Reviewerly/exHarmony huggingface dataset:
A Novel Clustering Based on Consensus Knowledge for Cross-Domain Fault Diagnoses

In recent years, cross-domain fault diagnosis problems based on knowledge transfer have attracted considerable attention from researchers, some of whom have adopted domain adaptation algorithms for model transfer under various working conditions. Such algorithms typically assume the samples of the target and source domains share the same fault mode sets and that the source and target domains are interrelated. However, such prior knowledge is difficult to obtain in actual industrial fault diagnoses. To address this issue, we propose a universal domain adaptation network model based on consensus knowledge (CKUAN). This model adopts cluster matching and domain consensus scores to mine effective knowledge from the class and sample levels, thus eliminating the dependence on prior knowledge of the label set. Furthermore, we introduced a contrastive domain discrepancy (CDD) to jointly optimize clustering. Experimental results on two diagnostic datasets demonstrate the proposed CKUAN method to be robust and effective, and it yields higher performance than existing state-of-the-art cross-domain fault diagnosis methods.
Analyzing and Recreating Data Visualizations of W.E.B. Du Bois

In February 2021, Allen Hillery, Athony Starks, and Sekou Tyler, started the #DuboisChallenge,and annual online challenge where participants use modern data visualization toolssuch as R, Python, and Tableau, among others, to recreate the data visualizations by W.E.B.Du Bois. The challenge took place again in February 2022 and it was featuredin 2021 and 2022 as part of the weekly online data visualization event TidyTuesday(https://github.com/rfordatascience/tidytuesday). This column presents examples of activities for the classroom that are inspired by the #DuBoisChallenge.
The Influencing Discovery Exploration &amp; Action Forum: An Initiative of the American Statistical Association

The vision of the ASA is to empower a world that relies on data and statistical thinking to drive discovery and inform decisions. The ASA Leadership Institute and the IDEA Forum are strategic initiatives to help the association realize this vision. The IDEA Forum focuses our attention on important global problems and builds strategic partnerships with leaders from all sectors to drive innovation and highlight the critical role played by statisticians in finding solutions to these global problems. This article provides the background on the development of the inaugural IDEA Forum and describes the event.
Monitoring of asymmetric values and parameters of electric networks

This paper considers the digitalization of electrical networks, the organization of remote control of the values and parameters of electrical energy, the creation of digital elements, devices and complexes for monitoring and managing power quality indicators based on Cloud Computing technology, the conversion of primary currents into signals in the form of secondary voltages, and also discusses management issues symmetrical quantities and parameters of these converters. In addition, a model of a three-phase AC converter with specific loads and analytical expressions for determining the output voltage of a three-phase AC converter with a specific load based on the configuration of this model are presented, a cloud computing algorithm for studying a three-phase AC converter, the characteristics of electrical loads are given, the dynamic characteristics of electromagnetic three-phase load current converters, graphs of magnetic fluxes and a three-phase current converter of specific loads, stabilization mode in the conversion system of electromagnetic converters of three-phase current in 0.02-0.03 seconds after being connected to the network under a special load, an algorithm for constructing dynamic characteristics and generating analytical expressions. Based on this information, conclusions were drawn about the cost and parameters of three-phase current electromagnetic converters.
Developing E-learning course "Circular Economy" in the Study process and Adult Education

The educational process has changed; many more technologies and solutions are involved in preparing the subject and the study process. A degree of maturity in using digital tools has been reached, allowing the student to learn the subject whenever and wherever he or she wishes. The experience gained in the USA shows that in the case of successful development of an asynchronous course, in combination with really extended feedback, even content-compliant courses can be acquired in this way very successfully. The purpose of the article is to show a success story of developing a modern e-learning course, modernizing and digitizing their study courses. A complete cycle of "learn by doing" and "do by learning" approaches are being implemented for the first time. By support Erasmus+ project is developing an innovative, asynchronous online course on the topic of Circular Economy and will to improve teachers' digital pedagogical competencies by enabling them to provide a high-quality learning process. At all levels of education, it is essential to keep up with the requirements of the 21st Century and opportunities, to change previous thinking and accept digitization is the duty, mission and task of every teacher, student and administrator.
Digitalisation in engineering education: practice challenges and opportunities

Digitalisation is the current tendency of modern life. It touches upon various spheres of society. This article contributes to this issue undertaking engineering education practice challenges and opportunities. The article aims at developing new insights: 1) by evaluating the importance of digitalization for the educational process, 2) by introducing the theory and methodology of digital transformation of engineering education, 3) by illustrating the implementation of digital tools in engineering practice. The following theoretical methods were used in the study: a method of theoretical analysis, method of generalisation of accumulated experience, survey method, and predictive methods (forecasting), also empirical research methods: observation, modeling, abstraction, comparison, and analysis of the results of students' educational activities. The article describes the successful experience of using digital technologies on the basis of the Department of Foreign Languages, and the analysis of the practice of using digital tools at Volgograd State Technical University. This approach makes a great contribution into revealing challenges and perspectives of engineering education, stimulating its transition from research to practice.
An Efficient Bet-GCN Approach for Link Prediction

The task of determining whether or not a link will exist between two entities, given the current position of the network, is called link prediction.The study of predicting and analyzing links between entities in a network is emerging as one of the most interesting research areas to explore.In the field of social network analysis, finding mutual friends, predicting the friendship status between two network individuals in the near future, etc., contributes significantly to a better understanding of the underlying network dynamics.The concept has many applications in biological networks, such as finding possible connections (possible interactions) between genes and predicting protein-protein interactions.Apart from these, the concept has applications in many other areas of network science.Exploration based on Graph Neural Networks (GNNs) to accomplish such tasks is another focus that is attracting a lot of attention these days.These approaches leverage the strength of the structural information of the network along with the properties of the nodes to make efficient predictions and classifications.In this work, we propose a network centrality based approach combined with Graph Convolution Networks (GCNs) to predict the connections between network nodes.We propose an idea to select training nodes for the model based on high edge betweenness centrality, which improves the prediction accuracy of the model.The study was conducted using three benchmark networks: CORA, Citeseer, and PubMed.The prediction accuracies for these networks are: 95.08%, 95.07%, and 95.3%.The performance of the model is comprehensive and comparable to the other prior art methods and studies.Moreover, the performance of the model is evaluated with 90.13% for WikiCS and 87.7% for Amazon Product network to show the generalizability of the model.The paper discusses in detail the reason for the improved predictive ability of the model both theoretically and experimentally.Our results are generalizable and our model has the potential to provide good results for link prediction tasks in any domain.
Professional online communication of a student in conditions of sustainable development of social systems

The article presents a description of the internal predictors of student success as a subject of communication in digital professional communities. The determinants of student success as a subject of modern communication in the digital environment are described. The role of communicative control, empathy, the chosen strategy of behavior in a conflict situation in the implementation of productive communication is shown. An analysis of the features of the manifestation of internal predictors of student success in the context of interaction in professional digital communities is presented. The introduction presents an analytical review of psychological research on student success as a subject of communication in digital professional communities. Clusters of factors that determine the success of students' communicative activity in the digital professional and educational environment are generalized and typified. The aim of the study is to study the success of a student as a subject of communication in digital professional communities. The study used a method of communicative self-control, an empathy scale, a test for studying behavior strategies in conflict. The article describes the main results of the study of self-control in communication, the level of empathy and the strategy of behavior in conflict as predictors of student success as a subject of communication.
Personnel engagement based on quality standards requirements as a factor in modern organization development

The article describes the main stages of the development and implementation of the process of engaging and improving the competence of employees as one of the principles of the quality management system by the example of a transport company. Based on the international standard ISO 10018:2014 "Quality Management. Guidelines for Employee Engagement and Competence" the strategic process of employee engagement and competence is considered. It was noted that often the engagement of employees is based on the stimulation of employees' work, which is not the main tool of their interest and retention. It is necessary to move to a new level of work with personnel, to create conditions for their involvement, to qualitatively improve this process. The importance of employees' labor assessment, improvement of their qualification and development for the growth of employees' performance and competitiveness growth of the transport company as a whole was determined. The role of managers and their leadership qualities in the implementation of the personnel engagement system has been determined.
Adaptation of students to interaction in the digital environment as a factor of sustainable educational and professional behavior

The article presents a characteristic of the features of students' adaptation in educational and professional interaction in a digital environment. The factors of successful adaptation of students, the role of ideas and subjective control in this process are shown. An analysis of the features of manifestations of subjective control among students in the process of interaction is given. The introduction presents an analytical review of research on the problem of students' adaptation to interaction in the context of digitalization, systematizes and typifies the main groups of factors that motivate students' effective activity in educational and professional interaction. The aim of the study is to study the peculiarities of technical students' ideas about the determinants of successful adaptation in the digital environment. The study used questionnaire methods, a subjective control test (SCT). The article describes the main results of studying the perceptions and qualities of students that contribute to successful adaptation to educational and professional interaction in a digital environment.
Scientific activity of students as an important factor of sustainable development in the scientific and social spheres

For sustainable development in various fields, highly qualified personnel are required. One of the ways to train such personnel is to involve young people in scientific activities while studying at the university. The author asks questions: how do students of psychological specialties perceive scientific activities, what emotional states arise in students when thinking about scientific activities or directly in the process of doing it. The introduction contains researches devoted to students' research activities; author presents his own model. The section "Methods" describes the sample: 73 students of psychological specialties; the author's questionnaire is given. The section "Results" reveals the students' opinion on how scientific activity can be included in various types of student activity, students' perception of scientific activity and their emotional states when thinking about it. The most frequently chosen emotional states are: interest and inspiration. The section "Discussion " contains the results obtained by other researchers. The author offers practical steps to popularize scientific activity at the university and introduce students to it. In conclusion, it is concluded that some university students have a superficial knowledge of research activities. Some students who would potentially like to start doing research don’t do it.
Prerequisites and factors of sustainable development through the introduction of innovative technologies in education

The article is devoted to the study of modern stage of introduction of modern innovative technologies in higher education system in the segment of Christian religious education as one of the aspects of modern theory and practice of confessional pedagogy from the standpoint of educational theology based on the saint fathers' and world experience. A brief overview of the development and current state of the educational system is given by the example of the Department of Theology at the Don State Technical University. The combination of the theological model with secular components of professional education, which is carried out both by programs corresponding to the Federal state educational standards, and by confessional university educational programs, which passed the Church accreditation of the Educational Committee of the Russian Orthodox Church, is considered. The article provides a substantiated conclusion about the Christian model of reproduction of pedagogical staff, capable of qualified work both in confessional educational institutions and in secular educational sphere, created in Donskoy State University. The analysis of effective experience in the use of innovative methods and forms of teaching has been carried out.
Formation of critical thinking in preparation future air transport specialists

The research describes the possibilities of critical thinking, its influence on the motivation for the formation of social and professional competencies. The relevance of the research is that today the formed critical thinking affects the success of graduates, their demand among employers and is a key indicator of assessing the quality of university activities. The novelty of the research consists in the development of technology for the forming of critical thinking among students of flight specialties, proof of its effectiveness in the practice of the educational process is provided. The methods of forming critical thinking among students during the implementation of the basic discipline «Physical Culture and Sports» are considered, which provide, in addition to optimizing the psychophysiological states of students, the development of social qualities - initiative, independence, competence, the ability to think critically, which affect the motivation to achieve results not only in physical training and sports activities, but also in professional aviation training. The practical significance of the research lies in the intensification of professional and applied training of students of aviation universities, which will help any student to navigate in the future profession and will eventually give the opportunity to manage the safety of aircraft flights.
Organizational conditions for successful professional activity (views of pedagogical community)

The article shows the results of theoretical conceptualization and empirical testing of organizational conditions of successful professional activity of teachers in modern Russia on the example of the territories of the southern region. Based on a theoretical review of the scientific literature on the interpretation of organizational conditions, the variables for testing the significant and latent characteristics in the empirical part of the study were formulated. An electronic survey of educational community representatives of the Stavropol Territory by random sampling was conducted. A total of 243 people from the scientific and pedagogical staff of North Caucasus Federal University, Stavropol State Agrarian University, and Stavropol State Pedagogical Institute took part in the survey. The database of the survey was subjected to statistical analysis in the program SPSS (version 24). The results of the study are the basis for the development of programs to improve organizational conditions of scientific and pedagogical staff of universities, increasing their effectiveness and solving important economic problems of personnel training in the region. Taking into account the request of the professional pedagogical community for optimizing organizational conditions will enable the university administration to make reasonable managerial decisions in the field of personnel policy.
Hierarchical Classification Method Based on Weighted Barycenter to Resolve the Problem of Group Separation

In this paper we propose an improvement of the Barycenter method; this will be done by introducing the notion of weighted center of gravity and by measuring distances and similarities to address the problem of separation of classified groups.
COVID-19 Contact-Tracing Technology, Users’ Privacy and Security

Nowadays, the entire world is struggling to adapt and survive the SARS-CoV-2/COVID-19 pandemic, the new mutations in the Coronavirus disease is causing damage and disruption across the world. Taking preventive measures to control the spreading of the virus, including lockdowns, curfews, social distancing, masks, vaccination are not enough to stop the virus. Many countries have sought to support their contact tracers with the use of digital contact tracing apps to manage and control the spread of the virus. Using the new technologies to adapt the prevention measures furthermore enhancing the existing ones, will definitely be more efficient. There are many contact tracing apps that have already been launched and used since 2020. There has been a lot of speculations about the confidentiality and security aspects of these apps and their possible violation of data protection principles. In this paper we propose a system of contact tracing, we explain how this system treats sensible information to preserve the user’s identity and protect their personal information.
Recommender System Using Machine Learning and BLE Beacons

Nowadays, Recommender system is present in our daily activities, people need the help of computer systems and machine learning to simplify their regular activities. Grocery shopping is an everyday essential task of people’s life so the retailers must exploit the advancement of technology to know their customers better and to improve their marketing strategies. This paper aims to apply machine learning algorithms to the development of a recommender system capable of preparing personalized grocery shopping lists. The proposed framework exploits K-means algorithm and Apriori association rules to understand the customer’s behavior. The K-means algorithm was used to identify groups of customers based on transactional data and movements of customers; it also divides customers into ten groups of customers. Apriori association rule was used to characterize the groups of customers by creating customer profiles. The analysis of customer behavior is helpful for the decision marketing managers to send the right promotion to the right consumer at the right time.
Pedagogical Scenarisation for Virtual Environments of Training: Survey

Virtual Environments for Training (VET), gained significant attention and popularity over the last years, thanks to the fast and remarkable technological progress. VET are based on virtual reality (VR) to offer users an outstanding experience. VET can not only enhance students to acquire knowledge and abstract concepts, but also develop specific skills by learning in an environment that offers high level of interaction. However, the success of a VET to reach its goal, do not depend only on the technological tools, but also on the pedagogical side. Thus, the trainer/teacher must create a pedagogical scenario to guide the learner through his experience in the VET. This paper aims to examine the existing literature to address currently used methods and approaches to model and create pedagogical scenarios for VET.
Development and Feasibility Study of an Autonomous Obstacle Detection System for Landing Operations

Potential obstacles on landing sites are becoming an increasing problem for aircraft landings, especially during challenging visual conditions for the pilot in command, and during fully autonomous landing operations. A novel vision based autonomous detection scheme has been proposed to allow the detection of obstacles on the runway. Using Detectron2 as the detection network, accurate detection and segmentation of runways and obstacles have been achieved all with over 95% accuracy. Network training has been done using transfer learning and over 1500 custom image dataset, achieving 73% average precision. Several modules have been developed for live data acquisition, pre-processing the data, which is then processed through the trained network. Data is then post-processed to be passed on to the custom decision-making algorithm, which outputs a decision based on obstacle location and its states. The complete network has been tested in a virtual, as well as real life environment, achieving promising results.
Real Time Victim Detection in Smoky Environments with Mobile Robot and Multi-sensor Unit Using Deep Learning

Victim detection in smoky indoor environments during search and rescue missions is still challenging and a critical situation. This situation is because firefighters are on the one hand exposed to unstable building structures and on the other hand their cognitive fatigue, due to long search missions, reduces the efficient victim detection in these hazardous environments. In this paper, an approach to detect a victim in real time with an optical and low resolution thermal camera assisting firefighters in their missions is presented. Thereby, the multi-sensor unit is mounted on a remote-controlled mobile robot with a trained victim detector using deep learning and display the detection in real time to an operator outside the scene. Experiments show that this approach enables an efficient detection in smoky indoor environments. The victim detection model achieves an average detection rate above 75% in real time with a low resolution thermal camera in dense smoke.