Reviewerly/exHarmony huggingface dataset:
Local training system as an object of pedagogical design

The article analyzes the approaches to designing training which exist in pedagogy from the standpoint of systems engineering. The author substantiates the need to develop the approach that takes into account both the specifics of the requirements imposed on the training process, and the conditions of training and the characteristics of the contingent of trainees in which this training will be implemented. The concept is introduced and the conceptual model of the local training system is justified. The structure of the formulation of the problem of pedagogical design of the local learning system is determined. The article substantiates the classification of the local learning system as a system of systems, on the basis of which the goal of its pedagogical design is formulated.
METHODOLOGY OF ANALYSIS OF THE CONTENT OF ELECTRONIC MEDIA

In the conditions of modern information society, the analysis of the flow of media information is of particular importance. Therefore, the issues of content analysis, which is based on the conversion of qualitative data into digital format in order to obtain information processing capabilities using technologies of big-data analytics and artificial intelligence approaches, are especially relevant. This study summarized the views on the use of content analysis and proposed a methodology for analyzing the content of electronic media for targeting and determining preferences for the content of publications. For this purpose, were proposed were proposed a conceptual scheme for conducting content analysis, which consists of 5 stages. The first stage consists of creating and updating a full-text database on a daily basis by automated data collection and retrieval of content from media websites (web scraping). The second stage involves using of modules for determining useful content (parsing) and its subsequent storage in the database. The quantitative analysis stage is especially important when generalization, aggregation of results, or to calculate the frequency of words (frequency analysis), categories, tags and expressions, as well as their joint use in the text. The purpose of qualitative analysis is to reduce the material so that the main content remains. Similarly, qualitative analysis can provide additional information about individual components of the text (terms, definitions) in order to improve understanding, explanation, and interpretation of a particular passage. Finally, the last stage is to analyze the tone of the texts (sentiment analysis), i.e. to determine the emotional (positive or negative) attitude of the authors of the test to the described event, person or phenomenon. Authors (or users who leave comments) actively use various means in order to create the desired picture of an event in the reader’s imagination, and to evoke the appropriate emotions. The proposed methodology is the basis for the implementation of modern tools of content analysis using information technologies and methods artificial intelligence approaches.
Casuality. Educational issues of social media

The emerging generation is undergoing several changes in their cultural habits, values, and attitudes, and are very different from their peers. The trend shows that young people, young adults, and even parents are spending more and more time online and at the same time are using social media platforms more and more. In addition to its many benefits, media socialization has also brought with it many dangers and problems.
PENGEMBANGAN MODUL PEMBELAJARAN MENULIS IKLAN LAYANAN MASYARAKAT DI SMP BERBASIS PENDEKATAN SAINTIFIK

This research was conducted with the aim of developing products in the form of a learning module for Writing Public Service Advertisements in Junior High Schools, as well as describing the feasibility of the module. This research used Research and Development (R &amp; D) method which referred to Borg &amp; Gall’s design. Data collecting techniques using an interview with Indonesian language educator and the validation questionnaires by educator and material expert. The results of this research indicated that The results of this study indicated that the feasibility based on material expert validation on the aspects assessed obtained an average score of 4.4 and an average percentage of 87.5% with very decent criteria. The results of validation by Indonesian language educators on the assessed aspects obtained an average score of 4.6 and an average percentage of 92.8% with very decent criteria. Based on the results of the validation of material experts and educators, the learning module developed is declared suitable for use.
Planning of online bookstore activities

e-commerce enterprise management in Ukraine still features numerous problems stemming both from the underdeveloped facilities and infrastructure needed for distribution and wider use of e-commerce and from the lack of theoretical foundations of its functioning.Another important task is the search for tools that would provide for advanced computerization of management functions in e-commerce enterprises.
Automatic Summarization of Malayalam Documents using Text Extraction Methods

Text summarization is a technique for reducing lengthy passages of text into smaller portions. The goal is to develop a logical and fluent summary that only includes the document's major ideas. It's a important task in Natural Language Processing (NLP) that undoubtedly has a significant impact on synthesization of lengthy documents. With the rise of the digital documentation and publication, devoting time to thoughtfully read an article, document, or book in order to determine its relevance is no longer an option, especially given time constraints. In machine learning and NLP, automatic text summarization is a generic problem. A comparison of text summarization applying the Term Frequency ~ Inverse Document Frequency, Latent Semantic Analysis and Text Rank algorithms for the Malayalam language is presented in this research paper.
CRITICAL THINKING IN THE EDUCATIONAL IN THE FIELD OF EDUCATION

The purpose of the study was to identify and analyse the contributions made to the development of critical thinking in education.The study corresponds to basic research, with a systematic review research design, for the data collection procedures was carried out by means of the bibliographic and systematic documents search where scientific articles were selected in the search engines of Ebsco and Scielo, the same ones that have been ordered in an Excel matrix to facilitate their quick localization; in total 20 articles were selected.In the analysis technique, the documentary review was used, after the analysis of the results and the conclusions obtained according to the objective, it has been determined that the most predominant investigations have been those of quantitative, descriptive, qualitative and mixed type.The development of critical thinking is essential to become an integral person, so that the subject can define or fully understand a situation or problem that leads to its solution.In this context, a student, as a critical thinker, must develop constantly stimulated specific abilities so that they can be sufficiently enhanced to become a true skill.
Automation Attendance Systems Approaches: A Practical Review

Accounting for people is the first step of every manpower-based organization in today’s world. Hence, it takes up a signification amount of energy and value in the form of money from respective organizations for both implementing a suitable system for manpower management as well as maintaining that same system. Although this amount of expenditure for big organizations is near to nothing, rather just a formality, it does not hold as much truth for small organizations such as schools, colleges, and even universities to a certain degree. This is the first point. The second point for discussion is that much work has been done to solve this issue. Various technologies like Biometrics, RFID, Bluetooth, GPS, QR Code, etc., have been used to tackle the issues of attendance collection. This study paves the path for researchers by reviewing practical methods and technologies used for existing attendance systems.
Project-Based Training in the System of Professional Training of Students: Goals and Problems of Implementation

In this article, the author conducts a theoretical analysis of the concepts of “vocational training” and “project training”, and also addresses the consideration of project training as a modern technology in the professional training of students. At the present stage of professional training of future specialists, new technologies of professional training are being actively introduced. One of such effective technologies is project-based learning. This technology of training specialists differs significantly from traditional educational forms but it also has both positive and negative characteristics. Despite the existing negative aspects, domestic authors engaged in the study of project-based learning, note the prospects and effectiveness of the use of project-based learning in the system of vocational training. The effectiveness of the application of project training resides in the preparation of specialists for real professional activity. The project approach in teaching allows students to plunge into the practical sphere of their future specialty, perform practical tasks and gain real experience, form professional competencies and personal qualities necessary for further professional activity.
Assessment and Modeling of Industrial-Scale Solar Thermal System Application in Hungary

With approximately 1.2% growth annually, the industrial sector accounts for 54% of the total consumed energy globally. Most of those facilities use fossil fuels to generate their needs. Renewable energies, mainly solar energy, can play a major role in meeting the global policies of reducing carbon dioxide emissions. Presently, Hungarian researchers exploit more energy from renewable energies such as solar sources, wind, and biomass. Knowing that reducing the carbon emission level is a general tendency in Hungary. This article presents an extensive analysis of the solar thermal system in the central European climate, especially in Hungary. The scope of this study is the low-to-medium heat generation in industries such as pharmaceutical, pulp &amp; paper textile, food processing and beverages. Through all the applications, the heat is consumed in hot water form. Integrating solar thermal technology in the industrial sector depends mainly on solar radiation, conventional fuel prices, available installation area, and the complexity level of integrating the solar system with the existing process. Furthermore, more challenges show up during the integration of economic difficulties. This article analyses the feasibility of providing industrial hot water for small-to-medium enterprises (SMEs) in different Hungarian counties. The analysis was performed using T*Sol 5.5 software, and metrological data were obtained by MeteoSyn built-in software. Results indicate that the most suitable region for integrating solar thermal energy was Szeged, Szolnok, and Kecskemet, which supplied 54.89%, 54.16%, and 54.03% of the total heat load for the studied case, respectively. This result accounts for 849.57, 840.25 and 839.27 kWh/m2 of specific generated heat of the solar system. In addition, it results in points that the annual carbon dioxide saved amount is up to 4,442.3 kg and 2,100.7 m3 annual amount of natural gas. In conclusion, Hungary has a potentially attractive market for solar thermal systems to provide industrial hot water for small and medium-sized factories.
The Role of Teachers in Overcoming Difficulties in Learning to Read: Writing and Counting Elementary School Students

The purpose of this study concerns (1) the role of the teacher in identifying students who have difficulty learning to read, write and count; (2) after the student data is identified, it can be seen the factors that cause students to have difficulty learning to read, write and count; (3) for that the teacher has a role in overcoming difficulties in learning to read, write and count. This type of research is descriptive qualitative. Data were collected through interviews, observation and documentation. This study uses data analysis techniques, which consist of the stages of data collection, data reduction, data presentation and drawing conclusions, while the validity of the data is done by checking the results of interviews, data sources and implementation time. The results of the research conducted by grade 1 teachers were (1) identifying learning difficulties by analyzing the results of learning tests, basic ability tests, a scale of disclosing attitudes and learning habits, and observations during the teaching and learning process; (2) Factors that cause difficulties in learning to read, write and count are internal factors, external factors and learning approach factors. These three factors can influence the individual process so as to determine the quality of learning outcomes; (3) the role of the teacher in overcoming learning difficulties in grade 1 students is by guiding, educating, training, and assessing (2) Factors that cause difficulties in learning to read, write and count are internal factors, external factors and learning approach factors. These three factors can influence the individual process so as to determine the quality of learning outcomes; (3) the role of the teacher in overcoming learning difficulties in grade 1 students is by guiding, educating, training, and assessing (2) Factors that cause difficulties in learning to read, write and count are internal factors, external factors and learning approach factors. These three factors can influence the individual process so as to determine the quality of learning outcomes; (3) the role of the teacher in overcoming learning difficulties in grade 1 students is by guiding, educating, training, and assessing
Analysis of Transaction Data for Modeling the Pattern of Goods Purchase Supporting Goods Location

Arlinda shop is a shop that sells daily necessities located in Salem, Brebes. Each day, this shop generates more and more data that is not used. The store layout which does not get enough attention will affect the level of sales. This study aimed to process the unused transaction data to obtain purchase patterns, some of the most frequently used algorithms were the apriori algorithm and FP-Growth algorithm to find relationship patterns, however, there was a technical constraint in the recommendation technique used which was frequently ignoring a large collection of items. To overcome this problem, the clustering process was carried out using the K-Medoids algorithm so that the association process became smaller. The test was carried out using RapidMiner with a minimum support of 10% - 30% and a minimum confidence of 70% and the results of recommendations for the layout of the goods with the highest lift ratio, namely if someone buys Nuvo BW then he buys pepsodent act, if someone buys wrapping papers then he buys mamy poko, and if someone buys cereal milo then he buys chitato.
Knowledge Management Strategy by Means of Virtualization in Covid-19

In an era where companies, governmental programs, and the economy are knowledge-driven, they must understand the best ways to apply knowledge management to yield better results. Fortunately, technology is continuously evolving to better cope with knowledge management's arising challenges by innovating better problem-solving models. Cloud computing is one of the many technologies today that has revolutionized how different companies and economic sectors treat knowledge management by enabling this Knowledge's virtualization. The paper focuses on knowledge management transition to virtualization technology in supporting businesses during the COVID-19. Pandemic times despite many social restrictions being put in place to contain the virus. The text further presents the results of a study involving major firms in different sectors and how their applied virtualization technology is yielding results even during the toughest of times in any company or economy.
Machine Learning approaches for convergence of IoT and Blockchain

Abstract Blockchain plays a significant role in providing security during data handling operations and defines how trusted transactions can be carried out addressing the solution for internet facing vulnerability problems. Blockchain solves the security fault line among AI and IoT, where most of the IoT devices are connected to each other through public networks. This special issue aims to publish a collection of high quality research articles in the area of blockchain, IoT and Machine Learning.
ISLAMIC FEFAC AS AN INTERESTING LEARNING MEDIA TO IMPROVE STUDENTS’ ENGLISH ABILITY AND DEVELOP THEIR CHARACTER VALUES IN MAN REJANG LEBONG

The article aims to improve students’ English ability and develop character values in MAN Rejang Lebong. The subject of Community Service was 40 (fourty) students from low economic category that studied in MAN Rejang Lebong. The result showed that the service activities have been carried out well and smoothly without any obstacles; this community service showed improvement in students’ English ability. It can be seen in the result of pre-test and post-test (65 and 79). Then, this community service is also can develop students’ character such as active, independent, brave, responsibility, discussion, polite in the classroom. Students are very enthusiastic in receiving the learning material that has been delivered by the servant; and school plays an active role in supporting the implementation of this community service.
The raise of machine learning hyperparameter constraints in Python code

Machine-learning operators often have correctness constraints that cut across multiple hyperparameters and/or data. Violating these constraints causes the operator to raise runtime exceptions, but those are usually documented only informally or not at all. This paper presents the first interprocedural weakest-precondition analysis for Python to extract hyperparameter constraints. The analysis is mostly static, but to make it tractable for typical Python idioms in machine-learning libraries, it selectively switches to the concrete domain for some cases. This paper demonstrates the analysis by extracting hyperparameter constraints for 181 operators from a total of 8 ML libraries, where it achieved high precision and recall and found real bugs. Our technique advances static analysis for Python and is a step towards safer and more robust machine learning.
Sybil Attack Prediction on Vehicle Network Using Deep Learning

Vehicular Ad Hoc Network (VANET) or vehicle network is a technology developed for autonomous vehicles in Intelligent Transportation Systems (ITS). The communication system of VANET is using a wireless network that is potentially being attacked. The Sybil attack is one of the attacks that occur by broadcasting spurious information to the nodes in the network and could cause a crippled network. The Sybil strikes the network by camouflaging themselves as a node and providing false information to nearby nodes. This study is conducted to predict the Sybil attack by analyzing the attack pattern using a deep learning algorithm. The variables exerted in this research are time, location, and traffic density. By implementing a deep learning algorithm enacting the Sybil attack pattern and combining several variables, such as time, position, and traffic density, it reaches 94% of detected Sybil attacks.&#x0D;
Exploration of Sports Participation and Curriculum Resource Utilization in Primary Schools Before and After the “Double Reduction”

In order to eliminate capital chaos in the Education And Training (EAT) industry and ease parents' and students' excessive attention to subject achievements over physical quality, China government has launched the "Double Reduction" ("DR") policy which promotes students' Sports Participation (SP) in the Compulsory Education (CE) stage concerning students' physical and mental health. Firstly, based on the actual situation of students' SP before and after releasing the "DR" policy, this paper understands the exact needs of parents and children. Secondly, following empirical research and mathematical statistics, it analyzes the structure and characteristics of students' SP before and after the release of the "DR" policy. Mainly, the experiment focuses on the frequency, project types, and off-campus class expenditure. It also considers students' SP motivation in on-campus and off-campus sports classes before and after the "DR" policy proposal. Additionally the general curriculum resource utilization of PE teachers are surveyed in order to find out the current status of on-campus PE classes. Eventually, the strategies are put forward to optimize students' SP under the "DR" from the perspectives of family, school, and society. The results show that after the release of "DR", parents and schools gradually pay attention to student's physical health and better understand students' physical exercise in school. The consumption expenditure on sports off-campus classes has increased significantly. Meanwhile, family income and the father's occupation significantly impact the children's SP frequency in off-campus sports classes. Overall, "DR" is a protracted war. The existing difficulties need to be solved by families, schools, and the government. The research provides a practical basis for extending and managing on-campus sports classes and training. It helps timely uncover the problems in policy implementation. It guides the formulation of PE policy in the next stage of CE.
A Big Data Technique for Internet Financial Risk Control

The danger of losing funds on an investment or business enterprise is referred to as financial risk. Credit risk, liquidity risk, and operational risk are some of the most prevalent and different financial hazards. Financial risk control is an organizational activity that seeks to detect, monitor, and manage exposure to different risks associated with the usage of financial services. Conventional accounting risk control has relatively great timeliness and unpredictability; therefore, traditional accounting risk identification has numerous difficulties, such as high error rate, low precision, lengthy time, and risk. As a result, this research provides a unique financial risk control strategy in the Internet environment based on big data. First, the decision tree algorithm is used to classify the users who can face financial risks. Simultaneously, the user’s personal credit information is established and represented mathematically, and the 5C mathematical model is obtained. In this way, the user’s credit degree can be judged more accurately, and the user’s credit rating can be obtained, allowing quantitative analysis of users to be realized. Second, construct and weight the financial risk system index of the Internet in accordance with the existing financial system. Finally, the Internet financial risk control model based on big data is built, and the financial risk early warning threshold range is determined to achieve Internet financial risk control. The experimental findings reveal that the method’s risk identification error rate is minimal, accuracy is high, and control time is quick. It can match the actual risk level, which shows that the control effect of this method is good.