bluuebunny/crossref_metadata_2025 huggingface dataset:
Leveraging Manifold Learning and Relationship Equity Management for Symbiotic Explainable Artificial Intelligence
Authors: Davis Eric , Dey Sourya , Karvonen Adam , Lew Ethan , Quick Donya , Shyamshankar Panchapakesan , Hille Ted , Lebeau Matt
Published: June 2023

Improvements in neural methods have led to the unprecedented adoption of AI in domains previously limited to human experts. As these technologies mature, especially in the area of neuro-symbolic intelligence, interest has increased in artificial cognitive capabilities that would allow an AI system to function less like an application and more like an interdependent teammate. In addition to improving language capabilities, next-generation AI systems need to support symbiotic, human-centered processes, including objective alignment, trust calibration, common ground, and the ability to build complex workflows that manage risks due to resources such as time, environmental constraints, and diverse computational settings from super computers to autonomous vehicles.In this paper we review current challenges in achieving Symbiotic Intelligence, and introduce novel capabilities in Artificial Executive Function we have developed towards solving these challenges. We present our work in the context of current literature on context-aware and self-aware computing and present basic building blocks of a novel, open-source, AI architecture for Symbiotic Intelligence. Our methods have been demonstrated effectively in both simulated crisis and during the pandemic. We argue our system meets the basic criteria outlined by DARPA and AFRL providing: (1) introspection via graph-based reasoning to establish expectations for both autonomous and team performance, to communicate expectations for interdependent co-performance, capability, an understanding of shared goals; (2) adaptivity through the use of automatic workflow generation using semantic labels to understand requirements, constraints, and expectations; (3) self healing capabilities using after-action review and co-training capabilities; (4) goal oriented reasoning via an awareness of machine, human, and team responsibilities and goals; (5) approximate, risk-aware, planning using a flexible workflow infrastructure with interchangeable units of computation capable of supporting both high fidelity, costly, reasoning suitable for traditional data centers, as well as in-the-field reasoning with highly performable surrogate models suitable for more constrained edge computing environments. Our framework provides unique symbiotic reasoning to support crisis response, allowing fast, flexible, analysis pipelines that can be responsive to changing resource and risk conditions in the field. We discuss the theory behind our methods, practical concerns, and our experimental results that provide evidence of their efficacy, especially in crisis decision making.
A Formal Method for the Analysis of the Veteran’s Ebenefits’ Website
Authors: Camacho Giovanna , Bolton Matthew , Peng Jingan , Wagle Prashanth
Published: June 2023

Currently, the Ebenefits/VA.gov website has login problems. This is a serious situation because it prevents veterans from accessing critical services: applying for medical disabilities; enrolling in health care services; accessing educational benefits; managing current VA benefits; acquiring home and auto loans, life insurance, burial services; and connecting veteran networks for other community resources. When a service member is unable to access this website, they are unable to help themselves. This adds inefficiencies to the overall VA system and could lead to poor veteran integration to civilian life. In this analysis, we used a technology called probabilistic model checking (a formal method for proving properties about stochastic systems) to identify the optimal process for veterans to login to Ebenefits while adhering to safety constraints for protecting veterans’ sensitive information. To perform this analysis, a veteran in our research group documented multiple login attempts to gain realistic probabilities of the system transitioning between different interface states. Probabilistic model checking was used to quantify the probability of successfully getting from initial states to a successful login. In analyzing these results, the probability of a successful login for Ebenefits was found to be 0.25. Reviewing the data produced by the model checker revealed that a particular state called two factor authentication, utilized to verify the veteran’s identity by a password and passcode sent to a technological device in their possession, was a problematic state. Our analyses also showed that one particular path, the Defense Self-Service Logon Path, was the most successful pathway at 0.98. This pathway begins with the user entering their password, verification of this password, followed up with a second authentication which the end user can skip or chose to add to their cellular device prior to allowing them to have a successful login. Based on this path, we found that use of a Common Access Card was most effective for enabling logins. Further work utilizing formal methods for exposing problems in the Ebenefits website will be explored in the full paper.
Energy Cooperatives as Energy Transition Actors
Authors: Hellmuth Nils , Jakobs Eva-Maria
Published: June 2023

Germany is pursuing the ambitious goal of climate neutrality by 2045. In fact, the expansion of renewable energies is taking place far too slowly. There are several reasons for that. Project approval and planning processes are too lengthy and time-consuming; they are also often complicated by citizen protests against wind farms and ground-mounted photovoltaic parks. Various studies show that many protests are the result of perceived conflicts. The nature and extent of the conflicts vary, e.g., depending on the type of conflict, the stakeholders, technology, and local context. Overall, studies show that communication is a crucial factor in the success of infra-structure projects, e.g., as a means of conflict management.Many studies about energy infrastructure projects look at projects that are implement-ed by companies. This study changes the perspective on the ongoing transformation process to renewable energies. The focus is not on companies that need to interest and attract citizens to renewable energy projects but on citizens who join citizen energy cooperatives (CECs) and become local entrepreneurs themselves. The study aims to provide statements on how CECs function, what communication tasks they must master, and what challenges are in communicating internally with members and externally with stakeholders. This includes a deeper understanding of the perspectives for CECs regarding current legislation and planned business models, as well as conflicts that have arisen and are emerging.For the study, CECs were researched online, and executives (n=12) were asked for an interview. Before the in-depth interview, they were asked to complete a questionnaire where they provided information about their cooperative. The literature-based interview guideline addresses three topic areas: (1) CECs' expertise and scope of tasks; (2) communication tasks of the CEC; and (3) perceived risks and conflicts. The interviews were conducted in 2022. The data were anonymized, transcribed, and analyzed qualitatively (interview) and quantitatively (preliminary questionnaire).Results: The respondents understand communication as an essential and success-relevant part of the implementation of CEC energy projects. In recent years, the communication effort for CECs has steadily increased. The most important communication areas are project planning and acquisition, public relations, and member communication. Most respondents are convinced that local acceptance of energy projects is higher when CECs implement projects compared to companies since those responsible are themselves members of the community and therefore share local needs, desires, and problems of the community actors. To remain competitive, the CECs surveyed are expanding their portfolio structure, e.g., by communication-intensive models such as tenant electricity. CECs are developing many formats or pursuing novel approaches. Companies would be well advised to learn from this wealth of ideas from CECs, e.g., in public relations work and addressing new target groups.
Investigating the Influence of Perceived Anthropomorphism of Vehicles on Pedestrians’ Crossing Decisions in a Test Track Study
Authors: Theobald Nina , Joisten Philip , Friedrich Felix , Abendroth Bettina
Published: June 2023

People tend to anthropomorphize, i.e., perceive the fronts of vehicles in a face-like manner and attribute personality traits to them. This study investigates the influence of perceived vehicle appearance, in terms of perceived anthropomorphism of vehicles, on pedestrians’ crossing decisions. Therefore, a test track study with 20 participants and two vehicle types was conducted. No relationship between the perceived anthropomorphism of the vehicles and pedestrians’ decisions when crossing the road in front of the vehicles was found. However, the results show that the anthropomorphic description and the non-anthropomorphic description have opposite valences in case of both vehicles. A lack of influence of perceived anthropomorphism of vehicles on pedestrians’ crossing decisions in this study could be due to compensation mechanisms between anthropomorphic and non-anthropomorphic positive and negative attributions to the vehicles. The study concludes with a discussion of both approaches used for operationalizing vehicle appearance and implications for further research.
Effect of Secondary Tasks in Touchscreen In-Vehicle Information System Operation on Driving Distraction
Authors: Duolikun Wuweidan , Wang Binjue , Yang Xiaonan , Niu Hongwei , Wan Xuanzhu , Xue Qing , Zhao Yan
Published: June 2023

With the rapid development of the automotive industry and the advancement of mobile communication technology, In-Vehicle Information System shifted from traditional button to touchscreen. However, while enriching the drivers' driving experience, there are also certain potential driving distractions when operating touchscreen IVIS during the driving process. This study takes the operation of touchscreen IVIS by the driver as the secondary driving task, and designs a simulated driving experiment to explore the im-pact of the operation of secondary tasks on driving safety from driving performance, secondary task performance and EEG. Research has shown that low load operation tasks can easily cause drivers to be distracted, while high load operation tasks can affect drivers' judgment ability and occupy too much action resources. And when the difficulty level increases, drivers develop a compensation mechanism to complete secondary tasks through self-regulation.
Predictive Validity of the Vehicle Seat Comfort Score by Using the Seat Design and Testing Factors
Authors: Sunwoong Kim
Published: June 2023

Vehicle seat comfort engineering is one of the most important things among vari-ous seat engineering fields. Many seat engineers want to make it easier to predict and improve comfort. There were several attempts, but it was not easy to predict due to the highly subjective nature of comfort. In this study, we tried to confirm the feasibility of developing a tool that can easily predict comfort by utilizing the main design factors of seats and vehicle packages. As Consumer’s various expe-riences while using cars were defined as comfort factors and models to predict them were developed. A total of 5 cars of mid-sized sedans with various charac-teristics were selected as the subject of this study. As objective measures, dimen-sions of the seats with SAE J826 OSCAR, calculated data from force-deflection curves of the seat, and occupants package layout dimensions were selected. SLD measurement, SgRP calculation, and 3D scans were conducted for all study ve-hicle models. In order to obtain consumer evaluation results, a comfort clinic was conducted for 33 Americans (28 males and 5 females). A model for predicting overall comfort was developed by analyzing both quantitatively and qualitatively measured and evaluated data. The adjusted R2 value of the developed prediction model was 0.8047, showing very high explanatory power.
Building Trust in Highly Automated and Autonomous Vehicles
Authors: Proctor Karl
Published: June 2023

Trust in highly Automated and Autonomous Vehicles (AAVs) is a topic that has been gaining traction in recent years, across academia, the technology industry, and of course, the automotive industry. A number of automotive OEMs and tech companies across the globe are developing AAVs, with the short-term focus being on SAE Level 2 and Level 3 vehicles, and the longer-term focus being on SAE Level 4 and Level 5 vehicles. Alongside the development of the core technology needed for such AAVs, these companies have been grappling with a key question that will influence the uptake and ultimate success of AAVs; How to get people to trust these vehicles? This paper outlines a series of small-scale projects undertaken by Jaguar Land Rover Research between 2016 and 2018 as part of the UKAutodrive project that attempted to address this question. Across this series of user trials, participants experienced a number of autonomous drives in a low-speed (6mph/10kph) prototype SAE Level 4 autonomous ‘pod’ for up to fifteen minutes at a time, and then asked to rate their trust at the end of each individual drive. Overall, the data shows that Trust is something that can indeed be reliably measured, something that changes/fluctuates over time, and can be undone if the occupant experiences a negative event (e.g. a near miss), with the impact of this event depending on when the occupant experienced it (first trip vs. fifth trip). Finally, we show that it seems to be the number of trips in, or exposures to, an autonomous vehicle rather than the length of time per trip that influences trust, with more, shorter trips (8x4 minute trips) recording higher reported trust compared to fewer, longer trips (4x8 minutes trips).
Topological Shape Differences in High-speed Trains from a Human Perspective
Authors: Ma Jingming , Ji Peng
Published: June 2023

The shape of high-speed trains is a combination of engineering and design, taking into account both performance requirements and aesthetic form. With the increase of operating speed, the shape design and aerodynamic research need to be synergistically unified. Different topological shapes have large differences in air resistance and aerodynamic noise, so trains in different regions have their own characteristics in terms of shape. By analyzing the evolution of the shape spectrum of high-speed trains in each platform in the world, we extract the genes of high-speed train aerodynamic performance shape, and analyze the regional characteristics and the influence of human factors on train shape to help the brand construction of high-speed trains in different regions.
Information Provision on Interactive Smart Public Displays in Public Transport in Events of Disruptions
Authors: Titov Waldemar , Gerlach Carl , Schlegel Thomas
Published: June 2023

The communication of information is an important component of public transport. New designs for interactive displays integrated into public transport vehicles, called SmartWindow1, are being developed and implemented. In this paper, we conduct a laboratory user study evaluating the information communication in cases of disruptions. The user study focuses the kind of information and the timing of the information being displayed as well as determines what improvements in the disruption communication can be made. The two scenarios selected for the user study are based in real live scenarios from the local public transport network of Karlsruhe, Germany. The user study is being conducted in combination with a study on notifications on smartphones, resulting in three test groups. Similar to a prior proven approach group A tests only the notifications on the smartphone, group B tests only those on the SmartWindow and group C tests both media outputs.
Contributing factors to fatigue among high-speed train drivers: A questionnaire study in China
Authors: Li Yanyi , Wang Ziteng , Zhang Qidi , Kingsley Li Musen , Zhang Wei
Published: June 2023

Based on global statistics from 1993 to 2017, most railway accidents were caused by human errors, and drivers’ unsafe operation was one of the most common types of human errors ( Liu et al., 2019). One of the main contributing factors to drivers’ unsafe operations is driver fatigue. Therefore, it's essential to evaluate the level of fatigue among High-speed train (HST) drivers and identify the main influencing factors of fatigue. We designed a questionnaire that used the subjective score of SSS to assess the fatigue of HST drivers . A follow-up questionnaire survey was conducted with 243 HST drivers, and then exploratory factor analysis and hierarchical regression was conducted to determine the significant influencing factors of fatigue and form a prediction model. The results showed that HST drivers' personal characteristics (health status, personal trait score, number of chronic diseases), sleep, and working task (communicate task, lookout task) had significant effect on fatigue. The outcome of this research provided the main influencing factors of HST drivers’ fatigue and proposed an effective prediction model to promote structural understanding of HST drivers’ fatigue.
Highway work zone warning system design based on drivers' requirements
Authors: Liu Shuo-Fang , Ni Peng , Wang Shiyu
Published: June 2023

With the full coverage of the highway network in each country, the workload of highway construction and maintenance is getting bigger and bigger. The establishment of highway work zones has brought a more complex road environment for motorists. A large number of injuries and fatalities occur in work zones, of which about 60% are estimated to be road drivers. Many accident analysis studies have also shown that these accidents are mainly caused by driver's own human factors and inadequate road safety facilities. In order to reduce the occurrence of these accidents, some advanced technologies are being applied to traffic warning facilities. However, the real needs of drivers, who are the actual recipients of the warnings, are not fully considered in the warning design. Therefore, in this study, a Quality Function Deployment (QFD) approach is used to systematically analyze the user requirements and to design the actual design requirements of the traffic warning system in the work zone in conjunction with the emerging warning technologies. The new warning system design is expected to reduce work zone accidents caused by human factors because its requirements are based on real drivers' requirements. To achieve a human-centred safety design. In this study, two steps are taken. First, user requirements were obtained by interviewing driving experts. Second, the design requirements of the intelligent warning system were analysed and prioritized using a QFD method, resulting in the output of key design requirements.
Risk assessment and observation of driver with pedestrian using instantaneous heart rate and HRV
Authors: Kikuta Riku , Carruth Daniel , Ball John , Burch Reuben , Kageyama Ichiro
Published: June 2023

Currently, human drivers outperform self-driving vehicles in many conditions such as collision avoidance. Therefore, understanding human driver behaviour in these conditions will provide insight for future autonomous vehicles. For understanding driver behaviour, risk assessment is applied so far as one of the approaches by using both subjective and objective measurement. Subjective measurement methods such as questionnaires may provide insight into driver risk assessment but there is often significant variability between drivers. Physiological measurements such as heart rate (HR), electroencephalogram (EEG), and electromyogram (EMG) provide more objective measurements of driver risk assessment. HR is often used for measuring driver’s risk assessment based on observed correlations between HR and risk perception. Previous work has used HR to measure driver’s risk assessment in self-driving systems, but pedestrian dynamics is not considered for the research. In this study, we observed driver’s behaviour in certain scenarios which have pedestrian on driving simulator. The scenarios have safe/unsafe situations (i.e., pedestrian crosses road and vehicle may hit pedestrian in one scenario), HR analysis in time/frequency domain is processed for risk assessment. As a result, HR analysis in frequency domain shows certain reasonability for driver risk assessment when driver has pedestrian in its traffic.
Use of Tactile Alerts in Urban Air Mobility Vehicles
Authors: Haneji Kali , Leung Kristine , Tran Alina , Cheung Justin , Deabaapilux William , Marayong Panadda , L. Vu Kim-Phuong , Shankar Praveen , Strybel Thomas , Battiste Vernol
Published: June 2023

Urban Air Mobility (UAM) has been proposed as a solution to congested roads in cities. We tested an early concept of operation for UAM, where participants flew a simulated vehicle along a freeway route to and from two locations in the San Francisco area. We found that novice participants were able to pilot our UAM vehicle when it deviated from an automated route and return it back on course. Our study also provided a demonstration of how tactile cues can be used in UAM vehicles as part of an alerting system. We found little difference between whether the tactile alerts were administered on the arms or thighs or whether they provided directional information or not. The lack of an effect of directionality can be due to the low workload for the scenarios we examined. Future works should examine the effectiveness of the alerts in more complex task environments. However, the findings from the present study show that a tactile alerting system is feasible and that participants rated it high in terms of usability and trustworthiness.
Project AVIAN-S: Development of a Natural Language Processing Model for Analyzing Aviation Safety Event Reports
Authors: Jordan Hinson R , Bynum Edward , Kinsella Amelia , Berry Katherine , Sawyer Michael
Published: June 2023

Voluntary Safety Reporting Programs (VSRPs) allow civil aviation authorities, operators, and manufacturers to actively monitor and identify potential safety issues within their operations. These first-hand reports enable organizations to develop and implement safety and efficiency improvements based on front-line observations. The National Aeronautics and Space Administration (NASA) operates the Aviation Safety Reporting System (ASRS) to empower the aviation industry and its participants to report observed safety problems, discrepancies, or deficiencies. ASRS receives, processes, and publicly releases thousands of reports annually. For example, 6,428 ASRS reports are currently available detailing events that occurred in 2019; any interested party can download these ASRS reports and associated data. Often, researchers and analysts will then read and manually label factors of interest in each report to gain safety insights. This manual process can be labor-intensive and relies on the ongoing efforts of subject-matter experts. The full potential of various voluntary safety reporting data can be difficult to realize due to the limited resources available to analyze and summarize these data. New machine learning techniques involving natural language processing offer opportunities to assess and label factors of interest within safety reports more efficiently and effectively. A novel machine learning model has been developed and trained to identify human factors issues within aviation safety reports. The AVIAN-S model has been built and iteratively trained on over 50,000 rows of manually classified aviation safety reporting data. The model uses machine learning and natural language processing to automate the process of labeling aviation safety reporting data and codifying reporter narratives according to an established human factors taxonomy. This paper will describe lessons learned from the initial model development iterations and present interim results of the model as applied across a set of sample event reports. The paper will further discuss the challenges and implications of using natural language processing to identify human factors issues emerging from this or other large aviation safety reporting data sets.
Developing an Adaptive Instructional System for Simulation-Based Lifeboat Training Using Instructor Feedback
Authors: Smith Jennifer , Zeinali Torbati Reza , Billard Randy , Emond Bruno , Veitch Brian
Published: June 2023

Integrating adaptive instructional systems (AIS) into simulation-based lifeboat training creates the opportunity to customize instruction and practice to meet the individual needs of trainees. Embedding an AIS into lifeboat simulation could make training more accessible for on-demand and remote learning applications such as practicing lifeboat coxswain duties while onboard vessels. An AIS evaluates performance, tailors instruction, and delivers practice exercises using four key models: the domain knowledge, the student/learner, the instructional framework, and the user interface. This paper applies a human-centred approach to developing the instructional model for an AIS to ensure the adaptive simulation-based training is attuned to the learning strategies of seafarers. Specifically, we gathered information from users of the lifeboat simulators by conducting semi-structured interviews virtually with three lifeboat instructors. The instructors were asked questions about how they provided instruction, assessment, and feedback and to comment on video examples of lifeboat operations in a simulator. The videos depicted a trainee launching the lifeboat, clearing away from an offshore installation, and manoeuvring the lifeboat in the simulator. The instructors explained how they use simulation-based training to help trainees practice lifeboat operations and build the trainees’ confidence and leadership skills as coxswains. Information from the interviews was used to develop a conceptual instructional model for an AIS. Future work will integrate the instructional model into the AIS and test its functionality for providing adequate instruction, deliberate practice opportunities, and corrective feedback to trainee lifeboat coxswains.
Mining Students' Digital Footprints to Enhance Simulator Training
Authors: Musharraf Mashrura , Smith Jennifer , Veitch Brian , Khan Faisal
Published: June 2023

Offshore emergencies are dynamic in nature and personnel on board are challenged with stress, uncertainty, and complexity. The lack of knowledge about how these factors affect peoples’ egress performance in emergencies undermines organizations’ ability to manage safety. A solid understanding of the impact of these factors on egress performance can help design better training programs. This paper investigates the effect of three factors: hazard proximity (to reflect stress), information quality (to reflect uncertainty), and situation familiarity (to reflect complexity) on seven different performance criteria of emergency egress. The performance criteria include mustering in time, maintaining a safe pace, keeping fire doors closed, avoiding interaction with hazards, reporting at the correct muster location, selecting appropriate personal protective (PP) gear, and selecting an efficient egress route. The investigation is driven by digital footprints of individuals performing in a training simulator under the influence of these factors. Besides measuring the impact of the factors, the data is also used to mine correlation among the performance criteria themselves (i.e. if a participant selects an efficient egress route, does that mean s/he will muster in time as well?). Finally, the data were analyzed to investigate if task performance can be modelled as a function of the factors that were identified to have a significant impact. Plotting the relationship between a performance criteria (outcome variables) and the significant factors (predictors) helps visualize the plausibility of a predictive model. In cases where predictive models were deemed plausible, binary logistic regression models were used as all performance criteria were categorical and dichotomous. The models predicted the probability of success in the performance criteria under the pressure of an emergency. The predictions are an indication of the degree of emergency preparedness of participants subsequent to training. A high probability of success in each criterion increases confidence in the training program. A low probability of success in one or more criteria highlights the gap in the training. The corresponding logistic regression model can provide direction on how the gap can be addressed.
Distributed leadership and seafarers' emergency response in a simulated navigation environment
Authors: Shroff Delna
Published: June 2023

Merchant shipping is an occupation with a high rate of fatal injuries caused by accidents and maritime disasters. Human error plays a massive role in accidents; however, the shipping industry lacks substantial human factors research. A human factor, particularly leadership, has been implicated in numerous maritime disasters. However, there is a tendency for most research to focus on holders of formal positions. A lot of previous work on leadership has been carried out on the assumption that leadership rests with a single leader. The current study adopts a practice-based perspective to examine distributed leadership among seafarers. A simulation is used to investigate the relationship between one form of distributed leadership i.e., planfully aligned leadership, and the emergency response of the team members in a simulated navigation environment. The results showed that planfully aligned leadership was a positive and significant predictor of the team’s emergency response as compared to authoritarian leadership. This study makes a shift from the unitary view of the leader to a more practice-based perspective whereby leadership is conceived of as a collective social process emerging through the interactions of multiple actors seems to be the need of the hour. It would be worthwhile to study different configurations of distributed leadership and analyze the factors that facilitate distributed leadership.
Applied Cognitive Task Analysis (ACTA) of marine piloting in a Swedish Context
Authors: Berlin Cecilia , Praetorius Gesa
Published: June 2023

Modern-day marine pilots are a competent and experienced workforce. They are highly skilled navigators that support the merchant fleet in transiting through challenging sea areas and rivers, as well as in the navigation in and out of ports. In this study, Applied Cognitive Task Analysis (ACTA) was used to pursue a deeper understanding of expertise and tacit or procedural knowledge that experts rely on and exhibit, mostly in safety-critical situations. ACTA is a structured interview method, which relies on three distinct phases: a task diagram, a knowledge audit and a simulation interview. In this article, results from the first two interview steps are presented to show the intricate complexity of pilotage and building blocks of expertise within marine pilotage. A total of eight experienced pilots from two different port areas in Sweden were interviewed. The results show that there are large differences in how pilotage is conducted in the two areas with regards to both tasks, knowledge and understanding of the service as such. Further, despite recognizing maneuvering as cognitively demanding, the pilots emphasized social skills and learning on the job as key elements of expertise. Conclusions drawn from the ACTA structure highlight the mentally and socially complex task that piloting is, and that the pilots use great discernment and acuity when processing verbal and non-verbal input, as well as physical human and vessel movements.
Laterality in Gesture-Based Video Games
Authors: Kumar Mritunjay , Bhushan Braj , Sameer Ahmed , Kundal Amit
Published: June 2023

Brain lateralization refers to hemispheric dominance for different tasks. Lateralization of the brain and body has been consistently reported in the literature. An extreme right-hand preference has been reported among most people throughout the world. However, gesture control involves coordination among the eye, hand, and foot, and the lateralization pattern of all three is expected to influence such gestures. This study examines the effect of lateral bias in gesture-based video games. The experiment involved 23 students playing a gesture- based game on an Xbox console to determine the interplay of hand-foot lateralization in gesture-based games. The findings are discussed in light of game design and lateral bias in gesture-based games.
Rehabilitation behavior intention of upper extremity stroke patients by IMVT
Authors: Chen Wen-Chi , Wu Chih-Fu
Published: June 2023

In recent years, studies have shown that mirror therapy can improve the rehabilitation effect of upper extremity stroke patients. On the other hand, with the advancement of virtual reality technology, relevant rehabilitation medical researchers have widely introduced virtual reality technology into the rehabilitation medical system. This pilot study investigates the effect of the integration of mirror therapy and virtual reality technology (IMVT) with somatosensory game elements on upper extremity stroke patients. Based on research ethics, patients with upper extremity stroke were first consulted about their willingness to participate in the experiment, and the experiment was carried out with the patients’ consents. In this preliminary study, a total of 38 upper limb stroke patients were willing to participate in this ethical research investigation. Thirty-eight patients included 21 males and 17 females, with an average age of 53.8 and 55.4, respectively, are shown a demonstration video, made by the physical health personnel, of how to operate the equipment integrating mirror therapy and virtual reality before participating the experiment. The upper limb stroke patients who agreed to participate in the experiment after browsing the video are given a questionnaire survey on the rehabilitation behavior intention of the patients. The questionnaire used in this research is based on the literature survey of extending the unified theory of acceptance and use of technology II(UTAUT2) proposed by Venkatesh et al. (2012), and the questionnaire items are selected through interviews with rehabilitation medical experts from accredited institutions. The content of the questionnaire included five exogenous variables, namely, "performance expectation", "effort expectation", "social influence", "hedonic motivation" and "game setting", one endogenous variable of "behavioral intention" as well as twenty indicators. The statistical tool PLS-smart was used to perform PLS-SEM (Structural Equation Modeling) analysis on the data. The analysis results found that "hedonic motivation" has a significant impact on "behavior intention" in the SEM model. According to patient interviews and SEM analysis, it can be inferred that the increase in content of hedonic motivation can improve patients’ rehabilitation behavior intentions. In contrast, since upper limb stroke patients still question this novel rehabilitation method, performance expectations, effort expectations, social influence, as well as, game setting, are insignificant in behavioral intention.
Training and competency development on virtual safety training
Authors: Heilala Janne , Kwegyir-Afful Ebo , Kantola Jussi
Published: June 2023

In this paper, we explore cutting-edge technologies that enable virtual safety and control systems, drawing upon both traditional and recent literature on human system integration in operational contexts. Our objective is to enhance mission effectiveness and human well-being through the recommendation adoption of virtualization techniques. To achieve this, we design virtualized missions that facilitate the adoption of operational procedures across different organizational teams. The development of successful personnel simulations demands experience in creating training scenarios in industrial open field environments, leading to improved virtual safety experiences for personnel with reduced training infrastructure needs. Our findings reveal that networking-based virtual training and human system integration, implemented on a system-to-system basis, can support physical simulations. By integrating artificial intelligence, we can enhance data collection and support human operations. Future research should focus on refining training and competency, with a particular emphasis on improving data capture and information processing to bolster human decision-making and performance.
Understanding the Challenges of Today’s Labor Market Service Provision in the EU
Authors: Liutkevicius Markko , Weck Marina , Ben Yahia Sadok
Published: June 2023

This paper explores the challenges of today’s labor market service provision in the EU, where, based on our expertise, insufficient scientific inquiry has been conducted. As there are many different focus points and factors to consider in the modern turbulent labor market, we identify the main challenges along with a list of existing scientific discussions. The central finding of the paper is that there is a lack of central collaboration between stakeholders and poor attention toward implementing changes required to meet labor market needs. We found that change management is insufficiently integrated into the service provision of the EU’s public employment services. This study contributes input for building an artificial intelligence-enabled virtual assistant to help serve the needs of labor markets and citizens.
Barriers to Digital Transformation of the Silver Economy: Challenges to Adopting Digital Skills by the Silver Generation
Authors: Azmat Butt Sidra , Lips Silvia , Sharma Rahul , Pappel Ingrid , Draheim Dirk
Published: June 2023

In the European Union (EU) and the Baltic Sea Region (BSR), life expectancy amongst the population has increased. As the population ages and the percentage of older people in the total population upsurges, there is a dire requisite to address their needs such as higher risks of chronic disease, dependability, disability and a requirement for assistance. Another integral challenge for the elderly is the need to participate in economic and social activities. It is essential to develop systems to ensure that the needs of the ageing population are met efficiently. Information and Communication Technology (ICT) and innovations such as robotics, artificial intelligence (AI), cloud computing and digital infrastructure help facilitate healthy and active ageing, as well as independent living solutions for the elderly. With all these technological advancements being introduced, the silver generation must be also capable of adopting them. The innovative solutions can be deemed a waste of resources if the target group is incapable of benefitting from them. In this research, a systematic literature review is conducted to identify the technology readiness, technology acceptance and level of digital skills of the silver generation as well as the barriers and challenges towards the adoption of digital transformation in the silver economy. The resulting articles are analysed using thematic analysis with NVIVO and the main outcomes help in identifying and analyzing the attitude of the silver generation towards ICT, barriers and challenges to ICT adoption and the existing digital tools and solutions that are easily adopted by the silver generation to serve as benchmarks to introduce further innovations for the silver economy. Moreover, recommendations are provided on how digital transformation can be used as a tool to engage the elderly in the economy by addressing the hindering factors to ICT adoption. Overall, the findings of this research contribute to the literature and can serve as a useful resource for other regions facing similar challenges in addressing the needs of an ageing society.
Transnational Innovation Networks, Population Aging and The Silver Economy: Challenges, Opportunities and the State of Play
Authors: Blake Jackson Eric , Pappel Ingrid , Ben Yahia Sadok
Published: June 2023

Globally, lower fertility rates combined with increased life expectancy and the transition of “baby boomers” toward retirement have contributed to an aging population in many societies. Ultimately, these demographic developments contain immense societal and economic implications for the public and private sectors. Subsequently, the term “Silver Economy” has been used to describe the delivery of products and services to older people, with a particular focus on leveraging Information Communication Technologies (ICTs) to improve the well-being of older citizens in multi-faceted domains: healthcare, the labor market, social care, mobility, housing, and many others. In an increasingly globalized knowledge economy, regional knowledge sharing, integration, and synergy can enable innovation in the Silver Economy and combat population aging. Transnational innovation networks (TINs) represent a pathway for achieving these goals. Although research exploring population aging, primarily from the EU, has grown in the literature over the past five years, there is a knowledge gap regarding transnational innovation approaches, platforms, and initiatives in the Silver Economy domain. Thus, this paper utilizes a literature review approach from a global perspective to survey the Silver Economy and population aging transnational innovation landscape. Our state-of-the-art review shows the importance of transnational knowledge flows enabled by TINs and subsequent innovations.
Customer-Oriented Service Innovation Grounded in Data-Driven Decision-Making: A Readiness Assessment Framework
Authors: Weck Marina , Kedonperä Sonja , Sihvonen Markus
Published: June 2023

In the current increasingly competitive and technologically advanced market, significant opportunities to develop service innovations can be realized by utilizing data-driven decision-making (DDDM), which has been widely recognized as an effective means of making decisions that are more informed and based on evidence. Service innovation (SI) grounded in DDDM, or data-driven service innovation (DDSI), refers to integrating data-driven thinking or simply the use of data into the SI development process. However, the large variety of data available for organizational use creates pressure to achieve the capabilities necessary to obtain high-quality and time-sensitive data from internal and external sources, while also organizing and analyzing it properly. These capabilities present a particularly significant challenge for many firms seeking growth by triggering customer-oriented SI. Hence, firms must systematically evaluate the maturity level of their capabilities, enabling effective customer-oriented SI grounded in DDDM. This study sought to establish an approach to assess a firm’s readiness to implement customer-oriented DDSI and to explore the capabilities imperative for its implementation. Based on a theoretical analysis, a readiness assessment framework for customer-oriented DDSI was conceptualized by adopting a process view and utilizing the Business Process Maturity Model (BPMM) for the maturity assessment of the key capabilities identified, including DDDM. With a well-established framework, this study proposes a practical guide for firms looking to implement a customer-oriented SI grounded in DDDM.
Econometric analysis of the determining factors of the balance of emotions of people with disabilities in Chile
Authors: De La Fuente-Mella Hanns , Lay Nelson , Cortés Camila , Espinoza Mercedes , Arizaga Cristóbal
Published: June 2023

The research proposes a logit econometric model that allows determining the factors that improve the balance of emotions of people with disabilities in Chile. In the research, the different variables that influence the phenomenon of disability are studied and identified. Through binomial models, the determinants of disability are estimated using the Social Well-being Survey, designed by the Undersecretariat for Social Evaluation of the Ministry of Social Development. The results indicate that factors such as educational level, health conditions, recognition at work, mood and quality of life, significantly indicate the emotional balance of people with disabilities in Chile. This is how the variables related to recognition at work and security at home have the greatest impact on the emotional level of people with disabilities in Chile.
Enabling active learning experience in XR environments – identifying the design elements for XR learning objects
Authors: Paananen Henry , Prendergast Trevor , Salminen Vesa , Torkkel Juha-Matti
Published: June 2023

This research focuses on identifying the design elements for XR learning objects. In this research the data gathered is focusing on the Finnish secondary level education pilot projects which use XR-environments. In this concept paper we present the identified phases for data collection. The identified phases are teacher’s design documents, the planning, implementing phases and reflection phase. Data is collected from teachers that are designing the learning object for XR environment.Extended Reality (XR) is an umbrella term for virtual, mixed and augmented realities. Commonly they’re known as Virtual Reality (VR), Mixed Reality (MR) and Augmented Reality (AR). VR is usually associated into Head Mounted Displays (HMD) and they’re referred as VR-glasses in common language. VR-glasses are basically creating stereoscopic picture and it creates the user feeling like they’re immersed in the 3-dimensional space. (Milgram & Kishino, 1994)XR-environments provides many possibilities to support learning. When XR is used effectively in learning, it increases the participant’s interest in and focus on the learning task. XR makes it possible to look at things that would not otherwise be so well illustrated in the real world. Augmented reality increases students motivation and helps them explore the existing environment (Sotiriou & Bogner 2008). Several studies show that the use of AR in education leads to enhanced learning outcomes (Akçayır & Akçayır 2016).Data is collected nowadays everywhere but there’s a big gap in utilizing the data for the purposes to develop learning and pedagogy. Most of the data applied is for business and management purposes. The term Educational data mining has been firstly mentioned in half of the 2005 and since that the applications and research of this field has been growing. One of the substudy fields of EDM is Learning Analytics which is defined as measuring, collecting, analysing and reporting of data from acquired from learning environments (Larusson & White, 2014; Siemens & Baker, 2013). Learning analytics interprets the collected data from various sources. Data is collected from various learning environments which leave “digital footprints” from student interactions. The data is analysed to make predictions, to visualize learning progress and to make interventions in learning processes. Learning analytics field doesn’t limit only to algorithm based interpretations of learning but it could utilize different techniques to analyze the data properly. (Johnson et al, 2011).