micro Interactions in UI
Authors: Owa Shunsuke , Yang Wonseok
Published: June 2024

With the shift to an online-centric living environment, users are increasingly utilizing digital devices to search for information and decide. Users are often at a painful point when accessing content and functions because of unclear interactions with the system or delayed reactions, preventing them from using the system as they wish. Therefore, to improve the usability of services, methods must be devised for rapid recognition of the UI. The use of dynamic elements in the UI can quickly convey feedback and status changes to users to decide intuitively. Based on the current survey, many Micro Interactions often use animation to physically differentiate UI from other UI and information, such as zooming in and out, contrast, movement, and color change. However, current Micro Interactions lack clear rules and are considered dependent on the skills of designers when creating them. In this research, we considered that user perception could be influenced by utilizing the dynamic characteristics of Micro Interactions, focusing on verb that express the movement of objects and human actions based on the images that language has to offer. This experiment yielded the following analysis of the images of the movement of objects and people. The results were classified into two broad categories: those in which the subjects had a common perception of the dynamic image recalled from the verb and those in which the subjects did not have a common perception of the verb, and variations existed in the motion recalled. Each was characterized by differences in whether the verb itself contained the meaning of a vector or context.
Designing hybrid intelligence: understanding the impact of human decision-making on AI
Authors: Kessler Melanie , Antons Oliver , Arlinghaus Julia
Published: June 2024

In many domains such as management, production and government, established control approaches struggle to address increasing complexity in a timely manner, resulting in a demand for more agile methods. Hybrid intelligence and decision support systems are useful approaches to augment human decision-making through artificial intelligence (AI). Various application of AI methods to estimate production parameters or to provide forecasts are discussed in the literature or already being implemented, however, human decision-making is still required for either deciding whether to follow specific suggestions or for monitoring their respective implementation. But human behavioral research has shown that human decision-making is rather biased than fully rational, leading to unintended consequences in the collaborative work of humans and machines. Subsequently, the research stream of hybrid intelligence has gained interest recently, aiming to study the collaboration between humans and machines. We contribute to this issue by combining a systematic literature review on AI and cognitive biases combined with practical insights from discussions with experts in order to derive first guidelines addressing the human factor in the design of AI-based decision support systems for complex production environments.
Innovating ceramic products through digitalization and additive manufacturing: two Made in Italy case studies
Authors: Goretti Gabriele , TERENZI BENEDETTA
Published: June 2024

The research addresses contemporary trends in the ceramic sector in Italy, emphasizing formal, emotional, and functional innovation through the application of digital tools in two case studies. The digital transition in the Italian manufacturing sector involves multiple aspects, such as the automation of production processes, the adoption of advanced technologies, the digitization of supply chains and the implementation of artificial intelligence solutions. The adoption of advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI) and augmented reality (AR) is also becoming increasingly common in this in the context, enabling real-time data collection and analysis, process optimization, improved product quality and, in general, improved efficiency and innovation.Therefore, in both case studies, the goal is to demonstrate the development possibilities of new formal and chromatic solutions for ceramic artefacts, facilitating new product customization models, emotional values and functions.
Daily Multidimensional Fatigue Scale and Physiological Indicators to minimize Subjective Bias in assessing Fatigue Levels
Authors: Lee Yongkyun , Park Hyesu , Kim Sitai , Lee Younggun , Yoo Seunghoon , Kim Sungho , Oh Choongsik , Yun Hyesik , Ko Joonghoon , Ha Jongwoo , Kim Dongsoo
Published: June 2024

Fatigue is a human factor that can diminish task efficiency and serve as a potential cause of safety incidents. The specific aim is to investigate the removal of subjective bias in fatigue assessment with the daily multidimensional fatigue inventory (DMFI), covering acute, cumulative, physical, and mental fatigue. Additionally, the goal is to investigate the elimination of residual subjective bias after DMFI using physiological indicators, the Psychomotor Cognition Test (PCT), salivary CRP, blood lactate, and salivary cortisol, related to each type of fatigue. The DMFI significantly classified daily fatigue into 5 levels (p<0.001). As the level of fatigue increased, the reaction time of PCT slows down, and the success rate decreased. PCT alone was not sufficient for classifying fatigue levels. However, PCT could possibly serve as a tool for data refinement, eliminating some subjective bias in self-reported fatigue levels. The levels of blood lactate showed a positive correlation with the increase in fatigue levels. Especially in groups with high levels of physical activity, the concentration of blood lactate can be utilized as a tool to eliminate subjective bias, and it was found to be useful in classifying fatigue into binary or 3 levels. Salivary CRP, representing cumulative fatigue, had some utility as a tool to track subjective bias in participants, specifically in office work where cumulative fatigue levels were relatively low. Salivary cortisol, representing mental fatigue, was found to be unsuitable as an indicator for tracking fatigue levels in mentally healthy participants. The accumulated data here will be utilized for the training of a deep learning-based fatigue level classifier.
Detecting High-Risk Fatigue: Tracking with Alertness and Physiological Metric Pattern
Authors: Lee Yongkyun , Park Hyesu , Yoo Seunghoon , Kim Sungho , Ko Joonghoon , Ha Jongwoo , Kim Dongsoo
Published: June 2024

Fatigue is a recognized factor contributing to safety incidents and reduced task performance. However, classifying fatigue levels among workers in the workplace is a challenging task due to its subjective nature. This study aimed to establish universal criteria for identifying high-risk levels of fatigue. Industrial settings commonly use risk management checklists for this purpose. This study analyzed the correlation between fatigue levels and physiological indicators associated with fatigue, including alertness levels. The alertness levels were measured by the psychomotor cognition test (PCT), and the physiological indicators included salivary C-reactive protein related to cumulative fatigue, blood lactate concentration related to physical fatigue, and salivary cortisol associated with mental fatigue. Subjective fatigue levels were categorized into five levels, with Level 1 representing optimal mental and physical conditions and Level 5 indicating severe fatigue. Results showed that the mean reaction time in PCT at Level 5 significantly increased, and the success rate sharply decreased, demonstrating a significant difference compared to Levels 1 and 2 (p<0.01). Blood lactate levels were exhibited a positive correlation with fatigue levels, sharply increasing from Level 4. Blood lactate levels in Levels 4 and 5 were significantly higher than those of Levels 1 and 2 (p<0.01). Salivary C-reactive protein (CRP) levels were also showed a rapid increase from Level 4, significantly higher than those of Levels 1 and 2 (p<0.001). Salivary cortisol concentration at Level 5, however, was relatively lower compared to those of Levels 1-4. In conclusion, cumulative fatigue and high-risk levels of fatigue due to excessive workload are reflected in vigilance tests and physiological indicators. These indicators can be valuable in reducing subjective biases when assessing fatigue levels. The study suggests that profiling vigilance tests and physiological indicators associated with fatigue can be employed to screen for high-risk fatigue levels.
Musculoskeletal Disorders Among Construction Workers
Authors: Ngxesha Simamnkele , Deacon Claire , Smallwood John
Published: June 2024

Construction is a physically demanding process, and its activities entail exposure to a range of health and safety (H&S) and ergonomics hazards and risks. Given the persistence of H&S and ergonomics hazards and risks, a quantitative study was conducted to interrogate the related issues and evolve a response. The quantitative study included members of the Association of Construction Health and Safety Management (ACHASM) who completed a self-administered questionnaire delivered per e-mail. The findings indicate: workers are exposed to ergonomic hazards and risks, which leads to musculoskeletal disorders (MSDs); workers do report incidents; not all stakeholders are likely to be committed to H&S, and seven construction management factors impact H&S and ergonomics. Conclusions include: design hazard identification and risk assessment (HIRA) and construction HIRA is ineffective; exposure to ergonomic hazards and risks results in MSDs; workers do not fear losing their jobs due to reporting incidents; construction H&S is not receiving the necessary and potential multi-stakeholder support, and contractors are not adequately resourcing H&S and ergonomics. Recommendations include: multi-stakeholder commitment to and support for H&S and ergonomics should be engendered commencing the client brief; designers should consider the impact of design, details, and specifications on construction H&S and ergonomics during the construction process and subsequent maintenance; contractors should adequately resource H&S and ergonomics at tender stage, and ensure that the requisite H&S systems, procedures, and protocols are implemented when construction commences, and workers should be empowered through HIRA training, and participation in H&S processes.
Scientific Evaluation of the Impact of an Increase in the Retirement Age on the Cognitive Functions and Well-Being of Air Traffic Controllers (ATCOs)
Authors: Baumgartner Marc , Cabon Philippe , Drogoul Fabrice , CAUSSE Mickael , Imbert Jean-paul , Mouratille Damien
Published: June 2024

In 2020, the Swiss Federal Council made it a strategic objective to encourage Skyguide (Switzerland’s private air navigation service provider) and social partners (HelvetiCA) to work together to raise the retirement age from the current 56/59 to at least 60. In this context, HelvetiCA and Skyguide agreed to carry out a scientific study (RAFA study) to assess the possible impact of this increase in age, in particular on the psychological well-being and cognitive performance of ATCOs. Two studies were carried out following a review of the literature. The first study aimed to identify the factors relating to working conditions, individual characteristics and coping strategies that may be affected by ageing and sought to assess whether these factors have an impact on the ability to perform operational tasks according to the demands and conditions of the job carried out by ATCOs. The second study aimed to assess the cognitive functions of ATCOs of different ages using a battery of neuropsychological tests to examine the impact of ageing on cognitive performance, a crucial aspect of air traffic control activity. After a 13-month study period, a final report containing 17 recommendations was submitted to HelvetiCA/Skyguide. Within the context of the Collective Labour Agreement agreed in January 2024, the social partners agreed to implement the recommendations to help HelvetiCA and Skyguide manage this change safely and efficiently, with a transparent programme.
Combining Internal and External Communication: The Design of a Holistic Human-Machine Interface for Automated Vehicles
Authors: Verstegen Rutger , Gao Ruolin , Bernhaupt Regina , Bazilinskyy Pavlo , Martens Marieke
Published: June 2024

In this paper, we explore the field of holistic Human-Machine Interfaces (hHMIs). Currently, internal and external Human-Machine Interfaces are being researched as separate fields. This separation can lead to non-systemic designs that operate in different fashions, make the switch between traffic roles less seamless, and create differences in understanding of a traffic situation, potentially increasing confusion. These factors can limit the adoption of automated vehicles and lead to less seamless interactions in traffic. For this reason, we explore the concept of hHMIs, combining internal and external communication. This paper introduces a working definition for this new type of interface. Then, it explores considerations for the design of such an interface, which are the provision of anticipatory cues, interaction modalities and perceptibility, colour usage, building upon standardisation, and the usage of a singular versus a coupled interface. Then, we apply these considerations with an artefact contribution in the form of an hHMI concept. This interface communicates anticipatory cues in a unified manner to internal and external users of the automated vehicle and demonstrates how these proposed considerations can be applied. By sharing design considerations and a design concept, this paper aims to stimulate the field of holistic Human-Machine Interfaces for automated vehicles.
Exploring the Effects of Interior Design Elements on the Uncertainty of Passengers of Fully Automated Cars
Authors: Franssen Mervyn , Dong Haoyu , Verstegen Rutger , Martens Marieke
Published: June 2024

Humans are masters in predicting each other’s behaviour and acting relatively appropriately in ambiguous and uncertain situations. Although road accident statistics show a slight decrease in the number of road traffic deaths, these numbers are still very high. Fully automated cars are said to offer the potential to bring everyone everywhere, avoid accidents, and save parking spaces. This does not mean that the objective benefits of fully automated cars are also perceived this way by society. We may feel uncertain about the intentions, behaviour, and reliability of these fully automated cars. Our uncertainty influences our behaviour and interaction. Uncertainty can alter our mental state and, thus, our behaviour. Uncertainty further shapes perceptions of and interactions with fully automated cars. People mustn't feel uncertain about the capability of the fully automated car to prevent misuse. Interior design could play a role in mediating the uncertainty that passengers of fully automated cars perceive. A study was conducted to explore the effects of interior design elements on the uncertainty of passengers of fully automated vehicles. Results of the conducted study, with 113 participants, indicate that factors such as familiarity, trust, and perceived control are significant considerations when addressing perceived uncertainty through interior design. Furthermore, the introduction of unfamiliar design elements and perceived loss of control may lead to an increase in feelings of psychological uncertainty.
The role of users' privacy concerns in the decision for smart battery electric vehicle charging
Authors: Günther Madlen , Kämpfe Bettina , Krems Josef
Published: June 2024

As the availability of electricity from renewable sources in the power grid can fluctuate greatly, smart charging of battery electric vehicles (BEVs) is an effective approach to balance the grid. However, user centred smart BEV charging requires detailed settings of the BEV drivers’ mobility and consumption needs as well as the collection and processing of personal data. This may lead to privacy concerns among users and reduce their willingness to use smart BEV charging. Thus, the aim of the present study was to investigate the role of users’ privacy concerns in the decision for smart BEV charging. To this end, an online questionnaire study with N = 103 participants was conducted in Germany in 2023. The sample consisted of 62 women and 41 men, with an average age of 31 years (SD = 15.52; Min = 18 years; Max = 67 years). Participants were well educated and had on average 3,625 km driving experience with BEVs (SD = 7,397.13; Min = 0 km; Max = 38,000 km) within the last 12 months. Results revealed that smart BEV charging was perceived as significantly more critical in terms of data disclosure as conventional charging (p ≤ .043). The possibility of unauthorized persons gaining access to personal data was rated as the highest risk followed by the identity of possible data recipients compared to the possibility of data loss (p < .01). Further, participants’ perceived criticality of data disclosure significantly predicted their willingness to participate in smart BEV charging when controlling for participants BEV driving and charging experience (Radj2 = .075, F(3,102) = 3.8, p = .013). Within this study, we provided first empirical evidence that participants’ concerns regarding privacy emerged as a potential obstacle to their willingness to engage in smart BEV charging practices. Finally, we show strategies for reducing privacy concerns and increasing the willingness to participate in smart BEV charging.
EEG-based Prediction of Driver Takeover Performance
Authors: Huang Jinhui , Zhang Tingru
Published: June 2024

In the context of conditional autonomous driving, ensuring a safe takeover is of paramount importance. While previous studies have delved into factors influencing drivers’ takeover performance, there remains a gap in research concerning the development of performance models capable of predicting takeover quality. To address this challenge, this study focuses on predicting driver takeover performance before the issuance of a takeover request based on Electroencephalogram (EEG) features. For this purpose, 72 subjects were recruited to participate in a driving simulation experiment, responding to a total of eight takeover events. Both their EEG signals and driving performance data were recorded. The takeover performance was subsequently categorized as high, medium, or low quality through a subjective review of the takeover process videos. A total of 480 EEG features, such as the power of α band, were extracted. Five machine learning models: Decision Trees (DT), Support Vector Machine (SVM), Random Forest (RF), Light Gradient Boosting Machine (LightGBM), and Multi-layer Perceptron (MLP), were utilized to develop the takeover performance prediction models. The results showed that the LightGBM model outperformed others, achieving an accuracy of 84.2% and an F1 score of 83.0%. In contrast, the DT model demonstrated the lowest performance, with an accuracy of 59.4% and an F1 score of 57.8%. This study underscores the potential of machine learning models in predicting driver takeover performance, thereby contributing to the advancement of machine learning applications in the field of autonomous driving.
The impact of secondary in-vehicle display animations and their location on driver attention and glance behavior
Authors: Befelein Dennis , Purucker Christian , Schewe Frederik , Dostert Janik , Neukum Alexandra
Published: June 2024

This driving simulator study explores which kind and amount of non-driving-related animations can be implemented in cars’ front displays without causing significant driver distraction. While in recent years, a large amount of research has been conducted on how driving-relevant information must be displayed to capture the driver’s attention, the question on how non-driving-related animations can be conveyed in front displays without compromising the driver’s attention has rarely been addressed. However, due to the omnipresence of digital displays in present-day vehicles combined with observable efforts of vehicle manufacturers to increase the visual design appeal, the topic currently gains practical relevance. N = 53 participants were presented 16 animations that differed in stimulus salience features like fade-in time, brightness, target color, as well as internal and external movement. These animations were either displayed in the Cluster display or in the Central Infotainment Display (CID) and they were all irrelevant to the three driver tasks: To follow a lead vehicle (Car Following Task), perform a visual Detection Response Task (vDRT) and, optionally, react to a small set of driving-relevant info texts. In Test Drive 1, texts appeared in the Cluster only, whereas Test Drive 2, they appeared in both the Cluster and the CID. This was done to alter the task relevance of the two locations. Although a general effect of animations on vDRT performance could be observed across all study parts, this was with the exception of slow fading-in animations and other factors such as reduced brightness, target color, and the object size in the animation. Additionally, in Test Drive 1 a location effect could be observed: Animations displayed in the Cluster display led to a reduced vDRT performance when compared to animations that were displayed in the more distant CID. This effect disappeared when driving-relevant information texts were introduced to the CID in Test Drive 2. Taken together, visual attention was more vulnerable to animations of increased salience and to animations at lower-effort locations - an effect that can be moderated when the value of a more distant location is increased. The resulting design recommendations may be used to consider the risk of distractive features throughout the whole design process of in-car animations, reducing development costs, maximizing driving safety and providing a positive user experience.
The human element in data driven decision making for winter navigation
Authors: Musharraf Mashrura , Liu Cong
Published: June 2024

With the availability of big maritime data and advancements of the computational techniques, such as machine learning and AI, automation of navigational decision-making in ships is on the rise. For low risk and more frequently observed cases, such as local vessels operating in calm sea, abundant data facilitates straightforward automation. The traditional data driven modeling (including black-box models) and associated validation techniques suffice the automation process of these cases as human intervention is rarely needed. However, for high-risk and infrequent scenarios, like winter navigation, data may be scarce, sparse, or imbalanced. Black-box data-driven models and associated validation techniques prove insufficient in these cases, as the expectation is for human to jump in and take control over when needed. This paper explores the role of the human element in various stages of data driven decision-making for winter navigation, encompassing the establishment of a multipurpose winter navigation database, model development, and validation. To illustrate, a case study on ice-breaker assistance operations will be presented.
Enhancing Scenario Design in Maritime Education and Training
Authors: Harrington Susan
Published: June 2024

Within maritime education and training, the value of simulator-based training has long been recognized. Simulation is a powerful tool in providing students with immersive and experiential opportunities in practicing complex professional tasks in a controlled environment. In an industry where mistakes can have catastrophic consequences, the importance of providing students with an education which focuses on good seamanship, rather than simply training individual skills, is evident, with strong emphasis on training competencies such as communication, collaboration, and decision-making. Much focus in existing literature is placed upon factors such as the fidelity of the simulator and the role of the instructor during the simulation, for example, but very little has been published around the design of the scenario exercises themselves. This gap in understanding what constitutes a well-designed scenario, and the process involved in effective scenario design is addressed by this study. Semi-structured interviews have been conducted with experienced instructors from a range of institutions across Sweden, Norway, Finland, and the Netherlands. The goal of the interviews was to uncover valuable insights into the process of designing and developing scenario exercises, focusing on the key considerations that contribute to the success of such training programs. While the initial aim of the study was to develop a systematic approach to scenario design, the findings also revealed some key concerns that provide more in-depth insight into the complexity of good scenario design. Instructors emphasize the need for scenario exercises that not only mimic real-world situations, but also align with specific educational objectives. This highlights the importance of designing scenarios that accommodate the varying levels of knowledge and experience found in a group of students. The scenarios must be both concrete enough to ensure the objectives are met, and flexible enough that the instructor can cater to these individual student needs. In addition to the specific skills being trained, the scenario must be designed in a way which further embeds the non-technical skills, such as communication, teamwork, and reflexivity, central to good seamanship. Through increasing the understanding of effective scenario design, this study aims to contribute to the existing body of knowledge on simulator-based maritime education and training. The use of a recognized instructional design model, developed for training complex tasks, is recommended as complementing the existing approach taken by simulator instructors, formalizing their current practice, and providing a much-needed resource in the form of a systematic approach that captures the nuances of the instructors’ experience.