Reviewerly/exHarmony huggingface dataset:
Generating Various 3D Motions by Emergent Imitation Learning

This paper proposed emergent imitation learning (EIL) using deep reinforcement learning (deep RL) to generate various 3D motions for a character agent in a virtual 3D physical space. In the conventional method, agents acquire a motion by learning to imitate a predefined reference motion as a teacher motion and then achieve a specific task. In this study, we introduce a "generational change" to the conventional method to elicit a motion derived from a reference motion. When a generational change occurs, new agents begin learning using the current agent's motion as a teacher. Experimental results showed that the motions derived using the proposed method differ from the teacher's motions and are more diverse, and the task achievement rating is higher than those obtained by a conventional method.
A Privacy-Orientated Distributed Data Storage Model for Smart Homes

With the wide adoption of smart home devices, users are concerned with what sensitive data these devices may be collecting and what that data may be used for. This paper proposes a way to reduce the level of dis-trust between the end-users and the companies that offer smart home hard-ware and/or personalised software services by allowing end-users to retain an optimal degree of control over their personal data (such as voice and video recordings) which is typically collected by the service provider and stored on the service provider's cloud platform.
What Color is Your Swan? Uncertainty of Information Across Data

In 2007, Taleb coined the term “Black Swan” to describe those events that are extremely rare but unpredictable. However, if as Taleb states it is “our blindness with respect to randomness particularly large deviations” that is the issue, then how do we continue to understand these potential deviations and how do we adapt when they occur? Researchers continue to explore the area of uncertainty, how it is quantified, represented, and communicated. This paper is inspired by the concept of uncertainty and the association with the swans’ color as a means of expressing the uncertainty. In addition, this paper will discuss the concept of uncertainty of information, utilizing a taxonomy based on Gershon’s nature of imperfect information with a value. Firstly, we will explore existing associations made to different swan colors. Secondly, we will discuss how this concept can be modified relevant to uncertainty of information, and the challenges this idea presents such as risk and trust. Thirdly, we will explore applying a modified version of “uncertainty of information swan color” to a specific application.
Towards an Interaction Design Framework for IoT Healthcare Systems

The rising prevalence of chronic conditions has fuelled the development of numerous devices and IoT systems to improve patients’ health outcomes. Despite the abundance of these solutions, their usability remains a significant challenge, hindering their adoption and effectiveness. This paper proposes a conceptual interaction design framework for IoT healthcare systems that prioritises the three critical components of usability: effectiveness, efficiency, and satisfaction. To develop the framework, we conducted a state of the art review and interviewed patients and health experts using the Design Sprint methodology. This resulted in the creation of three personas and their related user stories. Our framework consists of three main components: User Interfaces as Services, Context-Aware Interactions, and User-Centred Data Management. A hypothetical scenario of a digital companion for individuals with diabetes was used to demonstrate the feasibility of the framework. The results of the proposal underscore the importance of considering all stakeholders when designing IoT systems and highlight the potential for individuals to benefit from a more integrated and personalised experience.
A Machine Learning Approach to Prediction of Online Reviews Reliability

The Internet accompanies us in every moment of our lives, supporting us in many ways. Among these, it helps us when we want to choose the best services and products. So when it comes to picking a movie to watch, a restaurant to eat in, a hotel to stay in, or a product to buy, we grab our smartphone and visit one of the countless sites where users can report their experiences and read those of others. However, as often happens, even in this case there are possible scams of which we must beware. In this paper, we propose a machine learning system for predicting the reliability of online reviews. Specifically, our system collects reviews from Amazon, extracts various features, and gives them as input to an ensemble learning system based on three anomaly detection algorithms. To demonstrate the benefits of our approach, we report the results of a comparative analysis with some state-of-the-art systems using the data collected by ReviewMeta. These results have allowed us to realize how widespread the phenomenon of online fake reviews is.
A Comparison of Finger, Stylus and Mouse in Trajectory Tracing Task Execution on Touchscreen Mobile Devices

In this paper, we empirically investigate the performance of trajectory tracing on mobile touchscreen devices. Our main goal is to compare three different tracing modalities, two of which rely on direct touch (finger and stylus) and one on indirect interaction (mouse). We conducted an experiment involving 25 users and a specially designed mobile application for managing trajectory tracing tasks and touch events logging. We describe the outcomes of this empirical study, with particular emphasis on tracing time and tracing error on a touchscreen tablet. In addition, we also discuss the associated interaction workload, specifically targeting the physical demand, perceived performance and effort, and level of frustration when using different ways to trace the given path. Finally, we show how the obtained data can be used to develop predictive models for trajectory tracing time.
Design Recommendations Based on Speech Analysis for Disability-Friendly Interfaces for the Control of a Home Automation Environment

The objective of this paper is to describe the study on speech interaction mode for home automation control of equipment by impaired people for an inclusive housing. The study is related to the HIP HOPE project concerning a building of 19 inclusive housing units. 7 participants with different types of disabilities were invited to carry out use cases using voice and touch control. Only the results obtained on the voice interaction mode through the Amazon voice assistant are reported here. The results show, according to the type of handicap, the success rates in the speech recognition of the command emitted on the equipment and highlight the errors related to the formulation, the noisy environment, the intelligible speech, the speech segmentation and the bad synchronization of the audio channel opening.
Method for Assessing the Potential Impact of Changes in Software Requirements of Agile Methodologies Based Projects

The main issues in impact analysis of scope changes are the need for identifying other requirements potentially affected by the change and determining how complex is the change. These challenges are potentialized into projects based on agile methodologies, characterized by broad communication with the customer, which leads to more opportunities for change requests during the software development life cycle. We propose a new method in which agile methodologies can benefit from requirement traceability and effort prediction on scope changes. By applying the method to a software development project, the results are synthesized into indicators presenting how scope changes realized through different development iterations impact other software requirements and how the complexity of the requirement being changed can be used to determine the effort estimate. The main contributions of our work are (i) method aimed to provide a potential impact rate on scope changes in agile methodologies-based projects; (ii) metric for ranking software requirements based on their potential impact, supporting effort prediction and impact analysis; (iii) value range to determine the risk of accepting a scope change request; and (iv) discussion on the results from applying the approach in an agile software development scenario. Our proposal is intended to be used by software development teams in the context of agile projects.
Controllable Features to Create Highly Evaluated Manga

This paper proposes a set of features of manga works that are controllable by manga creators. The features are comprehensive and easily applied to modify manga works. A new feature to measure manga works, the character betweeness centrality, is proposed. Multiple sets of features with similar prediction accuracies are proposed, corresponding to the multiple viewpoints to evaluate manga works.
Automated Content Generation for Intelligent Tutoring Systems

The demand for eLearning systems has grown as education becomes a priority and the need for better technological assistance in learning increases. One type of software aimed at providing a more engaging and educational experience is the Intelligent Tutoring System (ITS). The ITS system featured in this research is called FAIE, which focuses on using Artificial Intelligence (AI) in learning. The blueprint-based approach allows educators to design content for students, but this raises two challenges. First, designing the content requires technical skills that can be time-consuming for educators with many tasks. Second, it is difficult to immediately codify an educator's intrinsic knowledge. To tackle these challenges, a Blueprint-designer was created to generate content based on a text prompt from the educator containing key information. The content consists of problems to be answered with correct answers and distractors meant to challenge the student. The process of generating QA-Pairs involves determining a list of possible answers using a Named Entity Recognition (NER) model and passing the answers to a Question-Generation (QG) model. The QG model is based on the T5 Transformer model, which was trained to output questions based on the context and answer. Finally, distractors are generated by training a sequence-to-sequence model, BART, on the RACE dataset.
A Clothing-Type Wearable Device that Promotes a Sense of Unity for Viewers of Online Live Performances

In this research, we developed a clothing-type wearable device called ONE Parka, which promotes an increase in the sense of unity in online live performances. In recent years, demand for live entertainment has been increasing. Nevertheless, it has become clear that, due to factors such as the difficulty of establishing shared sensory communication between performers and viewers in events held online, the degree of satisfaction towards such events is low. Accordingly, our research group conjectured that the direct cause of this low level of satisfaction is that viewers do not feel a sense of unity with performers. In this research, by promoting a sense of unity, we aim to increase the degree of satisfaction towards online live performance. Firstly, we defined the components that form the term ‘sense of unity’, then investigated appropriate approaches in the proposal of a device. We focused on one possible approach, ‘recognition of excitement’, and developed the prototype of ONE Parka, which is capable of providing feedback by heart rate and vibration. In an evaluative experiment, we had eleven subjects watch a music video while wearing the prototype and then answer a questionnaire. As a result, it became evident that vibration is effective in recognition of excitement.
Fundamental Considerations on Representation Learning for Multimodal Processing

In recent years, there has been an extremely active research boom in the fields of machine learning, particularly in artificial neural networks (ANNs). This boom was triggered by the extremely high performance of an image classification system based on cellular neural networks (CNNs) proposed in 2012. This is not only because of the high performance, but also because the proposed system uses GPGPU to reduce various computational costs, the ReLU function to prevent gradient vanish phenomena, and Dropout to realize a regularization. The availability of very easy-to-use deep learning modules such as TensorFlow and PyTorch also contributed to the rise of this type of research. As a result, various systems have been proposed and a variety of applications have been proposed. For example, the recent image generation model is a good example. On the other hand, theoretical analysis of such artificial neural networks is completely insufficient, and there is no rigorous explanation as to why each system works well. In deep learning to date, emphasis has been placed on improving the quality of output data, and little consideration has been given to the quality of information represented by latent variables from which features in the input information are extracted. On the other hand, improvement of representation learning by contrast learning, in which latent variable representations of similar input data in the same modality are brought closer together, has begun to take place. In this study, we assume a multimodal environment and examine the possibility of bringing latent variable representations close to similar input data in various modalities.
Using Automatic and Semi-automatic Methods for Digitizing the Dictionary of Trinidad and Tobago English/Creole into a Graph Database

The Dictionary of Trinidad & Tobago English/Creole (DTTE/C) is the first scholarly dictionary to cover the lexicon of three of the languages of Trinidad & Tobago that are all regarded as low-resourced languages. There have been no successful attempts, prior, to efficiently digitize the dictionary for adoption and use in research communities within the broad field of Artificial Intelligence. As such, this paper presents the work done to produce an efficient DTTE/C digitisation framework using a series of automatic and semi-automatic methods. Through detailed modeling of the dictionary as a graph structure, the research uses graph database technology for the generation of a DTTE/C knowledge graph and lexical semantic layering by referencing upper level concepts in the SUMO ontology. Fauna datasets consisting of entries from Mollusc, Crustacean and Mammal categories were successfully modeled in the graph with F1 scores of 0.929, 0.886, and 0.987 respectively for headwords.
eGLU-Box Mobile: A Smartphone App for Usability Testing by Italian Public Administration Webmasters

Smartphones and tablets now offer consumers unique advantages such as portability and accessibility. Developers are also working with a mobile-first approach, and are prioritizing mobile applications over desktop versions. This study introduces eGLU-box Mobile, an application for performing a drive usability test directly from a smartphone. An experimental study was conducted in which the participants were divided into two groups: an experimental group, which used the new mobile application from a smartphone, and a control group, which used the desktop application from a computer. The participants’ behavior was assessed using explicit (self-report questionnaires) and implicit measures (eye movement data). The results were encouraging, and showed that both the mobile and desktop versions of eGLU-box enabled participants to test the usability with a similar level of UX, despite some minimal (although significant) differences in terms of satisfaction of use.
Co-Designing a Conversational Agent in Health and Social Care – Perspectives of Professional Care Staff and Older Adults

Working conditions in health and elderly care are increasingly characterized by work intensification, high physical and psychological demands, and a shortage of skilled workers [1]. The reasons for the high workload in healthcare are manifold. Among them are an increasing demand because of demographic developments or growing documentation efforts, fueled by the rising adoption of electronic health records [2, 3]. To address these challenges, technical solutions are seen as a promising way that can support care workers as well as patients. Voice-based human-technology interaction is an increasingly important field promising many advantages: supporting staff via documentation tasks, enabling care recipients to communicate their needs via voice commands. Against this background, the project presented here, funded by the German Ministry for Research and Education, follows a co-design process of a smart speaker with care workers and patients. The main aim of the project is to define use cases with the target groups and to disclose the potential users' assessments of the device within those. Therefore, the co-design process covers separate workshops with the two target groups, i.e., professional caregivers and potential patients.
Applying UX Design Process for a Web-Documentary Development: A Project Development

This paper aims to present the application of a User Experience (UX) design process in developing a web documentary based on promoting empathy among social groups, with the broader concern of contributing to the fight against prejudice and discrimination against immigrants in European countries. The Human-Centred Design methodology was used as the foundation for web-documentary development, comprising four main phases: discovering, defining, developing, and testing. This paper will explain the developing phase of this case study, and the final prototype will be presented. In the end, the results of this phase will be discussed, considering UX design. Usability tests were made, and the main results were applied to improve the solution. In this sense, this paper presents a case study of a web-documentary creation, from tools development and application to user testing.
Glasses Encourage Your Choices: A System that Supports Indecisive Choosers by Eye-Tracking

There is the problem of worrying when making a choice. To solve this problem, we propose a system that recommends products like a clerk in a store when in need. In this study, we focus on the fact that people tend to gaze at what they are interested in. Our system observes eye movement during selection and encourages selection by suggesting to a person who is having difficulty choosing that they select the product they have been looking at most. We developed a prototype system that implements the proposed method using a wearable eye-tracking system. We conducted two selection experiments, a selection from a menu (number of options: N = 20) and a selection from a catalog (N = 116), to test the system's usefulness. As a result, the selection from a menu reduced the time required for selection and resulted in high selector satisfaction. There was no such tendency in the case of selection from a catalog. Gaze movements during selection were more complex than in the selection from a menu, suggesting that the timing of recommendation may be necessary.
Enhancing Visual Encodings of Uncertainty Through Aesthetic Depictions in Line Graph Visualisations

The method of representing uncertainty can drastically influence a user's interpretation of the visualised data. Whilst reasons for the scarce adoption of accepting uncertainty visualisations has been extensively researched, exploring further intuitive depiction methods has taken a back seat. Currently, most visualisation methods for uncertainty revolve around the comprehension of grasping pre-existing techniques such as confidence intervals and error bars. Moreover, this anticipates that the intended audience will be proficient in obtaining the relevant information displayed. To help establish an accessible method for the visualisation of uncertainty, we adopt a novel cross-disciplinary approach to further understand and depict the more intuitive/affective dimensions of uncertainty. The field of aesthetics is mostly associated with the discipline of art and design, but it has been applied in this research to evaluate its effectiveness for uncertainty visualisation. In a recent study with one thousand one hundred and forty-two participants, the authors examined the influence of applying aesthetic dimensions to the visualisation of a line graph. We find that certain aesthetic renderings afford a higher degree of uncertainty and provide an intuitive approach to mapping uncertainty to the data. By analysing the participants' responses to different aesthetic renderings, we aim to build a picture of how we might encourage the use of uncertainty visualisation for a lay audience.
Evaluating User Experience in Information Visualization Systems: UXIV an Evaluation Questionnaire

Understanding how people interact with data and why users prefer one system over another is necessary to develop successful solutions for information visualization. Evaluating the users' experience with applications based on interaction with data is challenging due to the several parameters involved. It requires evaluating the experience offered by the system, affected data, and the analysis process supported. Existing measurement tools do not take all of these aspects into account. This study investigated the gaps in an existing user experience evaluation tool regarding the interaction with data. A thematic analysis identified the missing themes and grounded our definition of evaluation dimensions. A combination of literature review and designer collaboration resulted in the evaluation statements. Our contribution consists of a questionnaire to support evaluating specific aspects of experience and relevant dimensions for measuring the interaction with data in information visualization systems.
A Study of Junior High School Students' Willingness to Learn Table Tennis Using VR Technology

There has been an increasing amount of research into the use of virtual reality technology in the classroom since the outbreak of the epidemic in 2019. Technology is being combined with physical education primarily for the purpose of increasing students' interest in learning, promoting the rapid improvement of students' technical skills, and reducing the effect of venues and weather on physical education classes. We examined junior high school students' willingness to use VR technology for table tennis learning in this study, and data was collected from 144 junior high school students. According to the results of the study, emotional support is significantly related to satisfaction. Learning interest is significantly affected by emotional support and satisfaction. In addition to emotional support and satisfaction, learning interest has a significant impact on students’ willingness to use VR glasses to learn table tennis technology continually.
(I Can’t Get No) Satisfaction: On the Existence of Satisfaction as a Component of Usable Security and Privacy

In the ISO definitions of usability, user satisfaction is specified as an element and effectiveness and efficiency. Jakob Nielsen, who is well known for his work on usability in web and UI design, defines satisfaction as one of the five qualitative elements in usability. Whitten and Tygar’s paper, one of the earliest usability studies on usable security, also includes “sufficiently comfortable” as one of the usability definitions for security, which relates to user satisfaction. Although many usable security researches have been conducted and usability evaluations of the proposed methods have been done, most of them have mainly evaluated the effectiveness and efficiency of the proposed methods, and there is a possibility that satisfaction or comfort has not been sufficiently evaluated. Therefore, this paper investigates how satisfaction or comfort is evaluated in usable security research and discusses the results.