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USERS’ EXPERIENCES AND PERCEPTIONS ABOUT TELEPRESENCE ROBOTS IN EDUCATION
No full textTelepresence robots (TR) enable people to be represented by a mobile robot at a distant location and audio-visually interact with people and the environment around the robot. The user of the TR remotely controls and drives the TR in its environment as well as interacts with people using microphones, speakers, cameras, screens, and other facilities of the TR. TR have been exploited in various areas including education. However, most previous studies examined specific cases of introducing TR in education. The current study aims at synthesizing the experiences and perceptions of various TR users at different countries and various institutes. A qualitative research study was implemented with regard to the Erasmus+ project TRinE: Telepresence Robots in education. The team conducted 20 interviewees with experienced users (students, educators, technicians, etc.) in the integration of TR in education across Austria, France, Iceland, and U.S.A. The interviewer interrogated the interviewee employing 28 questions about the interviewee’s views, practices and experiences with TR in education. The results shown that the most common use of TR was that of a remote teacher or student participating in a class via a TR. The most frequently mentioned TR strength include the ability of the remote students to feel present, participate, communicate, and socialize with their classmates; TR weaknesses include their weak wireless connectivity, low sound and camera quality, lack of hands and gestures; TR challenges include obstacles in its movement (e.g., elevators, doors, stairs), privacy concerns, lack of WiFi everywhere, risks of misusing TR. The interviewees were not aware of any national or international policies about TR in education. Finally, they made recommendations in a number of issues.198709879EDULEARN22 Proceeding
Utilization of Socially Assistive Robot's Activity for Teaching Pontic Dialect
No full textSocially Assistive Robotics (SAR) aim at supporting their users, through social interaction, in carrying out various tasks. One of the areas in which SARs are widely used is teaching foreign/second languages, particularly to children. Socially Assistive Robots create incentives, shape appropriate attitudes, and foster suitable conditions to support learning through the social relationships developed with humans. This paper examines the extent to which a SAR could be utilized to teach the Pontic dialect to adults. For this purpose, four educational activities were designed with specific learning goals incorporated into the curriculum. A total of thirty adult students participated individually in this teaching intervention and then expressed their impressions and attitudes during personal semi-structured interviews. At the same time, the activities were recorded on video. The research data were analyzed based on qualitative research methods. The data analysis found that most participants viewed the endeavor favorably. Interaction with the SAR strengthened a positive learning atmosphere and stirred their interest. All participants made positive remarks on the fact that they had the ability to engage in language activities in an alternative, pleasant manner. However, some of them highlighted the absence of deeper and more substantial communication that is achieved between humans, a shortcoming that is the result of the currently unsolved design weaknesses of robots. Nevertheless, indications are positive and there is interest in further research on the use of SAR in teaching languages to adults.13303486505Human-Computer Interaction. Technological Innovatio
A metric for quantifying the ripple effects among requirements
No full textDuring software maintenance, it is often costlier to identify and understand the artifacts that need to be changed, rather than to actually apply the change. In addition to identifying the artifacts related to the change per se, one needs also to identify the artifacts that are changed due to ripple effects. In this paper, we focus on ripple effects and propose a metric for assessing the probability of one requirement to be affected by a change in another requirement (i.e., requirements ripple effect). We focus on the requirements level, since most maintenance tickets (which stem from the customer) are captured in natural language and therefore are more naturally mapped to requirements, rather than source code. The proposed metric—the requirements ripple effect measure (R2EM)—is calculated by considering the conceptual overlap between the involved requirements (through their past co-change), the parts of the code in which they are implemented (i.e., their overlapping implementations), and the underlying dependencies of the source code (i.e., ripple effects between classes). We note that despite the involvement of source code artifacts in the calculation of R2EM, this metric is considered as a requirements’ level one, since the unit of analysis is pairs of software requirements. To validate the proposed metric, we conducted an industrial case study, on two enterprise applications of an SME. The study design involved both quantitative and qualitative data, and input was given by 9 practitioners. The results suggested that R2EM is able to identify ripple effects between requirements at a satisfactory level, and those effects are mostly caused by overlapping implementations and source code ripple effects of these implementations
Adapting Open Innovation Practices for the Creation of a Traceability System in a Meat-Producing Industry in Northwest Greece
No full textTraceability is becoming an essential tool for both the industry and consumers to confirm the characteristics of food products, leading industries to implement traceability to their merchandise. In order for the Computer Technology Institute and Press "Diophantus" (CTI) to help small and medium-sized enterprises (SMEs) implement traceability systems based on open innovation, principles were introduced. This paper presents market research that was carried out in order to determine the significant concerns of the Greek consumers about pork meat and pork products, their opinion on traceability information, and their preferences regarding how they would like to receive this information. The survey was conducted online and took place from mid-February to mid-March 2021 on a sample of 224 participants. The market research showed a very high interest concerning traceability, especially on the expiry date of the meat (87.9%), while the way and conditions of transport of the meat products follow (79%). Furthermore, consumers showed that they believe that the quality and safety of pork products would be improved with traceability (70.1%) and (79%) would prefer to buy traceable compared with untraceable pork, signifying the importance of traceability for consumers. Additionally, it was found that consumers and SMEs have common concerns regarding traceability. The information gathered from this market research will be used to adapt the traceability system to consumers’ needs.149511
AI-enabled digital forgery analysis and crucial interactions monitoring in smart communities
No full textDigital forgery has become one of the attractive research fields in today’s technology. There are several types of forgery in digital media transmission, especially digital image transmission. A common type of forgery is copy-move forgery (CMF). The CMF may be encountered in streets, railway stations, underground stations, or festivals. This type of forgery may lead to hugger-mugger in some cases. Therefore, there is a need to find a sufficient countermeasure mechanism to detect image forgeries. This paper presents a new CMFD approach that depends on deep learning for IoT based smart cities. Two well-known deep learning models, namely CNN and ConvLSTM, are adopted for CMFD. The proposed models are tested on MICC-220, MICC-600 and MICC 2000 datasets for validation. Several tests are performed to verify the effectiveness of the proposed models. The simulation results reveal that the testing accuracy reaches 95%, 73%, and 94% for MICC-F220, MICC-F600 and MICC-F2000 datasets. In addition, the proposed approach achieves an accuracy of 85% for a combined set of all datasets.17712155
Augmented Reality and Virtual Reality in Education: Public Perspectives, Sentiments, Attitudes, and Discourses
No full textThis study aims to understand the public’s perspectives, sentiments, attitudes, and discourses regarding the adoption, integration, and use of augmented reality and virtual reality in education and in general by analyzing social media data. Due to its nature, Twitter was the selected platform. Over 17 million tweets were retrieved from January 2010 to December 2020 and four datasets were created. Two of them referred to the general use of these technologies and two to their educational use. The data was analyzed using text mining, sentiment analysis (e.g., polarity and emotion detection), and topic modeling methods. TextBlob, Word-Emotion Association Lexicon (EmoLex), Valence Aware Dictionary for Sentiment Reasoning (VADER), and Latent Dirichlet Allocation (LDA) were some of the tools used. Based on the results, the majority of the public were positively disposed toward the general and the educational use of both augmented reality and virtual reality and mostly expressed positive emotions (e.g., anticipation, trust, and joy) when referring to them. In total, 11 topics emerged that were related to education, new technologies, digital and social media use, marketing and advertising, the industrial domain, the health domain, gaming, fitness and exercising, devices, the travel and tourism domain, and software development kits. The educational benefits of augmented reality and virtual reality, their ability to enrich both teaching and learning activities, and their role as effective educational means were evident.121179
Bond markets integration in the EU: New empirical evidence from the Eastern non-euro member-states
No full textThe financial integration among the member-states in the long run inside the union constitutes an important task of the EU officials and policy makers. The sovereign-debt crisis of the Eurozone decelerated its economic integration and subsequently increased the unwillingness of the non-euro member-states to join the monetary union. In the light of this background, the research aim of this manuscript is to examine the bond markets integration among the EU CEE non-euro countries and the EA Big-5 economies. The empirical evidence supports that the Eastern member-states’ bond markets integration is heterogeneous and disparate. Lastly, the directional volatility spillovers, unveil that the volatility effects on the EU CEE non-euro bond markets are diversified revealing the leading role of EA core bond markets.6310182
Delineating Transformative Value Creation through Service Communications: An Integrative Framework
No full textPurpose. Transformative value is a central tenet of transformative service research (TSR) because it affects individual and community well-being, quality of life, and sustainability. Although transformative value plays a significant role in well-being, the literature suffers from a lack of sound interdisciplinary conceptual frameworks that delineate how transformative value is created in services throughout the service consumption process. Therefore, the purpose of this paper is to examine the nature and role of service communications during the various stages of the service consumption process to enable the creation of transformative value for people and the environment. Design/methodology/approach. To achieve the above goal, we integrate agenda-setting theory (media theory) combined with framing and relational dialectics (communication theories) as well as Transformative Service Research (TSR). Findings. In line with the objectives of the study, we propose an integrative framework named Transformative Value Creation via Service Communications (TVCSC) that explains how firms set their transformative corporate agendas through their dialectics with consumers, society, and media. This transformative agenda is reflected in the marketing mix of their services (7Ps) as communicated with various means, physically and digitally (sales/frontline personnel, advertising, CSR, social media, website). Recommendations for a transformative marketing mix are provided. Furthermore, TVCSC illustrates how value is co-created in all customer-firm interactions via relationship dialectics throughout the service consumption process to result in transformative value outcomes. Originality. This is the first comprehensive framework that explains how transformative value is created through the various communications in services and is the outcome of value co-creation interactions of the service consumption process. Research Implications. The proposed framework identifies several research gaps and provides useful future research directions.334-553155
Exploring the Quality of Dynamic Open Government Data Using Statistical and Machine Learning Methods
No full textDynamic data (including environmental, traffic, and sensor data) were recently recognized as an important part of Open Government Data (OGD). Although these data are of vital importance in the development of data intelligence applications, such as business applications that exploit traffic data to predict traffic demand, they are prone to data quality errors produced by, e.g., failures of sensors and network faults. This paper explores the quality of Dynamic Open Government Data. To that end, a single case is studied using traffic data from the official Greek OGD portal. The portal uses an Application Programming Interface (API), which is essential for effective dynamic data dissemination. Our research approach includes assessing data quality using statistical and machine learning methods to detect missing values and anomalies. Traffic flow-speed correlation analysis, seasonal-trend decomposition, and unsupervised isolation Forest (iForest) are used to detect anomalies. iForest anomalies are classified as sensor faults and unusual traffic conditions. The iForest algorithm is also trained on additional features, and the model is explained using explainable artificial intelligence. There are 20.16% missing traffic observations, and 50% of the sensors have 15.5% to 33.43% missing values. The average percent of anomalies per sensor is 71.1%, with only a few sensors having less than 10% anomalies. Seasonal-trend decomposition detected 12.6% anomalies in the data of these sensors, and iForest 11.6%, with very few overlaps. To the authors’ knowledge, this is the first time a study has explored the quality of dynamic OGD.2224968
Extending the zero-sum gains data envelopment analysis model
No full textIn this paper, we adapt the ZSG-DEA model to the case of a reverse output, whose larger (smaller) values reflect lower (higher) achievements. Then, we introduce the zero-sum reverse output redistribution strategies, state the resulting Target’s Assessment Theorem for both the proportional and the equal expansion strategy, and confirm that the Benchmarks’ Contribution Equality Theorem is also applicable to these cases. We also apply the ZSG-DEA model with a forward and a reverse output to estimate respectively teams’ offensive and defensive efficiency in Greek premier soccer league.582-317118