bluuebunny/crossref_metadata_2025 huggingface dataset:
Advanced Numerical Simulations For Seakeeping Performance Analysis Of A Floating Architecture Based On Textile Structure
Authors: Gabriela Ene Alexandra , Mihai Carmen
Published: November 2024

The paper presents the results of the seakeeping performances on the regular wave through advanced numerical simulations of a floating unit intended for the capture, storage and transport of hydrocarbons. The behavior of the floating unit in a frontal regular wave with a height of 0.6 m and a length of 5.3 m was investigated, at speeds of 0 and 2 knots, considering the 3 drafts corresponding to the cases of loading with 75%. The numerical tests were based on solving the RANS equations. For the qualitative investigation of the hydrodynamic characteristics of the flow in a regular wave, the free surface and the analyzed architecture were represented at different time steps for the stationary ship and at the speed of 2 knots. Based on the results of the short-term seakeeping analysis, to avoid complete immersion of the floating unit, the most significant restrictions on navigation with 75% hydrocarbon loading were determined.
Impact of Audience Presence on Pressure and Running Performance: The Potential of AR Presence
Authors: Gong Ziting , Kanai Hideaki
Published: November 2024

This study investigated the impact of audience presence on the experience of running on a treadmill by specifically examining perceived pressure, calorie expenditure, and heart rate. The primary objective was to understand how various types of audiences—live audience, video call, augmented reality (AR) characters, and no audience—affect runners' performance and psychological states. By exploring these scenarios, this study identified the role of audience presence in influencing exercise outcomes. The significance of this study lies in its potential to enhance exercise interventions and promote long-term commitment to physical activity. By leveraging AR technology, our results may contribute toward managing pressure and improving performance by offering innovative solutions to support both physical and mental well-being in the exercise context.
Design of a Smart Interactive System for Pet Dogs from the Context-Aware Perspective
Authors: Ding Xuan , Hu Xin
Published: November 2024

With the constant advancement of technology and social development, the demands for pet dog care have been growing significantly, leading to a pressing need for intelligent and personalized solutions. This article aims to explore a smart proactive interaction system that integrates context-aware theory, designed specifically to meet the daily care needs of pet dogs.At the outset of the research, an exhaustive literature review was conducted to establish a clear understanding of the fundamental concepts and design principles of context-awareness. Subsequently, through in-depth social background research and user interviews, a user journey map was constructed, providing a comprehensive analysis of the daily routines and health requirements of pet dogs. These analyses offered valuable insights into the habits and preferences of both the pets and their owners.Based on these insights, an intelligent system grounded in context-aware principles was developed. This system possesses the capability to monitor the physiological state, behavior patterns, and location information of pet dogs in real-time, while actively offering interactive functional services tailored to the pet's specific needs. Additionally, a complementary application was designed for pet owners, providing precise health monitoring reports, behavioral analysis, and location tracking services. This comprehensive approach ensures that pet owners remain informed about their pet's well-being, while fostering deeper emotional bonds between the pet and its owner.The integration of various interactive features within the system facilitates seamless communication between pets and their owners, promoting not only the physical and mental health of the pets but also enhancing the emotional connection with their owners. This research provides a novel perspective for the design of smart service interaction systems for pet dogs, and serves as a practical reference for the application of context-aware technology in intelligent service systems. It opens up new horizons for future pet care solutions, paving the way for more intuitive and compassionate approaches to pet care.
My tool my rule:User-Participatory Design of an Angle Grinder
Authors: Zhao Yiwei , Yang Mengshi , Hu Ruchen
Published: November 2024

As a tool primarily designed for grinding, angle grinders are extensively used by workers in processing and maintenance tasks. However, using angle grinders for cutting purposes is not compliant with safety regulations, yet this practice is widespread. This misuse imposes significant wrist strain and safety hazards on workers. Existing tool designs often prioritize technology or market demands, frequently neglecting workers' needs and considerations for ergonomics and user experience.This study conducted multiple rounds of experiments and collaborated with users to advance a design plan for an angle grinder. We interviewed angle grinder users from various professions and observed their work processes, discovering numerous ergonomic issues in the actual use of angle grinders. Based on the forces exerted during operation, we proposed three new gripping methods to make the angle grinder suitable for both cutting and grinding. These methods were tested with users, leading to the creation of more detailed models to refine the mode-switching mechanism. This iterative process incorporated new user feedback into the design and resulted in the production of a prototype. The prototype was provided to 12 users for evaluation, and the scale results showed that the angle grinder designed with user participation significantly enhanced the user experience compared to traditional angle grinders.Based on this case, we developed a user-centric tool design methodology. This method begins with observing and interviewing users to extract their needs, followed by initial modifications to existing tools and seeking user feedback. The next steps involve integrating this feedback into design and structural development, conducting multiple rounds of discussions with users to adjust the design, and finally inviting users to evaluate the design outcome. Implementing this method requires detailed communication, extensive real-world experiments, and rigorous evaluation and collaborative decision-making. This approach finds a balance between practical conditions and users' ideal usage patterns, leading to more ergonomic design results. It enhances the user experience while providing new insights for designers and engineers.This user-centric design methodology emphasizes deep user involvement throughout the design process. By bridging the gap between actual working conditions and users' needs, it offers a new perspective on tool design that prioritizes ergonomics and user satisfaction. This method can lead to innovative solutions that improve the usability and safety of tools, ultimately benefiting both workers and the design community.
How User-Platform Interactions Influence Continuance Intention in Augmented Reality Mobile Platforms
Authors: Kabir Zian , Kang Kyeong
Published: November 2024

When we interact with mobile platforms in an augmented reality environment, it changes our cognitive and emotional engagements through different stimuli cues that respond to our behavioral intentions. The effects of those engagements through augmented reality, considering user-platform interactions, are unexplored. This study investigated a nuanced understanding of how stimuli cues in augmented reality affect sense of immersion and sense of presence, followed by an interaction-engagement-intention (I-E-I) model. A quantitative method was used to validate the proposed model. Based on our online survey with 886 responses, we assessed the influences of product fit, network quality, and artificial intelligence-driven recommendation in perceiving cognitive engagements. This study examined the importance of engaging satisfaction and trust as emotional engagements, influencing users’ continuance intention. Our findings confirm that sources of information, especially online reviews, positively affect in perceiving subjective norms. Also, trust has a more significant influence on the continuance intention to use AR mobile platforms. Also, the results explored that the generation of users has a significant impact on continuance intention. This could enhance the capabilities of information system designers, researchers, marketing professionals, and solution providers to attain sustainable user retention.
How Multi-sensory Can Help the Visually Impaired Better Play the Instruments: An Inclusive Design Practice
Authors: Jiang Qian , Wai Michael Siu Kin
Published: November 2024

For the visually impaired, it is harder to learn how to play an instrument. Taking playing the piano as the case, we conducted the research to explore how other senses work better to support this special group to learn how to play the piano. Using the methods of literature analysis and data collection by designed questionnaire, we tried to design a smart keyboard to solve the problems people with impaired sight may meet in three perspectives: 1) Finding the corresponding keys for notes. 2) Communication with instructors. 3) Variable changes in rhythm. We provide a new learning possibility for the visually impaired to play the piano. Based on the concept of inclusive design, we also considered the needs of the normal people with the expectation to achieve the inclusive goal of music communication between the abled and the disabled.
Optimizing UX design to enhance user confidence in digital products
Authors: Li Vivian , Sun Peiyi , Lim Yihyun
Published: November 2024

As digital products grow in prominence, the significance of user experience (UX) design becomes increasingly evident. A crucial outcome of strong UX design is user confidence, defined as a user’s trust in their ability to effectively interact with a product. Designs that foster user confidence reduce interface uncertainty and enhance user self-belief, leading to increased engagement and repeated interactions. Conversely, a lack of user confidence can drive users to seek alternative products. This study aims to uncover the underlying principles that enable users to navigate products with confidence, thereby providing design guidance for fostering long-term product loyalty. This study identifies five key design principles that enhance user confidence: 1) Creating familiarity with UI elements and interactions, 2) Balancing information accessibility and overload, 3) Providing clarity in action descriptions, 4) Offering feedback after decisive user actions, and 5) Enabling the reversibility of actions. To explore user confidence, the study employed three methods. In-depth user interviews were conducted to gather insights on user experiences with both digital and physical products. Afterward, a three-day immersion study (“UX diary”) was conducted to document users’ emotional interactions with everyday products. Finally, a series of generative workshops were hosted to validate the principles and explore their applicability in different product contexts, such as posting content on Reddit and placing an order on Amazon. Participants reported that these principles provided reassurance and facilitated ease of use. User confidence is a prerequisite for other UX design considerations. By focusing on these principles, designers can create products that foster confidence and satisfaction, ultimately leading to improved user engagement and retention.
Comparing the Efficacy of Virtual Reality Training, Augmented Reality Instruction and Traditional Paper-Based Instruction Methods for Assembly Tasks
Authors: Abdullah Md , Nirmal Vibhav , Rahman Mahmudur
Published: November 2024

The landscape of instructional methods is continually evolving, driven by advancements in technology. Virtual Reality (VR) and Augmented reality (AR) are emerging technologies offering innovative approaches to training and providing real-time assistance. In order to compare the efficacy of these methods in assembly tasks, in this study, 24 participants were randomly assigned to three groups: one group used paper-based instructions, while another used instruction displayed through the HoloLens 2.0 (AR), and the remaining group was trained in a fully immersive VR environment and were asked to perform the same assembly task afterward. The participants were tasked with assembling a monster truck Lego set, and their performance was measured using objective metrics such as completion time and the number of errors made. Subjective measures were obtained through the NASA Task Load Index (TLX) questionnaire, which assessed the perceived workload of each instructional method. Participants using paper-based instructions completed the task in an average of 5.92 minutes, which was significantly faster than those using AR (average completion time of 8.21 minutes), and those using VR training (average completion time of 7.23 minutes). The number of errors was highest with the VR training, averaging 2 errors per participant, compared to the paper-based instructions (0.625 errors) and AR (1.25 errors). Subjectively, participants rated the AR experience slightly higher, with an average NASA TLX score of 23.26, compared to 26.25 for VR training. Paper-based instructions had the lowest workload value, with a mean NASA TLX score of 17.60. The findings suggest that while VR and AR offer advanced learning experiences, they may not always outperform traditional paper-based instructions in terms of task completion time and error rates. These results emphasize the need to consider task complexity and user experience when evaluating instructional methods. Further research is needed to explore the benefits of VR and AR in different contexts.
CreteAR: Enhancing Learning Experiences through Tangible Transformable Artifacts and Extended Reality
Authors: Tosios Antonios , Leonidis Asterios , Korozi Maria , Menelaos Stivaktakis Nikolaos , Apostolakis Emannouil , Roulios Michalis , Paparoulis Spiros , Stamatakis Emmanouil , Stephanidis Constantine
Published: November 2024

This paper discusses the design and development of CreteAR, a system that integrates Extended Reality (XR) with a transformable physical model of the island of Crete to enhance learning experiences. CreteAR features an XR application for handheld devices that overlays information on a scale model, which is equipped with mechatronics to elevate or conceal showcases containing culturally significant items. Users can interact with both the digital content and the physical model, activating the showcases and accessing information through a companion display. The paper explores relevant literature, analyzes similar systems, and details the design process, including user requirements and expert feedback. CreteAR was initially conceived as a prototype, but it holds the potential to contribute to the development of broader applications across various domains beyond the scope of Crete's geography and heritage. It was designed to deliver an immersive and hands-on learning experience, emphasizing social interaction and cooperative exploration, engaging users in dynamic and meaningful interactions.
A Digital Human Model for Symptom Progression of Vestibular Motion Sickness based on Subjective Vertical Conflict Theory
Authors: Inoue Shota , Liu Hailong , Wada Takahiro
Published: November 2024

Digital human models of motion sickness have been actively developed, among which models based on subjective vertical conflict (SVC) theory are the most actively studied. These models facilitate the prediction of motion sickness in various scenarios such as riding in a car. Most SVC theory models predict the motion sickness incidence (MSI), which is defined as the percentage of people who would vomit with the given specific motion stimulus. However, no model has been developed to describe milder forms of discomfort or specific symptoms of motion sickness, even though predicting milder symptoms is important for applications in automobiles and daily use vehicles. Therefore, the purpose of this study was to build a computational model of symptom progression of vestibular motion sickness based on SVC theory. We focused on a model of vestibular motion sickness with six degrees-of-freedom (6DoF) head motions. The model was developed by updating the output part of the state-of-the-art SVC model, termed the 6DoF-SVC (IN1) model, from MSI to the MIsery SCale (MISC), which is a subjective rating scale for symptom progression. We conducted an experiment to measure the progression of motion sickness during a straight fore-aft motion. It was demonstrated that our proposed method, with the parameters of the output parts optimized by the experimental results, fits well with the observed MISC.
Timbre estimation of compound tones from an auditory cortex by deep learning using fMRI: Sound pressure levels detection of specific frequency
Authors: Kusumoto Junnosuke , Shibata Kyoko , Satoh Hironobu
Published: November 2024

Brain decoding have been widely treated in the neuroscience. However, compared to research in the visual cortex, progress in the field of auditory cortex has not been made. Therefore, the purpose of this study is to establish a technique to estimate sounds heard by human using deep learning from brain images captured by fMRI. The sounds we hear in usual have a unique timbre. Timbre is determined by the combination of sound pressure levels at the overtone, which is the natural multiple of the fundamental frequency, in a compound tone. Before, this research group decoded the pitch of pure tones, which are waves of a single frequency. As a result, the discrimination of two tones in increasing degrees and the detection of a specific pitch in triad were realized. Next phase of this research is to decode a sound pressure level at a specific frequency. By combining these methods, we believe it is possible to decode timbre by detecting a sound pressure level of specific overtone. In a previous report, we examined whether the brain activity of listening to pure tones at two different sound pressure levels at specific frequency can be discriminated by deep learning binary classification. The result was a discrimination rate of 70.84% with relative levels of 0 [dB] and -20 [dB] when 90 [dB] was used as a reference. This result indicates that the difference in brain activation intensity by sound pressure level could be handled as classification problem by deep learning. Therefore, the purpose of this paper is to detect the sound pressure level of pure tones using deep learning for application to timbre decoding. Specifically, we attempt to detect specific sound pressure level among the three tones of 0 [dB], -10 [dB], and -20 [dB] when 90 [dB] based on an absolute level of 90[dB]
User trust in a depression screening app when outcomes are labelled as either AI-generated or doctor-generated: a pilot study.
Authors: Shahsavar Yeganeh , Choudhury Avishek
Published: November 2024

This study aimed to quantify and compare user trust when interacting with a web-based depression screening app, where outcomes were labeled as either AI-generated or doctor-generated. The app calculated a depression score based on user input and presented two screening outcomes, one labeled as “doctor-generated” and the other as “AI-generated.” Participants were then asked to select the outcome they trusted the most. Seventeen individuals participated in the study. Despite identical outcomes, 11 participants chose the AI-generated outcome (group-AI), while 6 selected the doctor-generated outcome (group-DR). To assess user trust (also attention), electroencephalogram (EEG) signals were recorded during the task, focusing on Alpha (Pz) and Beta (Fc1, Fc2) channels. Attention was measured through Alpha activity at Pz, while trust was assessed through Beta activity at Fc1 and Fc2. Post-intervention, participants’ perceived trust in the outcomes was measured using a survey. The mean normalized power spectral density (PSD) values were calculated and correlated with the survey-based trust scores. Comparisons of PSDs and trust scores were made both between and within the AI and DR groups. Results showed that the mean PSD value for attention (Pz) was 0.116 µV²/Hz, while the values for trust (Fc1 and Fc2) were 0.648 µV²/Hz and 0.646 µV²/Hz, respectively. The mean trust score for the AI-based outcome was 3.118, compared to 3.235 for the doctor-based outcome. A weak to moderate correlation was observed between survey trust scores and PSD values in Fc1 and Fc2. Group-AI exhibited lower Alpha power at Pz (0.108 µV²/Hz) and higher Beta power at Fc1 (0.660 µV²/Hz) and Fc2 (0.659 µV²/Hz) compared to group-DR, which showed higher Alpha power at Pz (0.131 µV²/Hz) and lower Beta power at Fc1 (0.626 µV²/Hz) and Fc2 (0.621 µV²/Hz). In conclusion, our findings suggest that while participants may express marginal preference for doctor-generated outcomes in self-reported trust, their EEG data reveals a nuanced picture where those choosing AI-based outcomes may exhibit higher levels of trust on a cognitive level.
The Influence of Gender/Sex on Work-Related Musculoskeletal Disorders: A Systematic Review and Meta-Analysis
Authors: Manning Christy , Ali Duha , Nagrecha Shivani
Published: November 2024

This systematic review and meta-analysis examines the influence of gender/sex on the risk of developing work-related musculoskeletal disorders (WMSDs). Previous research has indicated a link between female gender/sex and increased WMSD risk, but findings have been inconsistent due to varying study designs and high null result rates. This study synthesized adjusted odds ratios (AORs) from 93 high-quality cross-sectional studies that examine WMSD risk while controlling for various confounding factors such as job exposure and environmental variables. The overall synthesized AOR for female gender/sex on WMSD risk was 1.50, and gender was a statistically significant predictor of risk for most but not all body parts and industries. High heterogeneity was present in the overall synthesis but recued when stratifying results by industry and body part. The results suggest a significant but low to moderate link between gender and WMSD incidence, with some variation by industry and body part.
Facilitating Technology Diffusion: Unveiling the Dynamics of Emerging Technologies on Construction Project Sites
Authors: Adekunle Samuel , John Beauty , Ebekozien Andrew , Aigbavboa Clinton
Published: November 2024

Emerging technologies hold immense promise for enhancing productivity and safety in the construction industry. However, a persistent challenge remains: Why are these innovations not used on project sites and by site workers? This study investigates the phenomenon of bottom-up technology diffusion from construction sites. By examining the dynamics at the “grassroots” level, the study explores the barriers and facilitators that influence the adoption and utilization of emerging technologies by site workers. This was achieved through a mixed-methods approach, adopting interviews and on-site observations on selected construction sites in South Africa. The study uncovers factors such as power challenges, lack of trust, lack of training, resistance to change, and inadequate infrastructure, among others. The study also identified the strategies required to overcome this challenge of achieving technology diffusion to construction project sites. Ultimately, understanding the bottom-up diffusion process is crucial for bridging the gap between technological advancements and frontline workers, paving the way for a more inclusive and efficient construction industry.
A semantic matchmaking approach to empower human decision-making in Manufacturing-as-a-Service scenarios
Authors: Schuseil Frauke , Hertwig Michael , Lentes Joachim , Zimmermann Nikolas , Hölzle Katharina
Published: November 2024

Fragile and unreliable supply chains, due to environmental disasters or other disruptions are a challenge for modern production companies. The concept of Manufacturing-as-a-Service (MaaS) marks a shift from traditional manufacturing, focusing on shared, networked infrastructures. In MaaS environments, effective management of demand for manufacturing capabilities and supply of production capacity is crucial, while final decisions remain with human operators. The EU project ACCURATE (Achieving Resilience through Manufacturing-as-a-Service, Digital Twins and Ecosystems) aims to create a distributed MaaS ecosystem that offers a collaborative, human-centered Decision Support System (DSS) for robust planning and resilient operations. A primary challenge is aligning services from suppliers with the demand for physical goods, which includes transportation, warehousing, and information, in addition to manufacturing. Semantic approaches and ontologies can describe these services comparably. This paper introduces a semantic matchmaking concept in MaaS networks to empower human decision makers in supply chain management. To support this, related concepts of service-oriented manufacturing concepts are analyzed and a working definition of MaaS is derived. Based on this, an approach is presented that matches supply and demand for manufacturing services while considering product process requirements. Importantly, this is not a standalone decision-making tool but a foundation for informed choices, enabling users, like order fulfilment managers, to receive tailored offers from suitable providers based on recommendations from the semantic matchmaking service.
Elementary Students' Reflection Tool, Content Suggestions, and Discussion
Authors: Hsuan Tsai Yi , Chang Johan
Published: November 2024

Children's inability to take ownership of their own learning might lead to a reduction in motivation and effectiveness. Metacognition and reflection can improve learners' thinking and learning efficacy; this is now the most popular strategy among college students, but there are no rules or suggestions for elementary school students. There has been past research on reflection, and through literature review, data collecting and analysis, a questionnaire for students was produced. This study will build on the previously specified reflection tool and investigate the material's usefulness for students. Through expert interviews discussing the content and guidance methods of the reflection questions, as well as interviews with four current elementary school teachers, we understand the actual application and situation of reflection strategies in teaching, which serves as the foundation for subsequent revisions of sentences, questioning methods, and content. The experts were found to have similar ideas about Teaching Reflection and the questionnaire's content. In addition to Teaching Reflection, the process of group competition should begin with topics that are of interest to the students and have a high level of relevance to their lives in order to keep their interest and efficiency in learning reflection. The questionnaire should be tailored to include a specific subject, a clear task, and easy language, and it is preferable to ask students quantitatively about their emotions or feelings at the appropriate time. With these adjustments, the reflection tool and questionnaire material are appropriate for an elementary student.
Innovation and Trends in Human Resources: Analysis of Improvement Strategies in Graduation Projects from a Master's in HR and Human Talent Management
Authors: Lay Nelson , Felipe Vergara Maldonado Luis , Rubio Andres , Riquelme Paula
Published: November 2024

This study analyzes the improvement strategies in the area of Human Resources (HR) proposed in 67 graduation projects (Master's Final Project) over the last 3 years from two master's programs of the Faculty of Economics and Business at Andrés Bello University: Master in Human Resources Management and Management Skills and Master in People Management and Talent Management. Using quantitative and qualitative techniques, the study examines trends and the degree of innovation in the projects presented by students. The focus is on the relevance of these strategies in addressing current challenges in the field, including talent retention, diversity and inclusion, and digital transformation. The results point to significant progress in applying modern theories and cutting-edge talent management practices. This analysis provides a valuable perspective on the evolution of HR practices and serves as a resource for academics in improving educational practices and for professionals interested in the ongoing development of the sector.
Using Media Equation Theory to Assess Anthropomorphism of Intelligent Virtual Reality Training Systems in Organizational Settings
Authors: Oetken Michael
Published: November 2024

The advent of immersive virtual reality (VR) media technology is revolutionizing communication by providing a platform that goes beyond traditional video, audio, and static web pages. These new media technologies allow users to engage in life-like, anthropomorphic interactions with both humans and non-human entities within immersive environments. Notably, this technology holds the potential to address and solve cultural and societal issues through more meaningful and effective engagement. This research explores the application of an intelligent VR media system in diversity, equity, and inclusion (DEI) training, highlighting its potential to enhance organizational training. Unlike traditional one-size-fits-all approaches, which may fail to meet the specific needs of different organizations—whether corporate, academic, or non-profit—VR-based DEI training offers a tailored, impactful experience. Rooted in media equation theory, which posits that humans react to media as they do to other humans, the study presented in this paper investigates how immersive VR can better equip individuals to navigate complex cultural and societal challenges.The findings suggest that successful DEI training via VR involves three critical components: an engaging and immersive user experience, the use of storytelling as a key communication tool, and interactive media to enhance learning effectiveness. Effective user experience design, supported by a strategic human-computer interaction framework, significantly boosts the impact of DEI training. Immersive environments, when well-designed, enhance learning by providing realistic contexts that mirror real-world scenarios, thereby aiding in practical understanding and memory retention. Additionally, VR creates a safe space for exploring sensitive issues, encouraging open dialogue and reflection without real-world consequences. Interactive scenarios can be customized to align with an organization's specific DEI goals, ensuring relevance and applicability to workplace situations. Ultimately, VR transforms DEI training from a passive learning experience into an active exercise in empathy and understanding, making it more engaging and meaningful for participants.
Recommendations and Discussions on the Use of Role Play in Online Social Studies Teaching for Elementary School Students
Authors: Zhong Yifeng , Chang Johan
Published: November 2024

Online teaching is increasingly being utilized in elementary education. However, elementary school students' learning performance in digital environments can be affected by online distractions and a lack of interactivity. Role play offers a highly interactive and immersive learning experience that can help students adapt to the online environment. To better achieve the teaching goals of the core competencies -- “thinking” and “teamwork” -- outlined in Taiwan's Curriculum Guidelines of 12-Year Basic Education for Social Studies, this study explores the integration of role play into Social Studies teaching. To understand the learning challenges students face in Social Studies and provide recommendations for designing role play courses, this study interviewed three Social Studies education experts. The findings reveal that the extensive and complex historical knowledge in Social Studies can make learning difficult for students. The study suggests incorporating “pre-class preparation,” “thought-tracking,” “peer assessment,” and “reflection and discussion” into role play activities. These results offer valuable materials and suggestions for designing online role play courses in Social Studies, aiming to enhance students' learning performance in online classes.
Collecting Anthropometric Data from the Perspective of Ergonomics. A Learning Experience for Industrial Engineering Students
Authors: Daphne Prado Jimenez Stephanie , Rey-Galindo John , Rosales-cinco Rosa , Aceves-gonzalez Carlos
Published: November 2024

The correct collection of anthropometric measurements is crucial in the field of ergonomics, especially for the design of tools and workspaces that adapt to the physical characteristics of the users. This article presents an educational proposal for industrial engineering students in a Public University in Mexico, focused on the teaching of anthropometric data collection techniques from an ergonomic perspective. The implementation of this proposal aims to improve the training of future professionals in Industrial Engineering with a solid knowledge of the application of ergonomics, ensuring the accuracy and relevance of the data collected in real contexts. The methodology used in the study included the design of a theoretical-practical educational programme, implemented in a university course from the perspective of institutional design and using theBenjamin Bloom’s cognitive levels and Gerald Grow’s model of self-directed learning by stages. The effectiveness of the programme was assessed through tests of practical knowledge and the accuracy of data collected by the students in supervised practice. The results of the study showed a significant improvement in the students' theoretical and practical knowledge of anthropometric measurement collection and its application in a real project. The study concludes that the educational proposal implemented is effective in teaching students the techniques of collecting anthropometric dimensions using a real case study and that students approach the problem from its real context and not just the reading of the problem, which allows them to learn to apply theoretical knowledge.
Exploring Driving Style Variations When Driving in Work Zone: A Driving Simulation Study
Authors: Wang Ze , Wu Hongyue , Chen Yunfeng , Zhang Jiansong , L Jenkins James
Published: November 2024

Traffic safety hinges on individual driving styles, which can vary within a single trip through a work zone. A work zone, with its limited visibility, heavy machinery, and unexpected traffic flow, is a major contributor to a high number of traffic accidents. Driving style has a significant effect on driving behavior and directly impacts driving safety. However, studies on the variation in driving styles in the specific scenario of driving through a work zone are still missing. Also, most studies used either surveys or machine learning methods for classifying driving styles, while there is a lack of comparison between these two classification methods. To address the gaps, this study aims to detect and classify variations in driving styles when driving through a work zone and compare the results obtained from the self-evaluation method with those from the machine learning method. Firstly, a lane closure work zone was simulated by Webots and SUMO, based on a real-world case of an urban road section in Indiana state. Daytime and nighttime scenarios were included to analyze variations in driving styles. Secondly, sixteen participants were invited to drive through the road section with a lane closure work zone using a driving simulator. Their driving speed, as well as acceleration and deceleration, were collected by Webots. Then, the K-means algorithm was used to classify three types of driving styles (aggressive, normal, or calm) based on the total non-linear traits in the driving data (eg, speed, acceleration). Finally, a self-evaluation survey on driving styles was conducted after the driving simulation experiment, and a comparative analysis was performed between the self-evaluation survey data and the driving simulation data. The results show that 1) The percentage of aggressive driving style was 51.6%. Participants tended towards a calm driving style at nighttime compared to daytime, and the normal driving style remained consistent across both daytime and nighttime; 2) There were significant differences between self-evaluation and K-means method on driving styles. Compared to the results from the K-means method, drivers tended to overestimate their normal driving style and underestimate their aggressive driving style based on the results from the self-evaluation method.; and 3) There was an observed increase in calm driving style before and during the work zone, contrasting with a rise in aggressive driving tendencies after exiting. The results may help understand the variance of driving styles in a work zone and improve the classification accuracy of driving styles by comparing the differences between driving data evaluation and post-survey data evaluation.
Assessing driver engagement in assisted driving: Insights from Pilot Evaluation, Focus Groups and driving simulator testing
Authors: Deiana Francesco , Jackson James , Periago Cristina , Castro Elena
Published: November 2024

Automated driving assistance systems (ADAS) have become increasingly prevalent in consumer vehicles, particularly at L2 level, offering various degrees of safety and comfort. However, many concerns arise regarding driver attention and engagement, as drivers may not fully understand the system limitations and their continued responsibility for vehicle control. For this reason, driver engagement is a topic of significant interest in the context of ADAS development. The European Commission is already working on future regulations regarding the integration of advanced L2 systems from a safe driving perspective, as is the NHTSA in the US. Driver engagement is included in the EuroNCAP 2030 roadmap and is also being considered as one of the criteria for the assessment of Smart Cockpit according to C-ICAP (2023). This work introduces a methodology aimed at evaluating driver engagement, which combines proving ground testing, focus groups, and dynamic driving simulator testing. Proving ground testing combines subjective metrics such as mental workload and trust, together with objective measures like Time to Collision (TTC). Results indicate differences in driver engagement between medium and advanced level 2 systems, with participants showing higher trust and lower mental workload in advanced L2 systems. Focus groups highlight generational differences in perceptions of ADAS, with younger participants demonstrating higher trust and acceptance. Also, situational awareness emerges as an important factor for a proper engagement. The upcoming driving simulator phase seeks to validate these findings in a controlled environment, integrating physiological measures and eye-tracking. Future steps include conducting cross-cultural studies to capture diverse driving habits and preferences.
IMU-based Assessment of Rider Kinematics in Motocross - a pilot study
Authors: Ostermeier Marie , - Laurin Sindinger Sigfrid , Marschall David
Published: November 2024

In vehicle development, the simulation of the mechanical system is already well advanced, while especially in two-wheelers the factor ‘rider’ is mostly simplified or fully omitted. In Motocross sports, the athlete’s posture and weight shift play a substantial role for efficiency and performance. The absence of objective measurement data alongside subjective feedback underscores the need to quantify rider and motorcycle kinematics during different Motocross maneuvers. In this pilot investigation, two male participants were riding on a Motocross circuit with two combustion motorcycle variants for six laps. Inertial measurement units were used to analyze the athletes’ postures during a cornering and jumping maneuver in the field by recording the position and orientation of all body segments as well as the approximation of the approximation of the center of mass. The results showed that between the two analyzed motorcycles, differing knee and hip angles and center of mass characteristics could be observed in specific parts of the maneuvers performed. Movement patterns can be identified and can help to analyze kinematics depending on varying motorcycle characteristics. Based on these results, conclusions about efficiency and performance can be drawn to assess and improve riding technique of motorsports athletes and aid vehicle development. In further steps, the data could be used to build a more realistic rider model for different riding scenarios to improve simulation routines.
Auto-generating Road Trip Vlogs While Safe-driving: a Human-Vehicle-Environment System for Capturing and Editing Scenic Views En Route
Authors: Guo Zichun , Meng Xianning , Xu Haiqing , Liu Zumeng , Wang Lingkan , Chen Jiawei , Zhu Yaxin
Published: November 2024

Road trip vlogs have gradually become popular content for sharing among people. This study introduces an artificial intelligence (AI)-based road trips video editing system, designed with a primary purpose of preventing traffic accidents caused by drivers recording scenic views with smartphones while driving. To enable the dashcam to automatically capture materials of interest, it is crucial to define the starting-ending time and content. Data monitoring around the Human-Vehicle-Environment (HVE) is a critical factor for establishing the capture rules. Guided by audiovisual language theory, the captured video materials are used to support intelligent editing. Furthermore, stylization in editing, including narrative lyrical and documentary style, is another design factor to achieve diversity in videos. Research results demonstrate that the synergy among the HVE elements is a pivotal factor in capturing key visuals. Using AI to complete road trip videos can reduce traffic accident risks and promote the effectiveness of recording scenic views.
Development of a Near-Miss Event Analysis Support System for Different Types of Human Error Using AI Technology
Authors: Lee Joohyun , Okada Yusaku
Published: November 2024

Preventive measures against various human errors are being taken based on information on near-miss events. However, the process from collecting near-miss events to analyzing them and planning countermeasures is labor-intensive. Focusing only on high-risk near-miss events can reduce labor, but many of the collected near-miss events will not be used. To solve these problems, we believe that a "near-miss event analysis support system" consisting of the following tools will be useful.(1st Tool) A tool to support the analysis of near-miss events, especially factor analysis (automatically extracts factors and identifies human error type. Analysts can add or modify.)(2nd Tool) A tool to support risk assessment of near-miss events (calculates the possibility of human error occurring in the target work on a 5-point scale. Analysts input the 5-point scale based on the expected extent of damage when it occurs. These two values are multiplied, and the risk is evaluated on a 5-point scale [1. Take physical measures immediately, 2. Implement on-site response plan immediately, 3. Horizontally deploy to the site and issue a warning, 4. Share information at the site manager level, 5. No response necessary])(3rd Tool) A tool to present countermeasures for near-miss events that are judged to be high risk (automatically presents appropriate human error countermeasure policies and three specific candidate measures based on human error type. Analysts select countermeasures based on the presented countermeasure policies)(4th Tool) Near-miss event occurrence trend analysis tool (Automatically performs statistical analysis of the causes of near-miss events that occurred during a period set by the analyst. Also performs categorization analysis based on the work site, work time period, and SRK level of the work.)(5th Tool) Near-miss event management tool (Connects the near-miss event input tool with the above four tools, stores all data such as evaluation results in the cloud, and supports horizontal deployment within the company. Based on the evaluation results, the urgency is evaluated in four stages (Level 0: no contact required, Level 1: information sharing, Level 2: detailed warning to the site, Level 3: immediate on-site inspection and improvement), and if it is Level 2 or above, a function is added to automatically contact related departments from the system.)We implemented these five tools based on AI technology and built a near-miss event analysis support system. This system is currently being test-operated by safety personnel from several companies, and although we are still in the process of collecting operational issues, it has been confirmed that it has the expected effects.
Gambaran pengunaan obat antidiabetes pada pasien BPJS diabetes melitus tipe 1 dan tipe 2 di rumah sakit x tahun 2023
Authors: Lestari Ayu Putri , Rochjana Anna Uswatun Hasanah , Adiana Sylvi
Published: November 2024

Diabetes melitus (DM) adalah gangguan metabolisme yang ditandai dengan kadar gula darah tinggi akibat penurunan produksi atau sensitivitas insulin. Federasi Diabetes Internasional memprediksi peningkatan kasus diabetes mencapai 678 juta pada tahun 2030 dan 700 juta pada tahun 2045. Penelitian ini bertujuan untuk mengkarakterisasi pasien DM Tipe 1 dan Tipe 2 berdasarkan usia, jenis kelamin, komorbiditas, dan penggunaan obat antidiabetes menurut nama obat, golongan obat dan tipe terapi. Studi deskriptif retrospektif ini menganalisis Resep Pasien DM Tipe 1 dan DM Tipe 2 yang digunakan sebagai sampel penelitian sebanyak 148 resep. Resep Pasien terdiagnosis DM Tipe 1 tidak ditemukan dan Resep Pasien terdiagnosis DM Tipe 2 berjumlah 148 resep dari Poli Penyakit Dalam Rawat Jalan BPJS Rumah Sakit X Pada Tahun 2023. Resep Pasien DM Tipe 2 Sebagian besar pasien berusia 56-65 tahun (43,92%), Perempuan (62,84%) lebih banyak daripada laki-laki (37,16%). Hipertensi merupakan komorbiditas yang paling umum (78,38%). Pada DM Tipe 2 resep obat tunggal biguanid (metformin) paling banyak (41,67%). Kombinasi dua obat oral yang paling banyak digunakan adalah biguanid dan sulfonilurea (metformin dan glimepirid) sebesar (13%). Secara keseluruhan, terapi kombinasi oral paling banyak digunakan (67,57%).
Kata Kunci : Diabetes Melitus Tipe 1 dan Tipe 2, Penggunaan Obat, Penyakit Penyerta.
Implementation of open educational resources in the context of student-centred approach
Authors: Batsurovska Ilona V. , Dotsenko Nataliia A. , Lymar Oleksandr O. , Gorbenko Olena A. , Kurepin Viacheslav M.
Published: November 2024

The article outlines pedagogical technologies for teaching environmental engineering in online learning systems of higher education using open educational resources (OER) with a student-centred approach. A technology integrating OER, including educational videos, online explanations for practical work, modular testing, and e-textbooks, was experimentally tested. The proposed technology was evaluated using a control and experimental group design at two universities. Statistical analysis using Pearson's chi-squared test showed a significant improvement in learning outcomes for the experimental group exposed to OER (χ2=45.55, p<0.01). The results demonstrate that a student-centred approach leveraging OER is a promising method to enhance the learning of complex subjects like environmental engineering. This study addresses a gap in empirical research on discipline-specific applications of OER. The findings are discussed in the context of recent literature highlighting the benefits of OER for accessibility, engagement, and learning outcomes in higher education. Recommendations are provided for the effective integration of OER by instructors and institutions.