Reviewerly/exHarmony huggingface dataset:
Augmented Social Meal via Multi-sensory Feedback Modulated by Bodily-In-Coordinated Measures

We study how people can affectively engage with one another, using the everyday social setting of an informal meal augmented by media fields sensitive to measurement of coordination. Our contributions are (1) to extend the study of social engagement from dyadic one-to-one interactions to ensemble activity, in which joint intention and coordinated activity of three or more people cannot be reduced to dyadic interaction, and (2) to create computational media techniques, social wearables, that enhance our bodily ability to communicate and empathize with others, to express with additional layers of social signaling that uses responsive haptic, sonic and visual media that are modulated by measures of ensemble togetherness such as group movement coordination. Our findings as design insights may inspire those particularly focused on the experimental design and development of technology intended to support co-located, embodied interaction.
A Drone-mounted Depth Camera-based Motion Capture System for Sports Performance Analysis

Video is the most used tool for sport performance analysis as it provides a common reference point for the coach and the athlete. The problem with video is that it is a subjective tool. To overcome this, motion capture systems can used to get an objective 3D model of a person’s posture and motion, but only in laboratory settings. Unfortunately, many activities, such as most outdoor sports, cannot be captured in a lab without compromising the activity. In this paper, we propose to use an aerial drone system equipped with depth cameras, AI-based marker-less motion capture software to perform automatic skeleton tracking and real-time sports performance analysis of athletes. We experiment with off-the-shelf drone systems, miniaturized depth cameras, and commercially available skeleton tracking software to build a system for analyzing sports-related performance of athletes in their real settings. To make this a fully working system, we have conducted a few initial experiments and identified many issues that still needs to be addressed.
VR and AR Application in Academia, Overview in the Middle East Universities

VR and AR is a technology that is being applied in various Universities in Middle East. The application in laboratories is done with the aim to contribute to the modelling of buildings and structure in different Departments such as Architecture, Civil-Mechanical-Electrical Engineering, and others. In each of these disciplines the VR and AR have different purposes. However, the overall aim is to assist the students in the learning process of the complex environment of construction. The methodology to be followed in this study is as per the below steps: The aim of this study is to increase the application of VR and AR in the academic environment in order to prepare the new generation for the digital future. This is achieved by having an overview of current applications of the VR in the Middle East top Universities, followed by the application in the UAEU, Architectural engineering Department, Design Studios. The findings of this research can be of great use to the Academic of Engineering College in UAEU but also the industrial sector in UAE.
Personality Traits as Predictors for Social Engineering Vulnerability

As security measures to protect against cyberattacks increase, hackers have begun to target the weakest link in the cybersecurity chain–people. Such attacks are categorized as Social Engineering and rely on the manipulation and deception of people rather than technical security flaws [4]. This study attempts to examine the relationship between people and their vulnerability to Social Engineering attacks by posing the following questions: (1) what relationship, if any, exists between personality traits and Social Engineering vulnerability, and (2) what relationship, if any, exists between personality traits and the speed at which an individual makes cybersecurity-related decisions. To answer these questions, 79 undergraduate students at the University of Hawaii were surveyed to measure their personality traits and cybersecurity awareness. The survey results indicated that there was no significant correlation between the measured personality traits and measured vulnerability. The relationship between different personality traits and the elapsed time to complete the survey was slightly more significant; however, it was still statistically insignificant overall.
What is the New Future of Work for UX Research Practice? Assessing UX Research Practice During the COVID-19 Pandemic and Beyond

The User Experience (UX) Research profession was particularly impacted by the COVID-19 pandemic shift to remote work, as their work is largely dependent on engagements with customers, stakeholders, co-workers, and colleagues. The new future of work for UX research practice is still uncertain. Therefore, our study seeks to (1) address how COVID-19-associated remote work impacted UX research practice and (2) assess changes to UX research practice considerations, including methodologies, tools, and applications. We conducted a survey of UX research professionals with 52 open- and closed-ended questions to assess demographics, application and tool use, and UX research practice factors before and during the COVID-19 pandemic. A total of 220 UX research survey respondents world-wide responded to the survey. We found an increase in use of virtual applications and tools, virtual studies, and a mix of positive and negative COVID-19 impacts on UX research practice. Respondents reported changes to how they recruit participants, what study design methods they employ, how they analyze data, and how they share findings with stakeholders as likely to persist post pandemic. This study aimed to assess the impacts of remote work on UX research practice to support the new future of work initiatives and identify best practices.
Impact of Multisensory XR Technologies on Museum Exhibition Visits

The use of digital technologies in museums is becoming increasingly popular, with a growing trend towards using multisensory eXtended Reality (XR) technologies to enhance visitor engagement and involvement. XR technologies like Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) have the potential to bring numerous advantages to museums, including increased accessibility and inclusivity. By allowing visitors to experience a sense of immersion and actively engage with cultural artifacts, XR technologies can improve emotional engagement and learning activities. However, the integration of these technologies is often related to temporary exhibitions, and there are concerns about the costs associated with implementation and the potential for technology to negatively impact the visitor experience. Despite these challenges, evaluating the impact of multisensory XR technologies on visitor experience is difficult. This paper outlines a laboratory-based research activity that compares the impact of traditional exhibitions and XR technologies on visitor experience and learning performance. The study simulates a museum exhibition and allows the user to interact with different paintings using different XR technologies in a controlled environment.
Learning Labs and Virtual Reality. The Metaverse to Enhance Learning

Virtual Reality (VR) is one of the scientific and technological frontiers of our era, a new mode of knowledge that puts the person at the center, becoming the highest point of approach of technological interfaces towards a progressive incarnation. This research is based on the prototype construction of a VR laboratory teaching project, in which, through an immersive experience, students will be able to experience simulations of different educational moments in kindergarten. The virtual environment is built with 360°video that allows students to look in all directions, to facilitate the exploration of the environment, observe the individual reactions of the children, decide where to place themselves in the space. We investigate the relationship between experiential teaching through VR and learning and if mnestic skills were implemented through this approach. Exploration of a new environment promotes memory formation through the concept of novelty mediated by hippocampal dopamine and has also shown that new environments not only promote learning in these environments but can also promote long-term enhancement for events occurring before/after exposure to the novelty. In fact, a new episode’s memory is formed immediately after the experience and can last a lifetime. The hippocampal network plays a key role in the rapid acquisition of a memory of a once-in-a-lifetime experience, in which the novelty component of the experience promotes the prompt formation of the memory. Furthermore, dopamine has been documented to be the neuromodulator most implicated in novelty signaling [1], and the dopaminergic system is closely related to learning [2].
Chatbots and Children with Special Educational Needs Interaction

Introduction and aim. Chatbots could have a strong potential for competence training, overcoming barriers, and wellbeing management for individuals with special educational needs. We carried out a review to describe the existing knowledge on design characteristics, and user involvement in research on chatbots related to individuals with special educational needs. Methods. We searched for publications on the topic in ACM Digital Library, Web of Science, PubMed, ERIC, Education Source, and proceedings from conferences on special needs education, and on health informatics. Results. A total of 9 studies were included in this review. Most of the studies used authoring tools to implement the chatbots or parts of them. Smartphones, tablets and PCs were the most common target devices for chatbots. End-users participated in the research mostly as experimental subjects to test the chatbot. Only one study involved participants as co-designers. Conclusions. Research on chatbots for individuals with special education seems to be in earlier stages. More high-quality research is needed, involving individuals with special educational needs in all stages of development and incorporating evidence-based training strategies.
Studying Human Factors Aspects of Text Classification Task Using Eye Tracking

Text classification has a wide range of applications in today’s world including filtering spam emails, identifying health conditions, categorizing news articles, business intelligence, and finding relevant legal documents. This has become scalable due to the use of supervised machine learning models which are usually trained on manually labelled text data and their performance is heavily dependent on the quality of training data. Manual text classification tasks involve a person reading the text and assigning the most appropriate category, which can incur a significant amount of cognitive load. Therefore, an in-depth understanding of human factors aspects of the text classification task is important, and it can help in determining the expected level of accuracy of human-labelled text as well as identifying the challenging aspects of the task. To the best of our knowledge, previous studies have not studied the text classification task from a human computer interaction (HCI) and human factors perspective. Our study is an early effort towards studying text classification task using eye-tracking information captured during the manual labelling process. We aim to analyze ocular parameters to understand the manual text classification process from an HCI perspective. We designed an eye-tracking study that involved 30 human subjects reading narratives of injury-related texts and selecting the best-suited category for the cause of injury events. Ocular parameters such as fixation count, average fixation duration, and pupil dilation values were recorded for each participant. Preliminary results from our study indicate that (a) reasonable level of average classification accuracy (75%) was observed for study participants, (b) a positive correlation between fixation count and fixation duration, and fixation count and pupil diameter was observed, and (c) we did not observe a consistent pattern between ocular parameters representative of cognitive load, the time taken to complete the task, and the classification accuracy, maybe due to underlying variations among humans and interpretability of textual narratives.
Multi-monitor System for Adaptive Image Saliency Detection Based on Attentive Mechanisms

One of the most powerful human-inspired cognitive processes adopted within robotics systems is visual attention to select salient information about the environment. The use of human-inspired cognitive processes has become an essential direction for the robotic research field, especially when robotics systems are deployed in complex and unstructured everyday environments where the limited computation capacity and the real-time requirements become the bottleneck of the system development. In the context above, developing a biologically plausible method must also meet the technical constraints needed to bridge the gap between bio-inspired influences and technical applicability. This paper proposes a bio-inspired visual attention system based on selective attention monitors to satisfy computational capacity constraints and identify semantically relevant information by prioritizing the visual stimuli based on both bottom-up and top-down information.
VPlaytime: Face-to-Face Recess in Virtual Reality Classrooms

Class break space is a potentially promising informal learning environment for both integrating formal and informal learning using Virtual Reality and supporting student self-regulated learning in art and design higher education contexts. The purpose of this paper is to (a) review research that support this claim, (b) conceptualize the connection breaking time, Virtual Reality, and self-regulated learning, and (c) provide a informal learning framework for using Virtual Reality to create between class that support student self-regulated learning. Implications a natural transition for connecting formal and informal learning for future research in this area are provided.
Exploring the Tensions of Self-tracking Wearable Technologies Through Design

In the last decade, the research interest in self-tracking practices mediated by wearable technologies has risen exponentially. A variety of contributions is focused on examining interaction modalities and user experiences to increase the usability and utility of such systems. However, several scholars are also committed to unveiling the inherent ethical, social and political implications of the self-tracking phenomenon, proposing an alternative perspective. Based on the review of contributions investigating polarities and issues in the landscape of self-tracking technologies, the current work proposes five interrelated tensions at play in the self-tracking domain. The tensions presented are allusion to objectivity and non-neutrality of numbers; trust in data and reliance on subjective experience; reductionism and complexity of lived phenomena; performance and wellbeing; and surveillance and self-surveillance. Rather than researching ways to avoid these tensions, the present contribution discusses the role that design may play in further exploring them. In particular, the paper illustrates studies leveraging speculative and critical design approaches to explore the ethical, political, and social issues of technologically-mediated self-tracking practices, as well as individuals’ relations with data, beyond conscious interaction.
An Exploration of Automatic Speech Recognition Within a Nordic Context

Automatic speech recognition (ASR) has become a familiar input component for voice user faces, such as texting, preparing structured documents, searching, and voice commands. Inclusive ASR is a premise for a sustainable HCI that supports all types of languages and users. ASR is quite robust for majority languages but still needs to be adequate for smaller languages. Moreover, specific user groups cannot use ASR due to, e.g., speech impediments or accents. This paper discusses the possibilities and limitations of ASR in its current form within a Nordic context raising the following questions: i) What is the state of ASR in terms of usability for smaller and minority languages, and ii) How is ASR discussed regarding future development and inclusion? The current research discusses such topics within the lens of ability-based participatory design established on exploratory data collection. Among other findings, the paper stresses that small and minority languages are neglected in ASR development from an international perspective. Consequently, these languages risk exclusion from the digital development of language technology.
The Effect of Information Type on Human Cognitive Augmentation

When performing a task alone, humans achieve a certain level of performance. When humans are assisted by a tool or automation to perform the same task, performance is enhanced—augmented. Recently developed cognitive systems are able to perform cognitive processing at or above the level of a human in some domains. When humans work collaboratively with such “cogs” in a human/cog ensemble, we expect augmentation of cognitive processing to be evident and measurable. This paper shows the degree of cognitive augmentation depends on the nature of the information the cog contributes to the ensemble. Results of an experiment are reported showing conceptual information is the most effective type of information resulting in increases in cognitive accuracy, cognitive precision, and cognitive power.
Immersion and Presence in Virtual Reality Applications for Physical Therapy and Upper Limb Rehabilitation

Human factors in the design of physical therapy virtual reality (VR) applications are important to consider in the creation of high-fidelity applications. The human factors contributing to the design concepts of immersion and presence in VR are inadequately understood. The aim of this study is to introduce a novel framework to design for immersion and presence in VR applications in the context of physical therapy in the virtual realm. The framework includes the dimension of self-embodiment for presence and realism for immersion. We present a use case of upper-limb therapy to demonstrate the framework’s utility in the design process of a gamified VR physical rehabilitation application. Design implications are discussed.
Archetypes of Blockchain-Based Business Models

Blockchain technology has the potential to significantly impact both existing and new business models. In existing business models, the use of blockchain can improve efficiency and security by providing a decentralized and tamper-proof way for conducting transactions and storing data. This can streamline processes, increase transparency, and increase trust as well as accountability among all involved parties. In terms of new business models, blockchain technology allows for creating entirely new types of businesses that were previously not possible due to the limitations of traditional centralized systems. As the blockchain technology has the potential to disrupt existing industries and create new ones, examining its impact on business models is highly relevant. Therefore, a framework for blockchain technology business models and archetypes for blockchain technology is developed based on various established ventures and literature about business models as well as blockchain technology. The results contribute to the blockchain literature by introducing a new framework for blockchain technology business models and new archetypes for blockchain technology.
Research on the Representations of Information in Koto Music Scores

This research analyzes the information in traditional koto scores, and proposes the representations of the information. Playing techniques and shoga are analyzed in koto part. The illustrations and icons of several playing techniques of left hand are proposed and evaluated by an experiment. The result indicates that these icons can be used in koto scores. Shoga (verbal description of melody or playing technique) is analyzed based on the most fundamental koto scores of Ikuta school and Yamada school. The result indicates that shoga has important information in koto scores. Then, score data format of koto part is proposed, and score display system of koto part has been implemented. On the other hand, melismas and rhythms are analyzed in voice part. Melismas (melody in syllable) are analyzed on the scale of koto music and the representation of melisma is proposed. The difference of rhythms between koto part and voice part is also indicated. Then, score data format of voice part is proposed. The score display system of voice part is under development.
Exploring the Efficacy of Persuasion Strategies for Different User Types in Games that Encourage Environmentally Behavior

With the ubiquitous use of the Internet and mobile technology, game systems are being used in various fields to achieve goals, including the environmental field. Research has shown that persuasion strategies are effective in encouraging people to behave in an environmentally friendly manner, and in order to better facilitate the achievement of goals, environmental persuasion games use a variety of persuasion strategies to change people's behavior and attitudes in order to promote environmental behavior. However, most current gamification systems treat users as a single group, and a one-size-fits-all design approach is likely to reduce the effectiveness of persuasion strategies for different types of users, and personalized environmental gamification systems for different user types are yet to be studied. To bridge this gap, we conducted a quantitative study with a large number of users to investigate the following questions: (1) Are persuasive strategies persuasive in promoting environmental behavior? (2) Are there differences in the effectiveness of different persuasion strategies to promote environmental behavior? (3) Is there a difference in understanding the effectiveness of the same user type when faced with different persuasion strategies to promote environmental behavior? (4) Is there an impact of understanding different user types on the effective-ness of the same persuasion strategy? Our results show that there are significant differences in the effectiveness of different persuasion strategies, and that different user types have different preferences for the same persuasion strategy. Based on our analysis, we provide corresponding personalized design suggestions to develop persuasive environmental applications for different user types.
CognitiveNet: Enriching Foundation Models with Emotions and Awareness

Foundation models are gaining considerable interest for their capacity of solving many downstream tasks without fine-tuning parameters on specific datasets. The same solutions can connect visual and linguistic representations through image-text contrastive learning. These abilities allow an artificial agent to act similarly to a human, but significant cognitive processes still need to be introduced in the learning process. The present study proposes an advancement to more human-like artificial intelligence by introducing CognitiveNet, a learnable architecture integrating foundation models. Starting from the latest studies in the field of Artificial Consciousness, a hierarchy of cognitive layers has been modeled and pre-trained for estimating the emotional content of images. By employing CLIP as the backbone model, significant concordant emotional activity was produced. Furthermore, the proposed model overcomes the accuracy of CLIP in classifying CIFAR-10 and -100 datasets through supervised optimization, suggesting CognitiveNet as a promising solution for solving classification tasks through online meta-learning.