Reviewerly/exHarmony huggingface dataset:
Funktsii i printsipy filosofii kak osnova razvitiia universitetskoi nauki i obrazovaniia v Rossii

In this work devoted to philosophical issues of the history of science, some of the most important functions of philosophy are revealed, their connection with the principles of cognition based on the history of university affairs in Russia is shown, the directions of activity for the creation of a Comprehensive red book of nature and the noosphere as tasks of the near future in the conditions of the noospheric transformative planetary process are revealed.
A Study on the School Culture and Teaching Methods that Elementary School Teachers Consider Important

There are many predictions of how education will change in the future. In particular, the impact of technological and social change will make schools look different than they are today. Schools are expected to perform various functions in the future, and their forms and functions will differ from those of today. This study is mainly composed of two research contents. The first is about the school culture that teachers consider important in the future school, and the second is about the teaching-learning method suitable for the future. In this study, a survey was conducted on 81 elementary school teachers from February to April 2022. Data collection was conducted online. A total of 73 data were analyzed, excluding data judged to be insincere among respondents. The results are as follow. First, the most important thing for teachers to recognize is to operate a competency-oriented curriculum and set educational goals suitable for the future society. In addition, the most important teaching and learning methods of future schools recognized by teachers were student-student interaction, discussion-centered classes, and student-centered classes. Meanwhile, according to teachers, education using smart devices showed relatively low importance compared to other questions. Since this result is limited to elementary school students, it is necessary to interpret it carefully.
Differences in Creative Personality and Attitude, Creative Problem Solving, and Convergence Thinking of College Students According to Self-Regulation and Cognitive Flexibility Training VR Program Participation

This study used a cognitive flexibility training VR program that can view and solve problems from various perspectives, self-regulation, and self-regulation with the super cognitive ability required for creativity to improve college students' creative personality and attitude, creative problem solving, and convergence thinking ability. In addition, differences in creative personality and attitude, creative problem solving, and convergence thinking ability were analyzed before and after participation in the program. In this study, 55 students were recruited voluntarily among four-year E University students in Gyeonggi-do. The experimental tool is VR content developed by FNI Co., Ltd. The main contents are mainly composed of improving self-control ability, strengthening positivity, and enhancing interpersonal relationships. The IBM SPSS Statistics 25 program was used to analyze the collected data to test the research question. First, frequency analysis and descriptive statistical analysis were performed to examine the mean and standard deviation of the sociodemographic factors and measurement variables of the subjects. Moreover, to determine how consistently the measuring instrument was used, the reliability was validated by calculating the Cronbach's coefficient value. Furthermore, factor analysis was utilized to minimize the number of items in the developed measurement tool by removing variables unrelated to the component to be studied. Factor analysis has the purpose of reducing variables, removing unnecessary variables, identifying variable characteristics, evaluating the validity of measurement items, and creating variables using factor scores. In addition, to confirm the statistical significance of the average values of creative personality and attitude, creative problem solving, and convergence thinking before and after participating in the VR program, a matched-sample t-test was performed. As a result of the study, it was found that participation in the self-regulation and cognitive flexibility VR program had a positive effect after participation compared to before participation in creative personality and attitude, creative problem solving, and convergence thinking.
Effects of University Students' Educational Satisfaction on Convergence and Creative Competencies

The purpose of this study is to understand the effect of individual and educational factors on convergence and creative competencies of university students. In order to achieve the research purpose, educational satisfaction and creativity and convergence capabilities were measured among 1,379 students in 2021, and multiple regression analysis was conducted using the optimization scale method. The findings showed that if educational satisfaction which is an educational factor that can be managed by a university is high, then the influence of individual factors on the convergence and creative competencies can be reduced. In addition, it was found that satisfaction with extra-curriculum did not affect convergence and creative competencies, but satisfaction with liberal arts and major curricula had an effect on convergence and creative competencies. In particular, it was found that satisfaction with the major curriculum had greater influence on convergence competency, and satisfaction with the liberal arts curriculum had greater influence on creative competency. Based on the research results, it is recommended that universities open various liberal arts and major subjects, and maintain a high level of quality according to the students’ level. Moreover, liberal arts subjects must be directed towards improving creativity, and major subjects must be focused on improving job performance for employment.
Professional'no-tvorcheskaia samorealizatsiia kak tsennostno-tselevoi orientir professional'noi podgotovki spetsialistov sfery kul'tury

Chapter of the monograph reflects the problems of training specialists of a new creative type, who are distinguished by a high level of professionalism, who are ready for professional and creative self-realization, who have a need for constant professional and personal development and growth. Professional and creative self-realization was not previously considered as a value-target reference point for the professional training of specialists in the field of culture, which makes our study relevant, given the current priorities of higher education. The model of the process of training specialists in the sphere of culture for professional and creative self-realization developed by the author is built in accordance with the logic of a holistic approach in the unity of its internal structure (goal – content – means – result). In the process of implementing the model, a gradual increase in the quality of formation of the studied readiness was carried out. In the system of pedagogical means to form the readiness of specialists for professional and creative self-realization, innovative technologies (playing, projective, creative) are leading. The implementation of these technologies contributed to the acquisition of experience in personal, professional and professional-creative self-realization by future specialists in the field of culture. The special course «Theory and methods of training specialists for professional and creative self-realization» developed by the author is aimed at summarizing and mobilizing the knowledge of a block of general professional and special disciplines, developing special professional abilities (projective, pedagogical, creative) of professional qualities (creativity, general professional competence, competitiveness), as well as the gradual formation of readiness for personal, professional and professional-creative self-realization.
AI-eXplained (AI-X) [President’s Message]

I have an exciting new development to report to you that has been a joint collaboration between CIS and IEEE staff teams across multiple OUs. Together, we are introducing to the IEEE a new type of article that is being labeled “immersive”. Our original foray into immersive articles will appear in this publication and have an educational orientation. We call the category AI-eXplained (AI-X). Essentially, educators who are building interactive educational software to teach aspects of computational and artificial intelligence can now find a peer reviewed venue for those efforts. This is so cool. A two page extended abstract will appear in both the printed and online versions of the magazine, but the magic happens inside Xplore. The “real” paper is viewed like a supplement and contains all of the immersive components to bring this material to life, allowing the reader to directly interact with the content. It’s much better to experience a concept than to read an explanation. Note the (purposeful) similarity of our name, AIX, to the popular research topic XAI (eXplainable AI). Even though both concern explaining, the difference is that the former is an educational enterprise while the latter is a research topic. The very first such manuscript is in this issue of CIM. The paper is titled “Choosing Representation, Mutation, and Crossover in Evolutionary Algorithms” by Alexander Dockhorn and Simon Lucas (who first posed the challenge to me for CIS to produce interactive articles). Please look at the abstract, but really have some fun trying to solve the 8-Queens problem and explore how one can do it through evolutionary computation in the immersive content. This paper went through a rigorous review process designed for such contributions and will have the same publication credentials as any other published manuscript in CIM
Internet-based New Media in Information Visualization

With the rapid development of mobile wireless Internet, the arrival of the information age has changed the way we think and communicate, and the pervasiveness of social media has prompted us to live in a culture of continuous learning and sharing. The influx and collection of information need to be controlled and applied, which has prompted changes and innovations in the means of information dissemination. The human visual system has amazing processing functions, and the visualization of information enables us to quickly and effectively gain insight and understanding of the communication of information. This article aims to study the application of Internet-based new media in information visualization. Based on the analysis of the shortcomings of traditional media information visualization design, the development characteristics of new media, and the superiority of information visualization design in new media, it is necessary to conduct new information on the residents of a certain city. Media information visualization questionnaire survey to understand the city’s residents’ understanding of new media information visualization. The survey results show that new media information visualization has a wide range of applications. What residents know best is new media charts, accounting for 24.5%; next are data news and information websites, accounting for 20% and 19.5% respectively; what residents don’t know is interaction design, the number of people who understand is only 10%.
Automatic Face Mask Detection and Recognition Using Deep Learning

The fast advancement of computer vision allows for human-computer interaction and has a broad range of applications. Since the first instance of COVID-19 was discovered, the worldwide battle against the pandemic has started. People's everyday actions, in addition to different research and conclusions by medical and healthcare professionals, have become critical in fighting the pandemic. In China, the government has adopted active and effective isolation and closure measures, as well as active public collaboration, such as making it unnecessary to remain inside and wear masks. China, the nation where the pandemic initially broke out, has now established itself as the world's model for epidemic prevention. Of course, people wearing masks deliberately isn't enough. Wearing masks in public areas still requires supervision. Real-world applications utilizing deep learning use deep learning as a critical component. Object detection is extremely important. currently, deep learning detection models and algorithms are using object recognition as their objective, which has achieved tremendous success in finding the object from an image. As this is the era of the COVID-19 virus, people frequently wear masks to cover themselves to minimize the transmission of the coronavirus. Because some portions of the face are concealed, this makes face identification is a very challenging job. In certain cases, traditional facial recognition technology is still inadequate, so it is very urgent to improve the recognition efficiency of the existing face recognition technology on masked faces, as masks are part of life from now for the next two to three years. This study proposes that, in this process, manual inspection be replaced with a deep learning method, and that YOLOV5, the most powerful objection detection algorithm currently available, be used to better apply it in the real world. For this study, First, we use the YOLO V5 to detect face masks. Using Face Net’s trained model, we looked at the images to determine whether the subjects were wearing masks or not. Two separate medical face mask datasets have been brought together in one dataset for research purposes. Mean IoU has been utilized to determine the best number of anchor boxes, hence improving the object detection process. The results showed that the Adam optimizer got an average of 81% accuracy. Finally, a related conclusion is offered in the research as a comparison study. The new detector outperformed related work in terms of accuracy and precision.
Effectiveness of Nusa Board Media on Student Learning Outcomes at Dahlanuddin SD Surabaya

The teacher's role in creating fun learning is very influential in the dissemination of the material. If in the process of delivering learning materials the teacher is not optimal and students are less interested in receiving the material, it will affect the process of understanding students in the material presented. This study aims to determine the effectiveness of Nusa Board media on the learning outcomes of class I students at SD Dahlanuddin Surabaya. This study uses a quantitative approach with the One Group Pretest-Posttest method. The subjects of this study were the first-grade students of SD Dahlanuddin Surabaya. Data collection techniques using tests in the form of pretest and posttest. The data analysis techniques used were instrument analysis, validity test, reliability test, assumption test using One-Sample Kolmogorov-Smirnov test, and paired T-test hypothesis test. The results of this study indicate that there is a difference in student learning outcomes before and after the implementation of Nusa Board media with an average pretest score of 66.8 and an average posttest score of 86.25. The increase in the average score of students is also evidenced from the results of the statistical test output analysis of the paired T-TEST (2 tailed) test which shows sig (2.tailed) 0.000 &lt; 0.05. It can be concluded that hypothesis 1 is accepted, which means that there is a difference between the learning outcomes on the score pretest and posttest, and it can be concluded that the Nusa Board media is effective in improving the learning outcomes of first grade students at Dahlanuddin Elementary School Surabaya.
Research on Big Data Helping Government Audit Improve Quality and Efficiency from the Perspective of Rural Revitalization

The field of rural revitalization has always been the focus of the supervision of audit institutions. At the first meeting of the Central Audit Committee, the General Secretary stressed that we should adhere to strengthening audit through science and technology. Since we strengthened the construction of audit informatization, the concentration and integration of audit data have been continuously strengthened, providing significant development opportunities for big data audit in the new era. With the continuous progress of poverty alleviation and rural revitalization strategy, big data technology has been widely used in audit work, and plays an irreplaceable role in special audit. The field of rural revitalization has always been the focus of audit supervision. With the continuous progress of poverty alleviation and rural revitalization strategy, big data technology has been widely used in audit work, and plays an irreplaceable role in special audit.
Safest Path Finding Algorithms On Street Harassment Prevention

The present work aims to generate an alternative solution to the current problem of street harassment, a form of sexual harassment that generally occurs in a public space and in which women are mainly affected. To prevent street harassment, the idea is to design a program capable of showing the best route from one point to another in terms of avoiding street harassment and considering the distance between the two points, this two terms multiplied are the weights in our graph since all the weights in our graph are positive. Dijkstra was considered the best fit for our project. It is an algorithm specifically designed to find the shortest path between two vertices in a weighted graph. Not only it does what we need but also it is well known as a fairly low time complexity algorithm.
ONLINE NEWS CLASSIFICATION BASED ON ARTICLE HEADLINES THROUGH WEB CRAWLING AND MACHINE LEARNING

The amount of information from print and digital media is huge, which leads to intelligent analysis of large amount of data, all of which are large amount of unclassified data stored together will not give results, so we can make some decisions, Storing them together doesn't give required results, so it can done by taking some decisions.Therefore, it is necessary to categorize messages and use different algorithms to assign multiple tags based on the category.As more and more sources publish a large amount of news on the Internet every day, there is a need to categorize news articles so that users can effectively receive information.The news headlines classification task attempts to group news articles based on their titles in which the title is made up of few words.The classification process is divided into modules.These modules are web crawling, web scraping, text preprocessing and model fitting.Web crawling is used to extract information from body content of html pages from news websites.Web scraping is used to scrape all the data from website to get necessary data to classify news titles.Classification models called k-nearest neighbor, logistic regression, decision tree are implemented and results are compared.
Dansk betydningsinventar i et datalingvistisk perspektiv

&#x0D; &#x0D; &#x0D; In this paper we investigate the Danish sense inventory from a paradigmatic and a syntagmatic perspective, respectively, and we present a collection of related lexical semantic resources that we have developed in collaboration between The Society for Danish Language and Literature and The University of Copenhagen. The resources comprise a Danish wordnet (DanNet), The Danish FrameNet Lexicon, and The Danish Sentiment Lexicon. All three resources are designed to enable semantic processing to be used in digital humanities research as well as more broadly in language-centric technology development. Finally, in order to illustrate the use of the resources when processing running text, we provide some annotation examples of each resource.&#x0D; &#x0D; &#x0D;
The Effect of Picture Series Towards Students’ Writing Skill In Recount Text at The Eighth Grade Students’ of SMPN 6 Malingping Lebak-Banten

This research paper aim to investigate the effect of picture series towards students’ writing skill in recount text at the eighth grade students’ of SMPN 6 Malingping Lebak Banten in academic year 2021/2022. The method used in this research was quantitative method. The design of this research was quasi-experimental design and cluster random sampling: the researcher used VIII A (20 students) as class experimental and VIII B (20 students) as class control. In the collecting data technique, the researcher used pre-test and post-test. The analysis data used to test research hypotheses using SPSS 25.0 is test of paired samples test. The results of the research concluded that there are a significant effect of picture series towards students’ writing skill in recount text with a significant value (p-value) = 0.000. They are &lt; α = 0.05. The results of the research indicate that the hypotheses is accepted. According to the criteria of the test, it could be concluded that there was was progress in the effect of picture series towards students’ writing skill in recount text at the eighth grade students’ SMPN 6 Malingping Lebak Banten was effective
Indonesian Cultural Perspective Critical Discourse Analysis in Junior High School Level English Textbooks

Language is a tool for people to communicate with structured words and sentence patterns. However, when there is a language there is also a culture that bonds together with language. One of the language that the world use is English. English has a very high demand in every sectors including education sectors. In education sector, English serves as the main subject in EFL countries, one of the EFL countries is Indonesia, and the teaching and learning English activity in Indonesia is still relying on textbook. Textbooks in Indonesia is rarely showing a cultural content which cultural contents in the textbook can be one of the appreciation of preserving a traditional culture. In this research, the author will analyze the discourse that found in a Junior High School level textbook, English on Sky 2 whether there is any Indonesian Cultural Perspective that included within the textbook. This research method will be using a qualitative method with descriptive analysis as the approach of research design.
A novel state estimation approach for suspension system with time-varying and unknown noise covariance

Abstract In this paper, a novel state estimation approach based on variational Bayesian adaptive Kalman filter (VBAKF) and road classification is proposed for suspension system with the time-varying and unknown noise covariance. Using the VB approach, the time-varying noise covariance can be inferred from the inverse-Wishart distribution, then optimized state estimation by finite sampling posterior probability distribution function (PDF) of noise covariance and backward Kalman smoothing. In addition, a new road classification algorithm based on multi-objective optimization and linear classifier is proposed to identify the unknown noise covariance. Simulation results for a suspension model with time-varying and unknown noise covariance show that the proposed approach has a higher performance in state estimation accuracy than other filters.