bluuebunny/crossref_metadata_2025 huggingface dataset:
The Robustness of Human Advantage in Swarm Leader Identification
Authors: Deka Ankur , Sycara Katia , Walker Phillip , Li Huao , Lewis Michael
Published: October 2022

Control of robotic swarms through control over a leader(s) has become the dominant approach to supervisory control over these largely autonomous systems. Resilience in the face of attrition is one of the primary advantages attributed to swarms yet the presence of leader(s) makes them vulnerable to decapitation. Algorithms which allow a swarm to hide its leader are a promising solution. In prior work we found that using a graph neural network, GNN, a swarm could be trained to flock following a leader. An Adversary NN trained to identify that leader (naïve condition) performed substantially better than human observers. When the swarm was trained to hide its leader (deception conditions), however, the advantage reversed with humans outperforming the Adversary. This human advantage persisted even when the swarm and Adversary were jointly trained, allowing the Adversary to adapt to the swarm’s evolving strategies for hiding its leader. The present study investigates the robustness of human leader identification by testing identifications made in the presence of medium and high levels of visual clutter. Clutter degraded human performance to some extent but human accuracy in leader identification remained well above that of the Adversary in deception conditions. Human performance even approached that for an unhidden leader under joint training. This study confirms the robustness of the human superiority effect and argues for the inclusion of humans in AI systems which may confront learned deception.
Activity and Usability Evaluation of Alternative Protective Face Mask Designs
Authors: Cloet Alison , Yu Minji , Arnold Jessica , Griffin Linsey
Published: October 2022

This research aimed to evaluate the usability of three alternative protective face mask designs from the clinical perspective. In a remote study, dental students (n=38) with experience wearing N95 FFRs participated in a randomized wear trial with simulated activities to measure mask performance. A Likertscale survey instrument was developed to examine conditions of discomfort, fit stability, wear efficiency, and speech intelligibility. Survey results indicated the KN95 mask demonstrated the highest overall mask usability, followed by MNmask v2, and MNmask v1. While participants found MNmask v1 uncomfortable, the stability was rated highest during a head up and down activity ( M=3.54). Here, the KN95 mask had a lower rating ( M=3.36), revealing potential issues with a loose fit. MNmask v2 showed overall improvement from MNmask v1, but revealed complications with the paracord bands. The findings from this study may be applied broadly in improving mask performance and usability in protective face mask designs.
Ergonomics in the Design of a Greywater Treatment System for an Urban Informal Settlement
Authors: Thatcher Andrew , Todd Andrew , Davy Jonathan , Metson Geneviève S
Published: October 2022

Greywater disposal in urban informal settlements currently leads to the presence of potentially harmful wastewater in the community. In this paper we describe how HFE contributed to the improved design of a nature-based solution, constructed wetlands, implemented for the channelling and treatment of greywater in an informal settlement. Using observational ethnographic activity analysis in two phases, HFE was used to identify human user interaction issues requiring redesign and to evaluate the effectiveness of the design recommendations. The paper demonstrates the value of HFE to the design team in getting community members to use the constructed wetlands and to provide additional services to the community not envisaged by the design team.
Examining the effectiveness of a lower back exoskeleton in reducing discomfort and workload in vascular surgery
Authors: Wang Tianke , Norasi Hamid , Tetteh Emmanuel , Smith Tianqi , Mendes Bernardo C. , Susan Hallbeck M.
Published: October 2022

Musculoskeletal disorders and intraoperative pain are prevalent among vascular surgeons which can negatively affect their surgical performance and quality of life. The effectiveness of a lower back support exoskeleton to reduce discomfort of the back, subjective fatigue, and the workload associated with performing vascular surgery was evaluated, as well as the participants’ intraoperative upper body postures. Three vascular surgeons were asked to rate their discomfort and fatigue before, during and after performing surgery, and their subjective workload post-operatively. Inertial measurement units (IMUs) were used to measure their intraoperative body postures. No significant differences were found between exoskeleton and baseline discomfort, fatigue, workload, or intraoperative postures. This indicates that although the exoskeleton did not restrict the vascular surgeons’ postures, this exoskeleton was ineffective at reducing their discomfort or workload. Future studies with exoskeletons specifically designed for healthcare applications may show more efficacy in reducing the ergonomic risks to surgeons.
DURESS SCADA: A simulation platform to study user interface design for cybersecurity of industrial control systems
Authors: Wang Hao , Lau Nathan
Published: October 2022

Supervisory Control and Data Acquisition (SCADA) systems are widely adopted in critical infrastructures and prime targets of cyberattacks. Ecological Interface Design (EID) is postulated to be an invaluable framework for supporting operators to cope with cyber intrusions, particularly zero-day attacks because prior research has demonstrated effectiveness of ecological interfaces during unanticipated events. However, a suitable research platform is absent for studying user interface in cybersecurity of SCADA systems. This paper presents a SCADA system simulation being designed and implemented for the DURESS thermohydraulic process control simulation common in EID studies. Based on the open literature and industrial standards to ensure representativeness of industrial SCADA systems, the simulation includes two programable logical controllers, seven routers, and a server in a wired communication network. These components should be sufficient to study human response to common cyberattacks on SCADA systems and support future work in prototyping and evaluating user interfaces for SCADA cybersecurity.
Generation Z and E-Learning: COVID-19, Personality, and Technology Acceptance
Authors: Marcus Viktoria , Masrahi Alaa , Motamedi Sanaz
Published: October 2022

The COVID-19 pandemic has severely affected schools, with traditional in-person operation changing to remote online learning. The rapid, involuntary shift was met with resistance and acceptance in varying degrees by Generation Z students. This study seeks to develop an e-learning technology acceptance model for Generation Z students, with a focus on the environment created by the COVID-19 pandemic. A theoretical framework based on the Technology Acceptance Model (TAM) was extended by 8 factors based on literature review and student input from a prior focus group study and survey (Motamedi et. al., 2021). The survey had 3 parts: 1) background information, 2) personality traits, 3) acceptance model factors. Twenty responses were collected and analyzed using Cronbach’s alphas. The results found the survey items to have good internal consistency. The outcome of this study provides a baseline for future studies to validate the model. The framework provides understanding of Generation Z acceptance of e-learning.
Deep Learning-based human activity recognition using RGB images in Human-robot collaboration
Authors: Keshinro Babatunde , Seong Younho , Yi Sun
Published: October 2022

In human-robot interaction, to ensure safety and effectiveness, robots need to be able to accurately predict human intentions. Hidden Markov Model, Bayesian Filtering, and deep learning methods have been used to predict human intentions. However, few studies have explored deep learning methods to predict variant human intention. Our study aims to evaluate the performance of the human intent recognition inference algorithm, and its impact on the human-robot team for collaborative tasks. Two deep learning algorithms ConvLSTM and LRCN were used to predict human intention. A dataset of 10 participants performing Pick, Throw, Wave, and Carry actions was used. The ConvLSTM method had a prediction accuracy of 74%. The LRCN method had a lower prediction accuracy of 25% compared to ConvLSTM. This result shows that deep learning methods using RGB images can predict human intent with high accuracy. The proposed method is successful in predicting human intents underlying human behavior.
The Proximity Compatibility Principle and Its Applications to Human Perception of Graphic Displays
Authors: Connor Zoe A. , Wickens Christopher D. , Patton Colleen E.
Published: October 2022

When engineering graphs, it is important that the engineer consider what display format will lead to both the most accurate and most rapid processing of information. The proximity compatibility principle (PCP) states that graphs with high display proximity (ex: line graphs in which lines connect data points) are better for tasks where participants must mentally integrate data points and predict trends, and those with low display proximity (ex: bar graphs, whose data points are unconnected) should be better for tasks that require focused attention on one specific data point. Participants in this experiment viewed either a bar or line graph and answered a corresponding true/false question (requiring either focused attention on a data point or integration across the points). ANOVA results support the PCP, finding a significant interaction between graph and question type for the accuracy of graph interpretation. A follow up experiment examining performance on tasks that required a hybrid of integration and focused attention processing revealed that those questions emphasizing trend integration were better supported by line graphs, whereas bar graphs better supported categorical integration.
Initial Steps to Assemble a Home Monitoring Kit Prototype for Parkinson’s Disease: Applications of Design Heuristics and Formative Usability Testing with Young Participants
Authors: Algahimi Noha , Boswell Eileen , Lowndes Bethany R.
Published: October 2022

Patients with Parkinson’s disease (PD) find it increasingly difficult to maintain consistency of clinic visits. Additionally, current methods of tracking symptoms between appointments are often incomplete or inaccurate due to variability of patient self-report. This research includes a needs assessment, application of design heuristics, and the completion of usability testing, to assemble a home monitoring kit prototype to track PD symptoms. Design needs for patients with PD include larger font size and simplicity to encourage and support user interactions during motor skill and eyesight decline. Five design heuristics were applied to the kit to guide necessary components and instructions for participants to log mobility and digital tapping test results through a mobile device. Usability testing with four young participants (not diagnosed with PD) revealed opportunities to improve instructions including the use of pictures. Future design iterations and usability testing will target participants with PD for interaction with all components.
Footwear Design Considerations for an Aging Population from User Experience, Service, and Technology Aspects
Authors: Lee Sheng-Hung , Lee Chaiwoo , Yang Maria C. , Coughlin Joseph F.
Published: October 2022

Growth of the aging population is a systemic, social-technological challenge facing the world. Typical ways of designing and developing products for older adults have been disrupted by this demographic shift and the introduction of new technologies. This study focuses on indoor footwear design for an aging population to help designers consider aspects of user experience, service, and technology. We investigated older adults’ use and purchasing behavior through surveys and semi-structured interviews. We presented ten smart footwear concepts and ideas around internet-of-things (IoT) wearable devices, data privacy, and security issues to help identify their unmet desires and pain points. We conclude that, for older adults, wearing shoes represents their independence in life, that their foot healthcare problems vary widely, and that they are not equipped with the proper/optimal knowledge to choose the right footwear. Designers need to consider their physical limitations and cognitive load while conducting such research.
Measuring Mental Models: General Aviation Pilots’ Understanding of Preflight Weather
Authors: Kleber John , Thomas Robert , Domingo Cassandra , Blickensderfer Beth
Published: October 2022

Weather has contributed to hundreds of General Aviation accidents. Research suggests inadequate preflight planning and lack of aviation weather knowledge are contributing factors. This study describes the development of three mental model measures (departure, enroute, and arrival) designed to assess pilots’ understanding of current and forecasted conditions. Each measure requires pilots (n=23) to evaluate weather conditions (flight category) at different regions within the flight area. A two-way mixed ANOVA examined differences in pilots’ understanding of flight category across three preflight weather briefing conditions (flight services call, self-briefing, and a combined condition) and three phases of flight (POF). No significant interaction occurred between briefing condition and POF on pilots’ ability to identify the correct flight category. However, significant differences in pilots’ understanding of weather conditions occurred between phases. Pilots were most effective at assessing flight category/weather on the enroute mental model measure and least effective at assessing weather forecasted surrounding arrival.
Ground reaction force and plantar pressure distribution data Korean young adults during barefoot walking
Authors: Yoon Woojin , Kwon Yujin , Choi Seobin , Lee Jieon , Song Donghyun , Shin Gwanseob
Published: October 2022

Gait analysis has been used to evaluate disease progression and efficiency of rehabilitation. This study aimed to establish the population database of the vertical ground reaction force and plantar pressure time-series data during walking. Plantar pressure and ground reaction force data were collected from 171 asymptomatic young Korean adults, and the normality of the data were tested. The normative data of the spatiotemperal gait parameters, time-series vertical ground reaction force curves, and butterfly diagrams (center of pressure trajectory) were established. The data collected in the current study would serve as the reference gait data of young Korean population and help healthcare professionals assess the existence or severity of abnormal gait patterns of patients.
Using a Patient Work System Model to Systematically Assess the Social Determinants of Health
Authors: Rogers Courtney C. , Jang Sophia S. , Valdez Rupa S.
Published: October 2022

Exploration of patient work through the lens of the Patient Work System model (PWS) has typically concentrated on clinical tasks, noting only how broader contextual factors shape these tasks. The purpose of this research was to use the PWS to begin to explore patient work originating directly from these broader contextual factors, referred to as the social determinants of health. Transportation access to maternal health services was used as a topic for a case study. Semi-structured interviews with eight health care and human services professionals were analyzed through deductive and inductive processes. The results reflected the main factors of the PWS and identified unique sub-factors under person, physical environment, and organizational environment. This preliminary work demonstrates that there is potential to use the PWS to examine patient work arising from SDoH.
Slow and Steady: Examining the impact of hands-on instructions on learnability of a training simulator to enhance development of core skills in Central Venous Catheterization
Authors: Tzamaras Haroula M. , Brown Dailen C. , Gonzalez-Vargas Jessica M. , Moore Jason Z. , Miller Scarlett R.
Published: October 2022

Instructional design is the theory surrounding how learners perceive information and is prevalent in simulation-based medical education. Simulation is used for a variety of medical procedures including central venous catheterization (CVC). The dynamic haptic robotic trainer (DHRT) is a CVC teaching simulator developed to specifically focus on training the needle insertion portion of CVC. While the DHRT has been validated to teach CVC as well as other training methods, an opportunity was seen to redesign the instructions of the DHRT to increase the learnability of the system. A hands-on instructional walkthrough was designed. A group trained with the hands-on instructions was compared to a previous group to assess initial insertion performance. Results indicate that changing the instructional method to be hands-on may have an impact on system learnability and help reinforce development of core components of CVC.
A Preliminary Study of Modeling Driver Situational Awareness based on SEEV and ACT-R Models
Authors: Du Na , Wu Xingwei , Misu Teruhisa , Akash Kumar
Published: October 2022

In automated driving, it is important to maintain drivers’ situational awareness (SA) in order to help them avoid unnecessary interventions and negotiate challenging scenarios where human takeovers are needed. Our study developed computational models to predict a driver’s SA of a target object. Using the SEEV (Salience, Effort, Expectancy, and Value) and ACT-R (Adaptive Control of Thought-Rational) framework, the model achieved an accuracy of 78.3%, an F1-score of 0.66, and the area under the receiver operating characteristic (AUROC) value of 0.773 with object features as inputs. On average, the model had a Root Mean Square Error (RMSE) of 0.18 to predict the SA of a target object across participants. In relative to the existing models, our model not only had comparable predictive performance but also considered the underlying mechanism of SA to increase model interpretability. Our research will provide essential and necessary steps toward developing in-vehicle SA prediction and assistance systems.
PER4Mance Prototyping environment for research on human-machine interactions for alarm floods management: the case study of a chemical plant process control
Authors: Ung Karine , Montreal Omar Nemer Polytechnique , Krishna Aswin , Chioua Moncef , Doyon-Poulin Philippe
Published: October 2022

Alarm floods are dangerous because the quantity of alarms triggered is too numerous for operators to reliably implement the right corrective action. Process operators of complex systems, such as chemical plants or nuclear power production, are faced with alarm management systems that can be better built in consideration of human capabilities and limitations. Developing human-machine interfaces (HMIs) that better support operators is critical for ensuring the safe and reliable operation of critical systems and processes. The research team has developed an accessible and adaptable prototyping environment dedicated for research on alarm management and human-machine interactions in the process industry. The method used was to build on the Tennessee Eastman Process (TEP) simulator and incorporate Human-Machine design guidelines. The results are an open-sourced prototyping environment that incorporates data from a real chemical plant and integrates true alarm data and thresholds. At the end of this article, we share the Github link to the entire MATLAB, Simulink and App Designer files of PER4Mance: a prototyping environment for research on human-machine interactions for alarm flood management.
Organizational Sensemaking Systems as a Determinant of Successful Organizational Change: A Grounded Theory Approach
Authors: Michael Hughes James , Henning Robert A. , Robertson Michelle M.
Published: October 2022

Organizational Sensemaking has been in the literature for nearly three decades – however, classical theories of organizational sensemaking have studied it as an individual or team-level phenomenon rather than at an organizational level. As a result, the multi-level implications of organizational sensemaking and its relationship to organizational change have yet to receive significant empirical attention. A greater understanding of organizational sensemaking may yield insights on how the effectiveness of organizational change interventions can be improved. A grounded theory approach is being used to examine the introduction of a training program for corrections staff in support of participatory ergonomics to improve worker health and wellbeing. Early findings are being used to construct a theoretical framework to guide the design of organizational sensemaking systems (OSS). The potential for OSS to promote organizational situational awareness, shared mental models, and organizational readiness for change is discussed along with design implications and directions for future research.
Wearable Technology and Pulse Transit Time (PTT) Used to Assess Workplace Violence Incidents in Nursing
Authors: Hamidi shishavan Hossein , Henning Robert , Cherniack Martin , Kim Insoo
Published: October 2022

Nurses are exposed to incidents of workplace violence involving patients and their family members, and also coworkers. Studies of occupational stressors generally rely on subjective self-reports, questionnaires, or biometric and biochemical markers in long-cycle time intervals, but such assessments offer little guidance to HF/E intervention efforts. This study examined the viability of using wearable sensors to detect workplace violence incidents, and included measurement of pulse transit time (PTT) as a biomarker of continuous blood pressure. Six nurses were monitored over seven days. The electrocardiogram, PTT, and activity level were measured using a custom-designed armband. Participants used a wristwatch (Empatica E4) to log incidents, and a smartphone survey app to rate incident severity. Results show PTT was a more reliable indicator of workplace incidents than low- to high-frequency (LF/LH) ratio heart rate variability, offering a more robust way to continuously monitor critical events noninvasively over long periods in demanding work environments.
Human Factors at the Speed of Relevance for Agile Engineering
Authors: (Dick) Steinberg Richard , Grumman Northrop
Published: October 2022

Traditional Human System Integration (HSI) processes are at risk of being eliminated in the development process given the high velocity and continuous delivery methods of Agile and DevOps engineering. New processes and tools are needed to enable human factors practitioners to promote usable and effective products for users. This paper describes tools and approaches developed to synchronize HF and UX product design with quick-turn feature development in the DevOps environment. The process involved rapid user research survey and design validation usability testing tools for gathering feedback from users quickly enough to support DevOps and Agile timelines. The tools and processes afforded objective data to validate design decisions prior to agile development, which had become informal and based upon subjective judgement rather than empirical evidence to keep pace with the development velocity. The tools developed worked remotely to increase the ability to access users and decrease the logistics effort associated with gathering participants. This paper addresses a case study that successfully addressed the challenges for HF and UX practioners in our role of developing designs using agile and DevOps environment to improve the quality of the design proving relevancy.
Virtual Reality Streaming for Remote Medical Training: Evaluation of Interface Usability with Physicians
Authors: Bailey Shannon K. T. , McKenna Ryan T. , Abdo Nicole T. , Reiner Colleen C. , Okuda Yasuharu , Brannick Michael T. , Llerena Luis E.
Published: October 2022

A novel virtual reality (VR) system for streaming medical training was designed and evaluated from a user-centered perspective. We developed the VR user interface for remote medical training based on interviews with physicians who instruct medical simulation sessions. We then conducted usability tests with eleven board-certified physicians who specialize in Emergency Medicine or Obstetrics and Gynecology (OBGYN) Physicians used the novel VR system to watch stereoscopic video of a training simulation for an obstetrica emergency: management of shoulder dystocia. Physicians then rated the usability of the VR system. Th average usability rating was above an "A+" grade average on an industry benchmark scale.
The Effect of Correlated Observations on Human-Automation Interaction in a Signal Detection Task
Authors: Munoz Gomez Andrade Fernando , Duncan-Reid Jackson , McCarley Jason S.
Published: October 2022

Automated signal detection aids assist human operators in various activities (e.g., medical diagnosis). However, operators tend to interact with these aids in suboptimal ways. An under-considered factor that might influence operators’ aid use is the correlation between the aid’s and the operator’s observations. Although prior research has generally assumed that human operators and automated aids rely on independent information sources, correlated observations may be common in naturalistic automation-aided detection tasks. The present study explored the effects of correlated observations on automation-use by analyzing performance in a numerical signal detection task using the Contingent Cutoff (CC) model, a statistical cognitive model of automation-aided decision making. Participants completed the task with and without assistance of an aid, and in one of two conditions: correlated observations vs. uncorrelated observations. The CC model accurately described observed performance for both conditions. Overall aid use efficiency was unaffected by correlated observations.
Comparing two Designs for Removing edge Violation of Stereoscopic 3d Maps
Authors: Sun Ganyun , Liu Weilong , Zhang Yun
Published: October 2022

Stereoscopic 3D (S3D) maps present a faithful image of the Earth’s surface. A stereo edge violation occurs when an object appears to be in front of the screen and is cut off by the screen edge. Two designs are proposed to remove this artifact. One applies dynamic floating windows which cover the contents existing alone on the left or right edges of images. The other is to transform all the horizontal disparities to positive values; all the perceived 3D contents are behind the screen. This study compares the two designs with respect to user preference and visual fatigue. For the selected terrain scenes, participants preferred the design of pushing back to the design of dynamic floating windows. For visual fatigue, the design of dynamic floating windows obtained higher scores in Simplified Simulator Sickness Questionnaires (SSSQs) and General Eye Symptoms Questionnaires (GESQs), which indicated higher visual fatigue. This preliminary study observed that for removing edge violation of interactive S3D maps, the design of setting 3D contents behind the screen might be better than the design of dynamic floating windows in terms of user preference and visual fatigue.
Comparisons of Perceptions of Risk for Visualizations Using Animated Risk Trajectories Versus Cones of Uncertainty
Authors: Witt Jessica K. , Labe Zachary M. , Clegg Benjamin A.
Published: October 2022

Dynamic ensemble visualizations might effectively convey the future path of an approaching tropical storm, and they offer benefits over commonly used Cones of Uncertainty. This experiment examined perceptions of risk at coastal locations of varying eccentricity from the most likely forecast path of a hypothetical hurricane. Perceptions of high (need to evacuate) and moderate (need to prepare) risk from inbound storms dropped off dramatically for Cone of Uncertainty visualizations, consistent with the influence of a containment effect induced by the cone’s boundary line. In contrast, Animated Risk Trajectories offered a more continuous sense of declining risk with distance, and much higher rates of needing to prepare at larger eccentricities that while at lower risk would still be vulnerable to some potential future paths. The findings lend further support to the viability of Animated Risk
Quantifying the Potential of the Xtract Heatsaver System to Enhance Thermoregulation and Prevent Hypothermia in Combat Casualties
Authors: Lavender Steven A. , Kachlan Anas , Pennells Simon , Spence David
Published: October 2022

Conductive or convective heat loss is a serious concern in combat casualties that are an enhanced risk of hypothermia due to shock and environmental exposures. Eleven subjects participated in repeated measures study designed to assess whether alternative hypothermia prevention systems can retain body temperatures better in a cold environment than the currently fielded solution. Results showed that when the subjects were using the new Xtract Heatsaver System there was significantly less change in the body’s core temperature and less thermal discomfort as compared with the currently field Hypothermia Prevention and Mitigation Kit.
Using the National Aeronautics Space Administration Task Load Index (NASA-TLX) in surgery: Considerations for use “in the wild”
Authors: Zamudio Jennifer , Catchpole Ken , Kanji Falisha , Anger Jennifer , Cohen Tara
Published: October 2022

Despite a variety of attempts to infer measurements of workload through more objective means, the NASATLX remains the most preferred tool in various industries. Interest in patient safety and healthcare systems design has seen a frequent application of the NASA-TLX over other methods within a range of surgical settings and has generated other adaptations to increase its sensitivity to specific tasks. However, in moving out of simulation settings and into real-world surgical settings, there are a range of challenges that need to be considered and addressed that have not been regularly reported in literature assessing intraoperative workload. In this paper, we offer insights from both prior research and our own studies that illustrate the value of using the NASA-TLX, and the potential pitfalls, to understand workload in surgery.
Development and Validation of Extended Reality Attentional Visual Field Tasks
Authors: Mitchell Daxton T. , Leibman Daniel , Choi HeeSun
Published: October 2022

A visuospatial attention measurement tool such as the Attentional Visual Field (AVF) task has been widely used in prior research to assess the spatial distribution of visual attention using a computerized task displaying visual targets on a computer screen. Although this computer-based task has been useful for examining individual differences in visuospatial attention and associated safety implications such as crash risk while driving, the computer-based task is limited due to its constraints. Newer AVF tasks were developed using virtual reality (VR) and augmented reality (AR) technology, and the results of the two evaluation studies provided partial evidence for the validities of the new AVF tasks. Overall, our current findings suggest that VR and AR versions of the AVF task can capture some aspects of visuospatial attention and that further validation and improvement are needed to establish the robustness of these new methods.
Are Emojis Worth a Thousand Words? An Iconic Tool for Emotion Assessment
Authors: Susindar Sahinya , Schermuly Maja , Krall Nathaniel , Pham Taylor , K. Thomas
Published: October 2022

Assessments of emotional states are plagued with challenges in both the quantitative and qualitative realms. There is a lack of a definitive guide to making objective assessments based on physiological responses and qualitative methods lean heavily on subjective interpretation using self-assessments, both of which are hampered by individual differences. Self-assessment tools have largely used words or phrases to describe feelings however, iconic or visual tools are also gaining popularity. A significant number of such tools are based on the dimensional models of emotion and may not always suit the needs of studies on the role of emotions on cognitive abilities such as decision making. The tool described in this paper is developed based on two key requirements: 1) use in studying emotion and decision making, and 2) can easily be integrated into a context with a demanding primary task, such as driving, to be used concurrently with the task. A survey was conducted to identify emojis that are most commonly associated with basic emotions. Emojis were weighted and ranked for inclusion in the tool. The tool developed is called the Iconic Communication of Emotions (ICE).
Impacts of Enhanced Physical Abilities via Exoskeletons on Attentional Performance and Workload
Authors: Leibman Daniel , Mitchell Daxton B. , Choi HeeSun
Published: October 2022

Exoskeletons have great potential for reducing physical fatigue and work-related musculoskeletal disorders. Prior research investigating the effects of wearing an exoskeleton on the wearers’ cognitive performance suggested both potentially positive and negative impacts. However, the precise effects of wearing different types of exoskeletons on the individual’s various aspects of cognitive functions are under-studied. This study investigated the effects of wearing upper and lower-body unpowered exoskeletons on visual attentional performance while performing simulated industrial tasks, using an innovative augmented reality (AR)-based attentional visual field task. This study also compared physical task performance and self-reported mental workload while wearing an exoskeleton vs. not wearing an exoskeleton. While no universal change in cognitive performance with exoskeleton use was observed, the current study demonstrated large individual differences, which may have significant practical and theoretical implications.
Older Workers’ Perception of Exoskeletons and the Impacts on their Retirement Intentions
Authors: Valentin Yves , Choi HeeSun
Published: October 2022

Advancing worker assistive technology, such as exoskeletons, has been increasingly implemented in broad workplaces due to its potential to improve worker health and safety, as well as retain and increase productivity, especially among workers with limited physical capabilities and older workers. Exoskeletons available at physically demanding workplaces may enable older workers to have a positive outlook and motivation for their jobs, affecting their retirement attitudes. This study examined how industrial exoskeletons impact older workers’ retirement intentions. Results showed that older workers whose jobs involve physical demands are likely to have increased retirement age expectations and intentions to delay their retirements when knowing that exoskeletons are potentially available to assist them with their jobs. The findings suggest that worker assistive technology has the potential to improve older worker retention in the workforce and contribute to older adults’ health, safety, and well-being.
Open Source Software Architecture for Computer Based Procedure Systems
Authors: Lew Roger , Ulrich Thomas A. , Boring Ronald L.
Published: October 2022

In the US and globally Advanced Reactors are being developed. These Nuclear Power Plants (NPP) will utilize modern engineering and simulation tools, as well as modern control systems. New plants are safer and more flexible than previous generations. New opportunities exist for how plants could manage and operate reactors. Specifically, future plants could utilize fleet management and reduced staffing to decrease operational expenses. Tools are needed to support the development of computer-based procedure systems for advanced reactors. Here we find inspiration from scientific open source software tools (Python, Jupyter Notebook, Jupytext, Jupyter Book, Rmarkdown, Rstudio, MarkDown, MyST, Sphinx, Git) for rapid prototyping and evaluation of computer based procedure systems to support the design and evaluation of novel concept of operations for new reactors, conducting engineering tests, validating and optimizing operations using machine learning.
Revisiting Risk Perception Measurement in Aviators: Scale Development and Validation
Authors: Trabysh Victoria , Keebler Joseph R. , Winter Scott R.
Published: October 2022

Approximately 85% of aviation accidents are attributed to pilot error (FAA, 2009). Given this knowledge, studying the thought processes of pilots, particularly how they perceive risk, is of considerable interest among aviation research. This static trend continues to emphasize the importance of seeking to understand the way in which pilots think, operate, and make decisions. Previous risk perception measures in the aviation domain have exhibited issues pertaining to construct validity, warranting the development of a new instrument. The purpose of this paper is to discuss the criticality of understanding risk perception and its implications, as well as the current scale development and validation process. Successful validation may result in a new standard measure of risk perception in aviators. In addition, this tool may facilitate further insight into pilot’s perceptions of risk, leading to a more robust understanding of decision-making in the cockpit.
Investigating the Effect of Personalization in a Mental Health App on Depressive Symptoms
Authors: Six Stephanie , Aly Heba , Byrne Kaileigh A.
Published: October 2022

Mental health apps have shown promise in improving quality of life in a variety of contexts; however, it is unclear how specific internal app features influence the effectiveness of such apps. The purpose of this study is to investigate the effect of app feature personalization, including avatar customization and naming, on depressive symptoms. A total of 59 students completed a 14-day trial utilizing a novel cognitive behavioral therapy-based app developed exclusively for this study. The study entailed a two-group experimental design with randomization to either a personalization or no-personalization version of the app. AirHeart successfully reduced depressive symptoms over the two-week period, but personalization of an avatar did not further this reduction.
The DataScope: A Mixed-Initiative Architecture for Data Labeling
Authors: Alsaid Areen , Lee John D.
Published: October 2022

Machine learning promises many advantages, but achieving these promises requires methods that smooth the interaction between humans and machine learning. Machine learning systems require meticulous training on large, labeled datasets. Labeling data is a tedious expensive process, and many times requires complex human-judgment skills. Mixed-initiative designs divide the labor between the artificial agent and the human to make the task at hand more efficient and effective. This paper proposes a mixed-initiative method for efficient coding of video and image data in general and emotion data in particular. We integrate an unsupervised dimensionality reduction algorithm and the R Shiny platform to develop an interactive method that leverages human expertise to label the data more efficiently and effectively. The method, through the interactive web tool, allows the user to explore the data interactively, examine similarities and dissimilarities in the data, and label clusters of many images and video frames at once. The combination of the unsupervised learning algorithm and the R Shiny platform enables interactive exploration and annotation of high-dimensional, complicated data. This method can be used to annotate large data sets faster and can advance research in machine vision.
Designing for Mutually Beneficial Decision Making in Human-Agent Teaming
Authors: Mallick Rohit , Sawant Sarvesh , McNeese Nathan , Chalil Madathil Kapil
Published: October 2022

This paper presents a joint decision-making framework between human and artificial intelligent agents in an effort to create a cohesive team uninhibited by each other’s actions. Based on the well-known Recognition Primed Decision-Making Model, our framework expands upon RPD’s single decision maker to be more Human-Agent Teaming (HAT) oriented. Specifically, our framework includes three layers of shared cognition to ensure both a consistent level of transparency between members and the efficient completion of the task. The first layer provides itself as a foundation of expectations that provides familiarity recognition in a situation. The second layer categorizes the environmental features into relevant decisions informing the symbiotic nature of who should and how to enact decisions collaboratively, which is the third layer. Altogether, this mutually beneficial decision-making model emphasizes transparency so that both humans and artificial agents are equal partners in completing tasks in unique situations.
Bruce Protocol Test affects Postural Stability in Healthy Young Adults
Authors: Germanos Andreas , Heiberg Tessa , Jeon Annie , Heisterkamp Emi , Giang Hao , Cota Jessica , Corona Laura , Loi Thomas , Bovino Vincent , Cordero Shayce , Kim Sunny , Shiraishi Michael , Soangra Rahul
Published: October 2022

Maintaining balance is key in avoiding falls and injury. However, little is known on how increased cardiac activity may affect postural stability. This study investigated if increase in cardiac activity to 85% maximal heart rate (HR) when exercising with standard Bruce Protocol Test (BPT) influence postural sway. Ten young adults were tested for three postural stances, quiet bilateral standing with i) eyes open, ii) eyes closed, and iii) tandem stance, before and after performing the BPT. Resting Heart Rate (HR) and HR variability along with standard postural sway parameters like sway velocity, sway area, turn index, and power frequency in the anterior-posterior (AP) and medial-lateral (ML) directions were evaluated. We found significant increases in postural sway values for turn index values due to HR changes. Thus, balance demanding tasks may be avoided immediately after performing submaximal cardiac activities in order to avoid fall risk and injury.
Digital Privacy of Assistive Technology Users with Visual Disabilities
Authors: Nam Kim Hyung
Published: October 2022

As technology is advancing, accessibility is also taken care of seriously. Many users with visual disabilities take advantage of, for example, Microsoft's Seeing AI application (app) that is equipped with artificial intelligence. The app helps people with visual disabilities to recognize objects, people, texts, and many more via a smartphone's built-in camera. As users may use the app in recognizing personally identifiable information, user privacy should carefully be treated and considered as a top priority. Yet, little is known about the user privacy issues among users with visual disabilities, such that this study aims to address the knowledge gap by conducting a questionnaire with the Seeing AI users with visual disabilities. This study found that those with visual disabilities had a lack of knowledge about user privacy policies. It is recommended to offer an adequate educational training; thus, those with visual disabilities can be well informed of user privacy policies, ultimately leading to promoting safe online behavior to protect themselves from digital privacy and security problems.
The Effects of Background Noise on User Experience and Performance of Mixed Reality Voice Dictation
Authors: Sinlapanuntakul Pitch , Skilton Katlyn S. , Mathew Jose N. , Chaparro Barbara S.
Published: October 2022

From education to manufacturing and medicine, the Microsoft HoloLens 2 mixed reality headset has been increasingly adopted. Text entry is a core functionality of the HoloLens 2, enabling communication and search features. The device tracks hand and finger movements interacting with a virtual keyboard but is slow and cumbersome. Speech-to-text dictation is a promising alternative requiring less physical effort and time. However, the HoloLens 2 dictation performance in environmental settings with varying noise levels is unclear. This study investigated the text input accuracy (WER), speed (WPM), and user perceptions of the HoloLens 2 dictation across three background noise levels (40 dB, 55 dB, and 70 dB). The 70 dB condition resulted in inferior outcomes for text input speed, perceived usability, mental demand, temporal demand, and effort. Users also reported lengthy processing delays in the 70 dB condition, while accuracy remained consistent (2–5% WER) across all noise conditions.
Effects of Context, Assistance, and Communication on Beliefs About Cooperation in Human-Machine Teaming
Authors: Funke Gregory , Tolston Michael , Bowers Margaret , Holderby Katherine
Published: October 2022

The efficacy of future human-machine teaming will be determined by the ability of machine agents to engage in teamwork behaviors and processes with their human teammates. A critical aspect of teamwork is cooperation, as team members must work interdependently to achieve common goals. In the current experiment we investigated how violations of cooperation expectations, presented to participants in a narrative vignette, influenced ratings of cooperation on a novel measure derived from social interdependence theory. Our results indicated that participants’ ratings of cooperation were strongly influenced by actions associated with assisting and communicating with a cooperating partner; violations in these expectations resulted in much lower estimates of cooperation, though the identity of the actors as two humans or a human and a robot did not appear to matter. Overall, this is an important first step to understanding the factors that influence perceptions of cooperation in human-machine teaming.
Exploring the Eating-Out Experience of People With Vision Impairment in Korea: A Persona-Based Method
Authors: Hong San , Kim So-eun , Oh Min-ah , Kim Sung-min , Hwang Kitae , Hwan Yun Myung
Published: October 2022

This study aims to explore the eating-out experience of people with vision impairment (VI) with the persona method. People with VI are not privileged with information due to limited accessibility. Previous studies have suggested kiosks are the main barrier in the eating-out experience of people with VI. However, the quality of the experience of people with VI has not changed with accessible kiosks in the market. Researchers recruited seven people with VI and low vision for one-to-one in-depth interviews. The researchers created four personas and user journey maps to present critical points in each stage of the eating-out experience. Four major themes in the eating experience are created: 1) expanding accessible information, 2) autonomous behaviors and choices, 3) depending on people without disabilities, 4) people’s attitude toward people with VI. The result suggests future research must seek an alternative to providing people with VI with proper means of accessibility.
Investigation of the Joint Simon Effect with Human, Robot, and Computer Interface Task Partners: A Pilot Study
Authors: Sobel Briana M , Sims Valerie K
Published: October 2022

This pilot study assessed whether there are fundamental differences in how people perceive human and nonhuman task partners using a joint Simon task. Fourteen participants completed the task with human, robot, and computer task partners. Results showed no joint Simon effect for any task partner, and the robot and computer were both perceived as not very humanlike. However, while the robot was seen as less accurate and slower than the human task partner, the computer was consistently viewed as more accurate and faster. This indicates that there may be differences in user’s perceptions of different types of technological task partners, and that for certain tasks, robots may be seen as inferior while computers are viewed as superior.