Reviewerly/exHarmony huggingface dataset:
Design and Implementation of Intelligent Treadmill with Fitness Tracker Using Raspberry Pi and IOT

Treadmill users mostly prefer automated treadmills having better construction and various speed levels over a manual treadmill. But using a treadmill with clickable buttons or screen sometimes becomes a dangerous task for newbies and people in their old ages. They find it difficult to reach the controller board and change the commands as per their need, having achieved a considerable fast speed, which results in injuries due to slip off from the mill. To avoid these situations, the proposed system changes the touch-operated controller to voice-operated one, to reduce the accident rates and provide a great user experience. Deep neural network handles sound input, Mel-spectrogram is used to achieve higher efficiency results which is the base of the audio processing technique in python that uses automatic speech recognition (ASR). The proposed system focuses on easing the treadmill speed control using ASR and also has features like checking the weight of a person standing on the mill, calculating his BMI, and time of run which is then stored on cloud platform ThingSpeak, for analysis of workout and a built-in music player which solely operates on speech recognition principle using Google APIs.
A Blockchain-based privacy preserving mechanism for mobile crowdsensing

In blockchain-based mobile crowdsensing, reporting of real-time data is stored on a public blockchain in which the address of every user/node is public. Now, the problem lies in the fact that if their addresses get shown to adversaries, all their transactions history is also going to be revealed. Therefore, crowdsensing demands a little privacy preservation strategy in which the identity of a user is unable to be revealed to an adversary or we can say that crowd sensors while reporting the real-time data must provide some level of anonymity to crowdsensing users/nodes [1]. The current crowdsensing architecture is not secure because of its centralized nature and the reason is a single point of failure also numerous kinds of attacks are possible by adversaries such as linkage attacks, Sybil attacks, and DDOS attacks to get the identity or any other valuable information about the nodes. The location of crowd sensors is also a threat that could lead to adversarial attacks. Consequently, some blockchain-based models must be proposed to attain privacy on the blockchain ledger. The solution can either be made up crowdsensing environment on a private blockchain or smart contracts may be the answer to this problem by which we can make the users secure from several attacks conducted by adversaries on the blockchain.
MEASURING THE EDUCATIONAL WORK PERFORMANCE ON THE FORMATION OF EMOTIONAL WELL-BEING OF PRIMARY SCHOOL CHILDREN

Ensuring the emotional well-being of children is an urgent task in working with children of any age, and especially with children of primary school age. Primary school children are faced with the need to adapt to a new life associated with a change in the daily routine, long stay at school, completion of educational tasks, new requirements for them as students, and other factors. The educational program plays an important role in the adaptation of primary school children; therefore, the evaluation of the effectiveness of this program is an urgent task.The aim of the study is to evaluate the effectiveness of the program of education of primary school children based on monitoring their emotional well-being and statistical analysis of factors (class and gender) associated with the assessment of emotional well-being.Measuring the emotional well-being of primary school children is carried out within the framework of the theory of latent variables. The dialog system "RUMM2020" was used to process the survey results. The obtained assessments of the emotional well-being of primary school children were structured according to three factors: the year of the surveys (2019 and 2020), grade (3A, 3B), and gender. Since the studied factors are qualitative, a three-factor analysis of variance was used to assess the influence of all three factors. Within the framework of the theory of latent variables, the emotional well-being of primary school children is measured on a linear scale. The construct validity of the questionnaire used is shown; the Cronbach's alpha coefficient is 0,822. This means that primary school children are well differentiated by their emotional well-being. The conducted three-factor analysis of variance showed that, on average, the assessment of the emotional well-being of primary school children in 2020 is statistically significantly higher than in 2019 for all grades. The emotional well-being of primary school children does not depend on their grade and gender. Thus, the monitoring results showed the educational work performance.Conclusion. Within the framework of the theory of latent variables, the emotional well-being of primary school children is measured on a linear scale. As a result of the monitoring, the effectiveness of the educational work performance is shown - the emotional well-being in 2020 is statistically significantly higher than in 2019..
THE PANDEMIC LOCKDOWN AS A PUSH FACTOR FOR USING DIGITAL TECHNOLOGY AS ARENA FOR WORK INTEGRATED LEARNING: A STUDY OF AN INNOVATION PROJECT IN MUNICIPAL HEALTHCARE SERVICES

Information about the paper titled "THE PANDEMIC LOCKDOWN AS A PUSH FACTOR FOR USING DIGITAL TECHNOLOGY AS ARENA FOR WORK INTEGRATED LEARNING: A STUDY OF AN INNOVATION PROJECT IN MUNICIPAL HEALTHCARE SERVICES" at IATED Digital Library
SOFTWARE SYSTEM FOR CARDIOLOGICAL DATA ANALYSIS ORIENTED TO THE TRAINING OF MEDICAL STUDENTS

G. Georgieva-Tsaneva , E. Gospodinova Institute of Robotics, Bulgarian Academy of Sciences (BULGARIA)
GAMIFICATION IN LEARNING AS A MEANS OF STUDENTS ADAPTATION TO INTERCULTURAL COMMUNICATION

T. Bukina 1, E. Novgorodova 1, L. Malakhova 2, L. Nurova 3 1Kazan Federal University (RUSSIAN FEDERATION) 2Kazan State Institute of Culture (RUSSIAN FEDERATION) 3Kazan Branch of the Russian State University of Justice (RUSSIAN FEDERATION)
ON THE SIGNIFICANCE OF AUGMENTED REALITY IN SECONDARY-LEVEL MATHEMATICS EDUCATION – A DISCUSSION OF MATHEMATICS DIDACTICS WITH REFERENCES TO KEY TEACHING-RELATED ASPECTS

Information about the paper titled "ON THE SIGNIFICANCE OF AUGMENTED REALITY IN SECONDARY-LEVEL MATHEMATICS EDUCATION – A DISCUSSION OF MATHEMATICS DIDACTICS WITH REFERENCES TO KEY TEACHING-RELATED ASPECTS" at IATED Digital Library
THE BLOG OF NATIVE FLORA GARDEN AT THE UNIVERSITY OF JAÉN AS A DIDACTIC RESOURCE

F. Aguilera Padilla 1, C. Salazar Mendías1, L. Ruiz Valenzuela1, A.M. Abril Gallego1, G. Parra Anguita1, M. Romero-Ariza1, M.L. Lendínez Barriga1, G. Siles Colmenero2 1University of Jaén (SPAIN) 2CE2A El Acebuche (SPAIN)
Decidability and complexity of action-based temporal planning over dense time

In this paper, we study the computational complexity of action-based temporal planning interpreted over dense time. When time is assumed to be discrete, the problem is known to be EXPSPACE-complete. However, the official PDDL 2.1 semantics and many implementations interpret time as a dense domain. This work provides several results about the complexity of the problem, focusing on some particularly interesting cases: whether a minimum amount ε of separation between mutually exclusive events is given, in contrast to the separation being simply required to be non-zero, and whether or not actions are allowed to overlap already running instances of themselves. We prove the problem to be PSPACE-complete when self-overlap is forbidden, whereas, when it is allowed, it becomes EXPSPACE-complete with ε-separation and even undecidable with non-zero separation. These results clarify the computational consequences of different choices in the definition at the core of the PDDL 2.1 semantics, which have been vague until now.1
Intelligent Interpretation of Folk Customs in Tibetan Folk Proverbs Based on Text Retrieval Algorithms in the Context of Big Data

In the context of big data, this article uses a text retrieval algorithm to intelligently interpret the folklore in Tibetan folk proverbs. The text retrieval algorithm based on deep learning performs grammatical recognition and extraction of Tibetan language, classifies and analyzes the characteristics of Tibetan proverbs, and discovers Tibetan proverbs In addition to the universal language and content characteristics of proverbs, special attention is paid to the expression of Tibetan folk philosophy, and many dialectical philosophical viewpoints such as objective laws, causality, mutual change of quality, the division of things into two, and the essence of phenomena have been formed ane unique world of proverbs. The simulation has proven the satisfactory performance of the designed model.
FORMATION OF COMPETENCIES OF WORKING WITH CHILDREN AT RISK AT THE PEDAGOGICAL UNIVERSITY STUDENTS

I. Balandina , T. Moskvitina , L. Yuzdova , E. Nikitina , G. Shiganova , A. Milyutina South Ural State Humanitarian Pedagogical University (RUSSIAN FEDERATION)
TECHNICAL EDUCATION IN SLOVAKIA DURING THE COVID-19 PANDEMIC

The world is facing a pandemic caused by the viral disease Covid-19. The introduction of movement restrictions has impacted education. Education which is traditionally slow to change was forced to adopt a different approach to teaching which resulted in fast modernization and implementation of advanced information and communication technologies. The research presented here is carried out by the Department of Technology and Information Technologies at the University of Constantine the Philosopher in Nitra, Slovakia. It examines the forms and methods of distance learning implemented at primary and secondary schools in Slovakia. Data was collected through questionnaires administered to participants at both levels of education in schools across the country. All respondents were active participants in the distance learning processes. The collected data was divided into three groups according to the respondents from International Standard Classification of Education ISCED 2, ISCED 3 and ISCED 3C. It was then processed using appropriate methods of statistical analysis.
5 The Action-oriented Approach in the CEFR and the CEFR Companion Volume: A Change of Paradigm(s)? A Case Study from Spain

5 The Action-oriented Approach in the CEFR and the CEFR Companion Volume: A Change of Paradigm(s)? A Case Study from Spain was published in Reflecting on the Common European Framework of Reference for Languages and its Companion Volume on page 64.
Reversible Secured Data Hiding using Binary Encryption and Digital Bit Modification Scheme

The information is getting precious day by day because of the digital revolution and more reach exposure of citizens to technology. The security of information is in demand and the topmost priority among researchers to develop data security systems. Image steganography is one of the data hiding schemes which is invisible in nature, although it uses visible image media to hide information. Steganography is not only limited to images. There are other media like text, audio, or video that can be utilized for hiding information. In this research work, a novel data hiding is being developed using an image as cover media. Researchers are facing during the development of the technique is maintaining the payload capacity as well as higher PSNR values and other parameters. This work uses colour images as cover and digital bit modification methods to hide secure information. Only hiding is not enough to secure information. There is an additional layer of security added by encrypting a secure message using an encryption method. The digital bit modification method is unconventionally spread the sequential bitstream over channels. This would make this approach unique and better as it is keeping the PSNR level higher along with NCC and lower MSE. All this is done by keeping the payload capacity as the maximum available. The average value of PSNR is 60.295dB, NCC is 1.00, and MSE is 0.1567.
CMCD at work with real-time, real-world data

This study examines some of the first production data obtained from deploying Common Media Client Data (CMCD) into production environments within a global content delivery network (CDN) and a global content distributor. It covers player integrations into Shaka, hls.js and dash.js, details of CDN support, handling of CMCD in a multi-CDN environment by a content distributor and the analysis and interpretation of the returned data.
Lived Experiences of Parents in the Implementation of Learning Distance Modality

The sudden widespread of the COVID-19 pandemic alarms and threatens the education system. This has become one of the biggest challenges most parents are dealing with. The study aimed to evaluate the lived experiences of Grade Four Quartz parents of Libertad Central Elementary School, School Year 2020-2021 in the implementation of Learning Distance Modality and come up with a Psychosocial Support Program Intervention that could help them, as teacher - partners in the delivery of education through the Learning Distance Modality successfully. A pure qualitative design of research was employed. A set of five questions were asked to gather data as basis for intervention with the parents. The result of the data show that as teacher-partners in the delivery of education in Learning Distance Modality, they lay the following facilitating factors: they spend more time with their child; they bond, enjoy, and have fun with the child; they know the learning capability of the children; and they also learn since they study the lessons first before teaching their children. The hindering factors that come out which serve as challenge to them are: the attitudes and behaviors of the pupils, some topics are not known to parents and difficult for them to explain to their child, some Mathematical problems and equations are confusing because some parents are undergraduates, the time constraints for working parents, and lack of learning resources. With these, parents have adapted measures to cope up the new normal learning delivery through the use of technology.
Rule-following robots? Transitional legal disruption through regulatee design and engineering

Artificial Intelligence (AI) and Extended Reality (XR) technologies present regulators with powerful tools to manipulate human behaviour, but more perniciously, human desire and indeed human being. This is because AI applications can interfere with our internal decision-making processes, and XR applications can affect our sensations by creating and mediating our experiences of the external world. When these technologically driven affordances are strained through contemporary cognitive science research to ground the notion that perceptions are processes for prediction error minimisation, such interferences can amount to designing and engineering the regulatee herself. Effectively, regulation no longer needs to be signalled in a normative regulatory environment, nor must it hardcoded into the architecture or technologically managed. Instead, AI and XR make it possible to design and create regulatees that embody the desired regulatory outcome. Paradoxically, however, such regulatory incorporation looks very much like the exercise of the agency of an agent and therefore is not recognised as a problem by contemporary legal principles and processes which seek to push back against obviously external influences or pressures. As a result, it is immensely difficult to articulate the legal or regulatory challenges posed by these developments, and to identify the harms through these doctrinal lenses.
AUGMENTED REALITY TECHNOLOGY AS A STRATEGY TO PROMOTE ASTRONOMY LEARNING ON MIDDLE SCHOOL STUDENTS

Due to the high degree of abstraction and the need to think in three-dimensional models, a significant part of the basic concepts of Astronomy are, most of the time, difficult to understand, involving the spatial reconstruction of representations, often taught in a two-dimensional approach. This difficulty in the three-dimensional visualization of the celestial bodies and their phenomena (seasons, moon phases, eclipses, among others), as well as the difficulty in perceiving the dimensions/proportions of the celestial bodies and distances in space, does not allow students to "achieve" hard-to-reach places, as well as to easily visualize these abstract concepts.Because it is a subject with a high level of abstraction, the use of different digital technologies, integrated in a pedagogical strategy, can be an important alternative in the teaching-learning process, allowing the student to be introduced to a diversity of relevant concepts in a natural way.Among several technologies, Augmented Reality (AR) appears as an emergent technology that bridges the gap between the virtual and the real world, both spatially and cognitively. This has been used by many teachers in school contexts, as it allows the creation of active and interactive learning environments, where the student interacts directly with three-dimensional objects in the real world, as well as promoting motivation in the teaching-learning process. Effectively AR allows students to move around the three-dimensional virtual image and examine it from any point of view, just like a real object, increasing their spatial visualization capacity and consequently the understanding of real-world phenomena. This augmented learning environment significantly improves the learning of astronomy concepts and contributes to an awareness of misconceptions in order to build scientifically correct mental models.The main objective of this article is to understand and discuss the problems and challenges of the inclusion of AR in a real educational context, as a strategy to promote active learning of Astronomy in middle school students, capable of overcoming the pedagogical challenges identified. Furthermore, it’s a clarification of key concepts for the implementation of AR technology in Astronomy teaching, considering that AR learning material is an effective tool in teaching Astronomy topics that include complex spatial relationships.
The Diatextual Construction of the Self in Short Message Systems

This chapter extends the use of the personal position repertoire beyond the psychotherapy domain, adopting it as a research method applied to the psychology of communication. The aim is to investigate the features of short message system (SMS) communication in a sample of late adolescents. Mobile phones are gradually becoming one of the most important new media. From a pragmatic point of view, mobile phones reshape the features of interaction, as SMS communication allows a more private and discrete reading and a more reflexive reply. SMSs are short texts that contain only 160 characters. The chapter focuses on a research which aims at showing the discursive modalities through which the dialogical self emerges from the communicative interactions developed in SMS messages. The dialogical construction of the self in SMS communication seems to push the enunciators to think about themselves through the interlocutor they are sending the message to.
EDUCATIONAL RIGHTS OF RUSSIAN SCHOOLCHILDREN AND STUDENTS DURING THE PANDEMIC

P. Ambarova Ural Federal University named after the first President of Russia B.N. Yeltsin (RUSSIAN FEDERATION)
The Effect of COVID-19 Depression, Self-Efficacy on Academic Achievement of Nursing Students Experienced Non-face-to-face class

본 연구는 비대면 수업을 경험한 간호대학생의 코로나우울과 자기효능감이 학업성취도에 영향을 미치는 요인을 파악하여 간호교육에 필요한 기초자료를 제공하기 위해 시도되었다. 연구대상은 N지역과 P지역에 소재한 비대면 수업을 경험한 간호대학생 245명이었다. 자료분석은 기술통계, t-test, ANOVA, Scheffé test, Pearson"s correlation coefficient, hierarchical multiple regression으로 분석하였다. 학업성취도는 코로나우울(r=-.226, p<.01)과 부적상관으로 나타났으며, 자기효능감의 하위요인인 일반적 자기효능감(r=.372, p< .01)과 사회적 자기효능감(r=.290, p< .01)은 정적상관이 있는 것으로 나타났다. 위계적 다중회귀분석 결과 일반적 특성 중 성별, 전공만족도, 성격성향, 학업성적, 비대면 수업 도움 유무가 학업성취도에 대해 19.9%(F=13.155, p <.001)의 설명력을 보였고, 코로나우울과 자기효능감의 하위요인인 일반적 자기효능감은 각각 2.8%와 3.4%의 유의미한 증분설명력을 보이는 것으로 나타났다. 따라서 비대면 수업 시 학생들의 우울을 감소시키고 자기효능감을 높이며 학생 개인별 특성을 고려한 수업전략과 학업성취도 향상을 위한 다양한 프로그램을 제공하여야 한다. The purpose of this study was to provide basic data for nursing education by investigating the effects of Coronavirus Disease-19 (COVID-19) depression and self-efficacy on academic achievement in nursing students who had an experience with non-face-to-face learning. A total of 245 nursing students living in areas N and P who had experienced learning were selected as the research subjects. Data analysis was performed using descriptive statistics, t-test, analysis of variance (ANOVA), Scheffé test, Pearson"s correlation coefficient and hierarchical multiple regression. Academic achievement had a negative correlation with COVID-19 depression (r=-.226, p <.01), while the sub-factors of self-efficacy, the general self-efficacy (r=.372, p <.01) and social self-efficacy (r=.290, p <.01), showed a positive correlation. The results of hierarchical multiple regression analysis, among the general characteristics, gender, major satisfaction, personality orientation, academic performance and non-face-to-face class help-level showed an explanatory power of 19.9% (F=13.155, p <.001) for academic achievement, and COVID-19 depression and the general self-efficacy showed significant incremental explanatory power of 2.8% and 3.4%, respectively. Therefore, it is necessary to provide nursing students with a range of online learning programs and class strategies considering the individual characteristics of each student to help them reduce depression, increase self-efficacy and improve academic achievement.
EVALUATION OF A BLENDED TEACHING MODEL BASED ON FLIPPED CLASSROOM AND STEAM APPROACH TO BOOST APPLIED SCIENCE CONCEPTS UNDERSTANDING IN TECHNOLOGY EDUCATION

Information about the paper titled "EVALUATION OF A BLENDED TEACHING MODEL BASED ON FLIPPED CLASSROOM AND STEAM APPROACH TO BOOST APPLIED SCIENCE CONCEPTS UNDERSTANDING IN TECHNOLOGY EDUCATION" at IATED Digital Library
Business Critical Solutions to Achieve Competitive Cyber Supremacy through Regulation and Policy

Panelists discuss the need for governance during the development and adoption of blockchain solutions, considerations when evaluating current and proposed legislation, recommendations for policymakers developing governance expectations and the current risks and limitations to policy development regarding industry adoption.
Attention module combined with A-U-Net architecture for image matting

Trimap plays an essential role in image matting. However, generating trimaps is expensive. Instead, we propose an architecture named A-U-Net equipped with both spatial and channel attention modules to estimate alpha matte without trimaps. However, there are two opposite phenomena observed in estimating alpha matte. The fine-structure edges connecting to the background should be preserved, whereas the texture details inside the foreground should be ignored. Thus, alpha matte is prone to making errors when the foreground is cluttered with texture or when both the foreground and the background have similar textures. To alleviate this problem, we design an additional classifier to learn the pure foreground from the input image. This “pure” indicates that those pixels must be foreground ones. Then, we add it to the original A-U-Net architecture result and successfully solve the problem. Extensive experiments have proved that our method is comparable or even better than other state-of-the-art methods.