Reviewerly/exHarmony huggingface dataset:
ONLINE E-LEARNING AS AN ACTUAL FORM OF PREPARING STUDENTS FOR FUTURE PROFESSIONAL ACTIVITIES

The article is devoted to the actual pedagogical problem-the development of online e-learning in the conditions of digitalization of modern society. This problem is considered taking into account the increasing importance of electronic educational resources in improving the efficiency of the organization of the educational process in a remote interactive mode. The role and significance of the factors influencing the development of e-learning are presented: technical and organizational and methodological support of the educational process, the appropriate level of digital competence of the teaching staff, personal motivation of students. The results of recent studies conducted among students of the Pedagogical Institute of the North-Eastern Federal University (hereinafter-the University) and the Arctic Institute of Culture and Art (hereinafter-the Institute) for a complete picture of the state of network learning among students studying at the Institute and university, reflecting the main characteristics of the current state of digitalization of education. Based on the primary data of the study, the current problems are identified: the lack of contact interaction between the participants, which determines an individual, differentiated approach; compliance with personal conditions (motivation of the student); access to electronic sources of information; increase in the number of independent tasks in the absence of constant feedback from students, etc. The article reflects the approaches to determining the place of online e-learning in the system of professional training of future specialists using modern technologies in the organization of the educational process. The analysis of the obtained results shows that in order to implement the tasks of network learning, namely, the practical mastery of digital competence, training should be aimed at developing students ' sustainable interest in network learning.
Multi-Sentence Knowledge Selection in Open-Domain Dialogue

Mihail Eric, Nicole Chartier, Behnam Hedayatnia, Karthik Gopalakrishnan, Pankaj Rajan, Yang Liu, Dilek Hakkani-Tur. Proceedings of the 14th International Conference on Natural Language Generation. 2021.
University Library Development Strategy

The paper is devoted to the development of a university library strategy in the period of digitalization of all spheres of social activity. There are analyzed theoretical approaches and practical methods for developing strategic planning in library activities. The paper defines the need for strategic management as a factor in the effectiveness of a university library. There are considered the directions of the library strategic development, which depend on the vector of development of the university, its educational and research activities. The strategic planning is presented as a process of modeling the future activities of the library. It includes the library’s mission formulation, its objectives, tasks and events to achieve the goals, as well as its key performance indicators. The article sees the development strategy as an element of the management process aimed at creating and maintaining a strategic balance between the goals of the library and the university, its potential and likely development prospects. The article shows the advantages of SWOT analysis as a unique tool for designing a library development strategy. There are presented five stages of developing the Strategy for the Scientific Library of the Siberian Federal University. The authors note that the library has a good potential to develop the digitalization process: there is a digitization center, good technical equipment, its own software products, an extensive repertoire of world resources, a wide range of online services, etc. However, there are also weak points that hinder the library development: the obsolescence of the computer equipment, the lack of modern ergonomic space for individual and group work of students, the irregular acquisition of printed publications, the instability of funding, etc. All this can complicate the library development in the context of the digital economy development and lead to a decline in the prestige of the library. The library’s development strategy is aimed at eliminating these problems. It presents the goals, objectives, efficiency criteria for each area of activity of the modern library of the university. The article reveals the main strategic directions of the library’s development. The proposed strategy can become a real tool for optimizing the activities of all libraries in the transition period of the digital society development.
Application of Internet and information technology in school physical education

The integration of information technology into college physical education is not only the extension of educational connotation, but also the inevitable trend to adapt to the basic standard of college physical education. The comprehensive application of information technology and sports will expand the existing teaching methods, stimulate students' interest in learning, optimize students' learning path, improve the efficiency of classroom teaching, optimize students' skills, cultivate students' aesthetic emotion, and provide support for the realization of students' all-round development, so as to lay a solid foundation for sports teaching. In this paper, through the combination of software and hardware, the use of the latest information technology means, physical education information database construction and other methods, and combined with the relevant policy theoretical basis for research and elaboration, how to apply information technology to physical education in the corresponding solutions.
Modeling the process of ordering the main obstacles to the professional competence of future teachers

The problem of understanding the pedagogical aspect of the process of forming the professional competence of a future teacher who is able to model the educational process, independently generate and implement new ideas and technologies of teaching and upbringing, is relevant today, since a professionally competent teacher has a positive effect on the formation of the educational process. The article provides a theoretical generalization and practical solution to the problem of understanding the pedagogical aspect of the process of compiling the main obstacles to the professional competence of future physical culture teachers. The relevance of the study lies in the formation of an assessment of the level and the main obstacles affecting the development and improvement of the professional competence of a future teacher.
An Unsupervised Learning-Based Multi-Organ Registration Method for 3D Abdominal CT Images

Medical image registration is an essential technique to achieve spatial consistency geometric positions of different medical images obtained from single- or multi-sensor, such as computed tomography (CT), magnetic resonance (MR), and ultrasound (US) images. In this paper, an improved unsupervised learning-based framework is proposed for multi-organ registration on 3D abdominal CT images. First, the explored coarse-to-fine recursive cascaded network (RCN) modules are embedded into a basic U-net framework to achieve more accurate multi-organ registration results from 3D abdominal CT images. Then, a topology-preserving loss is added in the total loss function to avoid a distortion of the predicted transformation field. Four public databases are selected to validate the registration performances of the proposed method. The experimental results show that the proposed method is superior to some existing traditional and deep learning-based methods and is promising to meet the real-time and high-precision clinical registration requirements of 3D abdominal CT images.
Integration of NLP and Speech-to-text Applications with Chatbots

Fast track article for IS&amp;T International Symposium on Electronic Imaging 2021: Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2021 proceedings.
Positive aspects and difficulties of teaching foreign languages in the blended learning course during COVID-19 pandemic

The aim of the research is to assess the learning process during a pandemic, provide feedback on this issue and promote a deeper understanding of the importance of the results of a Blended Learning Course project. This result clearly shows that effectiveness and satisfaction play an important role in involving students in this format of learning. It is obvious that the possibilities of self/ autonomous learning in BLC are significantly expanded. In general, it can be seen that the use of innovative and traditional forms of education makes it possible to obtain a much better result in the training of specialists. The experience of Vinnytsia State Pedagogical University in the implementation of blended learning shows that the integration of the traditional education system with e-learning is the most effective. The strategic plan for the development of the Pedagogical University for 2022 provides for the solution of a number of tasks that are directly related to the intensification of the use of digital technologies in the educational process.
Addressing Math Anxiety in a STEM World: Using Children’s Literature, Photography, and GeoGebra to Teach Mathematics and get Young People Ready for Gamification and Life

MacroWorld Publishing Co. is an independent global publisher of highest quality journals, monographs, revised dissertations, primary sources, bibliographies, textbooks, other books, eBooks, reference works and online resources.
Interactive simulation teaching system of electrical engineering based on virtual reality

The traditional simulation teaching system is limited by the system support software, which cannot realize good interactive teaching. To this end, an interactive simulation teaching system based on virtual reality for electrical engineering is designed. Based on the hardware consisting of ATmega328 chip as the core, sensors and surrounding circuits, the development tool OpenGL is used to draw 3D virtual teaching scenes. The system design is completed by using a double-layer hidden Markov chain to realize simultaneous interactive teaching of multiple paths. The comparison experiment shows that the teaching system has better interactivity, can effectively enhance students' learning interest, and has good user feedback.
An Overview of Explainable Artificial Intelligence (XAI) from a Modern Perspective

Explainable Artificial Intelligence (XAI) in the field of research is dedicated to the study of methods so that Artificial Intelligence applications produce solutions that can be explained to human beings, which seeks more transparent approaches, especially for deep neural networks. However, one of the greatest challenges of XAI is the difficulty in reaching a concise definition of what a sufficiently explainable model is, appearing as a counterpoint to the development of completely black-box models, that is, opaque models in which not even developers know how decisions are made. XAI is artificial intelligence programmed to explain its own purpose, purpose (rationalization of the decision process), providing where machines and devices digitally understand the environment and even context in which they operate and function and, over time, build underlying explanatory digital models such as AI that allows them to characterize, distinguish, and even describe real-world phenomena. XAI offers important information about how an AI makes decisions: the specific criteria used by the program to achieve a result; the reason why a decision was made, at the expense of other options; the appropriate level of confidence for different types of decisions; what errors the intelligent system in question is vulnerable to; and even how these errors can be corrected. Thus, people better understand the responses of these results, in the best and quickest way, and even how to solve problems. Therefore, this chapter aims to provide an updated overview of the XAI and your technologies, demonstrating a landscape view to the applied aspect, as also key concerns, and challenges, with a concise bibliographic background, featuring the potential of technologies.
Politeness Strategies for the Speech Acts of Indonesian Language Education Students in Pidie Regency

This study aims to describe the strategy of politeness in speech acts of final semester students of Indonesian Language Education at Pidie. This research focuses on the strategies of politeness speech acts used by the final semester students of Indonesian Language Education in Pidie Regency in communicating. This research was conducted with a qualitative approach. This research is a type of field research. The research was carried out in six stages: (1) making and distributing data source information instruments, (2) classifying the results of data collection as a reference for data collection, (3) recording student conversations when communicating freely in public places (4) transcribing data obtained by recording, (5) analyze and describe the research results carefully, (6) calculate the percentage of occurrence of each type of speech act politeness strategy used by students in communicating. The results showed that the final semester students of Indonesian Language Education in Pidie Regency used three of the four speech act politeness strategies, namely the type without a strategy, the type of positive politeness strategy, and the type of negative politeness strategy.
Using machine learning to examine preservice teachers’ perceptions of their digital competence

This research paper’s aim was to investigate both the pre-service teachers’ perceptions of their digital competence and if gender, type of the bachelor’s degree and age made the opinions different or not. To do so, the clustering analysis method was employed to analyze the areas and items of the digital competence questionnaires used as a data collection technique. The study group included 291 participants who are now teacher-trainees in Draa-Tafilalte Regional Teacher-Training Center in Errachidia and Ouarzazate in the south-east of Morocco. In so doing, a number of results attained and basically confirmed that the level of the teacher-trainees’ digital competence was low or weak and that the three parameters (the type of the bachelor’s degree, gender and age) played a significant role in shaping different opinions on their digital competence. This paper ended with some major implications that were drawn from the findings of this study in our bid to highlight some needs of the pre-service teachers that should be met in their training courses and related activities to develop their digital competence in teaching and learning process.
A Positive and Negative HFM for Speed Measurement

This paper details the wideband ambiguity function of hyperbolic frequency modulation (HFM) signal, because the ambiguity function of the HFM signal is coupled in the range dimension and speed dimension, a single HFM signal cannot eliminate the time delay caused by Doppler, which leads to ranging error. In this paper, a method of speed measurement and ranging based on positive and negative HFM combination signal is proposed, and the extensive simulation analysis of this method is carried out, which can better estimate the distance and speed of moving targets. It has reference value for engineering use application.
Occlusion disparity refinement for stereo matching through the geometric prior-based adaptive label search

In stereo matching, occlusion disparity refinement is one of the challenges when attempting to improve disparity accuracy. In order to refine the disparity in occluded regions, a geometric prior guided adaptive label search method and sequential disparity filling strategy are proposed. In our method, considering the scene structural correlation between pixels, the geometric prior information such as image patch similarity, matching distance, and disparity constraint is used in the proposed label search energy function and the disparity labels are searched by superpixel matching. Thus, the reliable disparity labels are adaptively searched and propagated for occlusion filling. In order to improve the accuracy in large occluded regions, by using the proposed sequential filling strategy, occluded regions are decomposed into multiple blocks and filled in multiple steps from the periphery; thus, reliable labels are iteratively propagated to the interior of occluded regions without violating the smooth disparity assumption. Experimental results on the Middlebury V3 benchmark show that, compared with other state-of-the-art algorithms, the proposed method achieves better disparity results under multiple criteria. The proposed method can provide better disparity refinement for typical stereo matching algorithms.
Model of online training in physical education under quarantine measures

A mixed learning model and a methodology for online physical education classes have been developed. The idea of the research is based on a new concept, the content of which is determined by us, as the integration of the discipline Physical culture and sport into the content of the subject Elective disciplines in physical culture and sports. For a convenient understanding of the problem, we propose to combine the name of the two subjects into the well-known term Physical education. The integration of the two disciplines will allow organizing an effective process for physical education in the context of online learning.
Contemporary Symbolic Regression Methods and their Relative Performance

Many promising approaches to symbolic regression have been presented in recent years, yet progress in the field continues to suffer from a lack of uniform, robust, and transparent benchmarking standards. In this paper, we address this shortcoming by introducing an open-source, reproducible benchmarking platform for symbolic regression. We assess 14 symbolic regression methods and 7 machine learning methods on a set of 252 diverse regression problems. Our assessment includes both real-world datasets with no known model form as well as ground-truth benchmark problems, including physics equations and systems of ordinary differential equations. For the real-world datasets, we benchmark the ability of each method to learn models with low error and low complexity relative to state-of-the-art machine learning methods. For the synthetic problems, we assess each method's ability to find exact solutions in the presence of varying levels of noise. Under these controlled experiments, we conclude that the best performing methods for real-world regression combine genetic algorithms with parameter estimation and/or semantic search drivers. When tasked with recovering exact equations in the presence of noise, we find that deep learning and genetic algorithm-based approaches perform similarly. We provide a detailed guide to reproducing this experiment and contributing new methods, and encourage other researchers to collaborate with us on a common and living symbolic regression benchmark.
Research on the Cultivation and Promotion of College Students’ Legal Quality and Legal Knowledge Based on Deep Learning

Under the new situation, it is urgent to strengthen the cultivation of the legal consciousness of young college students, which makes the research on the cultivation and promotion of college students’ legal quality and legal knowledge become very important. This article is aimed at studying the cultivation and promotion of college students’ legal quality and legal knowledge based on deep learning. This article first analyzes the legal quality and legal knowledge level of college students by proposing a questionnaire survey method, interview method, and interdisciplinary research method and establishes an explanatory structure model of the factors affecting the legal quality of college students; secondly, it introduces the basic theories of deep learning and explains its practical application; finally, the training rules of neural network are constructed through experiments, and the stage method of legal quality training based on BP neural network is introduced in detail. Considering that virtual reality technology has recently penetrated into the game industry and other fields, we have reason to believe that it will find ways to enter the legal knowledge training industry. The experimental results of this article show that the cultivation and improvement of college students’ legal quality and legal knowledge based on deep learning can reduce the momentary confusion and impulsiveness of college students. Among them, more than 80% of college students who know a little about the Constitution account for more than 80%, which also shows the importance of cultivating and improving the laws and regulations of college students. The results show that the method is accurate and fast.
A Survey on the State of the Art of Vulnerability Assessment Techniques

A suitable vulnerability assessment process improves the overall security of an organization, and therefore, reduces the chances that an attacker could breach the IT system. The detection of vulnerabilities is one of the first steps in software security lifecycle, but in some cases, it is not enough. Understanding how a vulnerability can affect the rest of the system as well as forecasting its exploitability are important issues when assessing its real impact. Under this premise, this paper presents an overview of the state of the art, including different approaches related to the detection, forecasting and propagation of vulnerabilities in software, focusing mainly on Machine Learning and Data Mining techniques.
Touring a Data Curation Network Primer: A Focus on Neuroimaging Data

This video article provides an introduction to a data primer which leads data curators through the process of preparing a neuroimaging dataset for submission into a repository. A team of health sciences librarians and informationists created the primer which is focused on data from functional magnetic resonance images that are saved in either DICOM or NIfTI formats. The video walks through a flowchart discussing the process of preparing data sets to be deposited into a repository, key curatorial questions to ask for data that is highly sensitive, and how to suggest edits to this and other primers. The primer grew out of a data curation workshop hosted by the Data Curation Network.
&lt;italic&gt;Vessel&lt;/italic&gt;: A Cultural Heritage Game for Entertainment

Museums are digitizing their collections of 3D objects. Video games provide the technology to interact with these objects, but the educational goals of a museum are often at odds with the creative forces in a traditional game for entertainment. Efforts to bridge this gap have either settled on serious games with diminished entertainment value or have relied on historical fictions that blur the line between reality and fantasy. The Vessel project is a 3D game designed around puzzle mechanics that remains a game for entertainment while realizing the benefits of incorporating digitized artifacts from a museum. We explore how the critical thinking present in solving puzzles can still encourage engagement of the story the artifacts have to tell without creating an historical fiction. Preliminary results show a preference for our in-game digital interaction over a traditional gallery and a desire to learn more about the artifacts after playing.