Virtual reality (VR) has grown in popularity in industry and science. While the development of virtual reality applications is progressing at a fast pace, even today it is a challenge to precisely define the aspects that make virtual reality software of high quality, user-friendly and usable. The biggest issue is that traditional software testing standards can only be partly followed. Using virtual reality for scientific purposes can provide researchers with new possibilities and change human-computer interaction. In this paper, we conducted a user study and identified a number of aspects that are the basic factors in determining the usability of virtual reality software. The results indicate that excessive head and arm movements have an impact on the VR experience.
The situation surrounding the dairy industry is constantly changing with the elimination of tariffs on overseas dairy products due to the issuance of the EU-Japan EPA. To increase international competitiveness and food self-sufficiency, adding more value to dairy products is necessary. However, there are many problems in the breeding and management methods of dairy farming in Japan, such as increased production costs, reproductive performance, and health management of dairy cows. Grazing has been attracting attention to solve these problems. However, grazing requires pasture management for the foraging conditions of the cows. Therefore, we aim to reduce the burden of grazing and promote grazing by classifying the behavior of a cow by machine learning using data from an accelerometer worn by a cow.
The aim of this systematic review is to examine the role of envy in the relation between Social Networking Sites (SNSs) use and depression. The full text screening identified 9 studies that fell within the inclusion criteria of the current review. Overall, results showed a positive association between SNSs use and depression levels, that was mediated by envy and moderated by several factors such as self-efficacy or friendship type. In the only two studies suitable to infer directionality of the association between the variables considered, depression proved to be a predictor rather than an outcome of SNSs use and envy. To improve the sustainability of SNS platforms, ICT practitioners should address design features that induce social comparison and envy, as these phenomena influence not only well-being but also behaviors relevant to SNSs use (e.g., discontinuance intentions, switching SNSs).
The term long-term memory color is used to describe those colors that are recalled in association with familiar objects, meaning objects with which we have a frequent visual experience. To understand this phenomenon in more detail, this study investigates whether nationality, image cue, and the hours of playing virtual reality games has an effect on it. Thus, memory colors for seven everyday objects were investigated: Caucasian skin, orange, banana, sky, leaf, grass, and river. In the course of the test 3 tasks were needed to be solved: coloring with the entire palette, coloring with a narrowed-down palette while the image cue is present, and coloring with a narrowed-down palette while the image cue is absent. The test was completed by 54 university students. Statistical analysis showed that our nationality does influence certain memory colors. If more than an average of 20 hours were spent playing virtual reality games per week, it resulted in darker memory colors, but not for every investigated object. The presence or absence of an image cue does indeed have an impact on the choice of color. 70.9% of observers chose a different color when the object in question was not present.
We aim at exploring the geometrical information that can be extracted from dynamic two-dimensional audiovisual records created by magnetic resonance imaging (MRI) and ultrasound (US) techniques during human speech. We connect US and MRI data by machine learning using tongue contours fitted automatically to the MRI and US images. We create different system configurations depending on the type and number of the input and output parameters of the network and the number of the hidden layers and neurons. We perform qualitative and quantitative analyses for all settings. The main benefit of this approach is to better understand the role of the geometric parameters of the vocal tract in speech production and to create a possible way to harmonize MRI and US sources.
This paper introduces an electroencephalogram (EEG) to the sound transformation tool written in Python and Pure Data using Faust. The proposed signal chain performs a real-time sonification representing the distance of the level from the threshold. We present four different music games implemented in Pure Data using our custom object Scale it in a neurofeedback application. These games were tested and evaluated by users. The subjective impression of the participants (N=53) of gaining control of the game after the session is overall 3.59 on a five-level Likert scale.
The issue of personalized medicine (patient-tailored therapy) is becoming increasingly popular, but a significant increase in research and publications on this topic has been observed in the last 20 years. This article aims to present the preliminary results of our own research on exoskeletons for the upper limb: for the hand and for the elbow. The solution named elbow exoskeleton presented in the paper implements the concept of personalized therapy. The combination of 3D scanning technology and 3D printing in the form of reverse engineering gives the possibility of relatively inexpensive creation (with adaptation to a specific user) of a digital design of an exoskeleton with a complex internal and external structure. The novelty of the presented solution lies in the simultaneous use of 3D scanning, 3D printing, human-machine interface and artificial-intelligent optimization in personalized medicine. This comprehensive approach contrasts the state of the art with the novelty of our research. Described exoskeleton constitutes a step toward the future of telemedicine, especially telerehabilitation and telecare within eHealth paradigm.
In our paper we introduce a bilingual language learning material based on the three dimensional virtual library model (3DVLM). This is an inherent part of the virtual library project started in 2013 in the framework of the Cognitive Infocommunications (CogInfoCom) research. The current version of the 3DVLM uses the 3D features and the hypertext-based presentation capabilities of the MaxWhere Seminar System. The latter is especially important because our material is based on web technology and organized so that it is going to be a scale-free network of interconnected nodes. First, we would like to provide a short overview on the virtual library in general, then introduce the organization and structure of the bilingual language learning material we have developed to support English language learning for Hungarian learners at an advanced level. The learning material is based on selected passages from classical literary works, presented both in English and in Hungarian, which we think may improve both English language skills and cultural awareness of language learners through the background knowledge they acquire. In order to check and test the bilingual language learning material we used the Google Translate service which proved to be a very efficient tool for both improving the learning material and deepening the language learning process.
The aim of this article is to present a systematic review of the impact of mobile health applications use in work-related stress management among adult workers. After an accurate assessment of articles potentially relevant to the search topic, the full-text screening identified 11 articles that match the review's eligibility criteria. Encouraging positive effects were found in most articles, with interventions based on mindfulness meditation predominating. However, a fruitful area for ICT was also highlighted to review what factors (type of technology, user experience, training time) may contribute to improve the effectiveness of mobile apps proposed for work-related stress reduction.
A prerequisite for the successful implementation of content management in digital reality environments is the optimization of the information-location-time triad. Projects in 3D digital spaces (whether created for business applications, educational or other purposes) typically focus on management, sharing, and even collaborative editing of a variety of digital content types. This paper introduces the concept of timestamp-based digital content synchronization in 3D VR/AR/MR digital spaces. Our goal is to propose a practical “workflow-based” time-stamping service relying on a weblink-based database and associated AI-based solutions. The goal is to synchronize digital content according to location, time, and work process-related characteristics, and to ensure the retrievability of the time-synchronized information set.
Nowadays, traffic congestion and air pollution in urban areas become huge challenges to transportation engineering. On the other hand, technologies have evolved, and simulation and artificial intelligence have become important tools to face these challenges. In this paper, a review of this research field is done, and a possible combination of simulation and machine learning to mitigate traffic emissions is proposed. The long-term goal of the research is to establish an effective emission mitigation model for some specific crossings.
Recent years have meant that teachers have learned to use tools, methods and educational aids which were not used before the pandemic. The development of didactic skills was mainly due to the need to teach over the Internet, and consequently to use specific environments, applications, tools and methods for teaching, motivating students and evaluating their achievement. The purpose of this article is to examine how teachers' jobs have changed, and what they have learned over the two years of the pandemic. It is also important to forecast what they can transfer to full-time teaching and compare it to the teachers declarations. In the paper, we present conclusions of a survey conducted at a Polish university.
Privacy awareness is an important issue in the educating new generations. The increasing use of online services in societies makes this area more relevant than before. It is the task of educational institutions to prepare their students for a safe online life. At our universities, we have decided to focus on this area. Before planning the necessary curriculum, we conducted a survey among university students to find out which areas of this field require more attention in privacy awareness education. In this paper, we present the results of this survey. Multiple-choice questions were used in the questionnaire, where students had to choose between good, most often chosen wrong, and random wrong answers. We found that in many cases the students chose the well-known wrong answers, which means that we have to deal not only with useful information but also with misconceptions in the course material. Based on these results, we designed a VR environment using the results of this survey. This VR environment includes a curriculum on privacy awareness that deal with those fields that students need to study. This environment is designed for self-paced learning as a supplement to university education and developed in a MaxWhere space.
Within recent years, it has become popular to use physiological and expression data to ameliorate inter-cognitive communication between human and machine. One emotion that is highly relevant for this is frustration, which occurs when a user's goal in using a system is failed to be met. This paper presents a latent variable model that estimates frustration in two different driving contexts by continuous subjective frustration rating, facial expressions and frontal alpha asymmetry in the electroencephalogram. We then compare this full model to models with less measurement variables to evaluate which measurements can be left out. Our results show that expression frequency and subjective frustration make important contributions to the model of experienced frustration. This paper presents a proof of concept for using a latent variable model to evaluate collected measures to estimate an experienced emotion. This method can inform researchers which measurements are most informative in different circumstances. Additionally, the method can be used to evaluate how well purely objective measurements (that are the only feasible measurements in most applied settings) perform in comparison to a model including subjective ratings.
The quality of the infocommunication plays a key role and influences the smoothness of the output resulted by the Human-Computer Interaction. To maximise the quality of the Human-Computer Interaction, high levels of synergy are needed between both actors. To achieve the required level and quality of infocommunication, there is a need for a better understanding of the underlying processes. These processes might not be limited to Human and Computer only but might show some similarity with other carbon-based Agents. Inspired by different fields of biology, the aim of this research is to show how the connection and communication between entities create a synergy that supports them bilaterally. This provides the opportunity to translate a similar result into the Human-Computer Interaction in order to improve the outcome of the infocommunication.
This article aims to present a systematic review of the impact of Virtual Reality on Social Anxiety Disorder (SAD) in adults. In recent years, the progressively fast development of new technologies is also affecting the field of psychotherapy. Indeed, there is a widespread use of online digitalized mental health services such as computer-mediated psychotherapy. In the cure of Social Anxiety Disorder, cognitive behavioral therapy uses in vivo exposure therapy, a particularly appropriate technique for implementation in Virtual Reality. Recent studies have examined the efficacy of virtual reality exposure therapy in the treatment of Social Anxiety Disorder. Therefore, the aim of our systematic review is to summarize the information from randomized controlled trials on the use of Virtual Reality Exposure Therapy in the treatment of Social Anxiety Disorder. After a careful review, 5 studies met the criteria for inclusion in the review. The results showed significant efficacy of both virtual reality exposure therapy and in vivo exposure therapy. However, virtual reality exposure therapy was found to be more beneficial in terms of cost, time, confidentiality, and practitioner burden, implying interesting CogInfoCom implications.
This paper introduces open-source sonification software that represents a real-time stream of time-series data as notes on a musical scale. The software comprises a data processing unit and a signal-to-sound conversion unit. Before being expressed as a note on a musical scale of predefined length and character, each chunk of the incoming data stream is transformed into a parameter representing its relative position in the original population.
People are known to judge artificial intelligence using a utilitarian moral philosophy and humans using a moral philosophy emphasizing perceived intentions. But why do people judge humans and machines differently? Psychology suggests that people may have different mind perception models of humans and machines, and thus, will treat human-like robots more similarly to the way they treat humans. Here we present a randomized experiment where we manipulated people's perception of machine agency (e.g., ability to plan, act) and experience (e.g., ability to feel) to explore whether people judge machines that are perceived to be more similar to humans along these two dimensions more similarly to the way they judge humans. We find that people's judgments of machines become more similar to that of humans when they perceive machines as having more agency but not more experience. Our findings indicate that people's use of different moral philosophies to judge humans and machines can be explained by a progression of mind perception models where the perception of agency plays a prominent role. These findings add to the body of evidence suggesting that people's judgment of machines becomes more similar to that of humans motivating further work on dimensions modulating people's judgment of human and machine actions.
The HEXACO model consists of six dimensions of personality: Honesty-Humility (H), Emotionality (E), eXtraversion (X), Agreeableness (A), Conscientiousness (C) and Openness to experience (O). Several studies in literature have shown that observer ratings of personality traits were strong predictors of job performance and academic performance. In this study we evaluated the personality traits of adolescents using the HEXACO-Middle School Inventory (MSI) and the Observer form of it. The aim was establishing if the observer HEXACO-MSI personality traits predict academic performance beyond the same self-report traits. Participants were 1089 children and 1089 Observers. The results showed that ratings by observer add something more to the self-report evaluations. The observer HEXACO-MSI personality traits predict scholastic performance beyond the same self-report traits. Parents or caregivers provide an evaluation that can complement the one provided by the adolescents themselves.
In this paper a new, easy-to-use algorithm is presented to support telerehabilitation of people with movement disabilities. This algorithm can adapt to the needs of the patients as it combines the cognitive property of intelligent decision-making systems with the human-computer interaction-based movement therapy. This algorithm is built upon the earlier work of the authors and it uses six various mean techniques to classify gesture descriptors. The preliminary results and a plan of evaluating the algorithm are presented in this paper.
