Reviewerly/exHarmony huggingface dataset:
VALUE-SEMANTIC ORIENTATIONS AS DETERMINANTS OF THE FUTURE PSYCHOLOGISTS’ PROFESSIONAL CULTURE

Public demand sets high demands on the professional training of future psychologists. One of the urgent problems is the formation of the professional culture of the future specialist. The article analyzes value orientations and meanings as determinants of the professional culture of future psychologists. A theoretical analysis of the concept of ‘professional culture’ has been carried out. It is indicated that there are disagreements in the opinions of scientists on the interpretation of this phenomenon. It has been established that the level of formation of professional culture determines the degree of readiness of an individual for activity in the profession. In the context of our research, it has been determined that professional culture is manifested in the way of organization, development and implementation of professional activity based on axiological principles. It has been determined that the role of value orientations in the process of formation of professional culture is that value orientations determine professional behavior, ensuring its content and orientation. It has been noted that the level of development of the professional culture of future psychologists will be influenced by the integral of the professional value of future specialists, which consists of the personal axiosphere, professional axiosphere, and social axiosphere. It has been established that by assimilating and transforming values, the student builds his own value system based on which he develops a personal and professional concept of professional culture and the meaning of professional activity. We believe that professional culture and value orientations are complementary formations, as they are formed under the influence of each other, determine not only the cognitive interests of the individual and professional interests, but also determine worldview guidelines, the general life credo. Since the professional culture of the future psychologist begins to form during training, we assume that its formation is also influenced by the values of university education. It has been concluded that values and meanings in professional culture act as regulators of behavior and relationships of the future psychologist in the ‘psychologist-client’ system.
ABOUT THE PROBLEM OF GOAL SETTING IN THE PROCESS OF TEACHING BACHELOR STUDENTS ENVIRONMENTAL DESIGN

The article deals with the problem of the formation of students – future environmental managers of the ability to set goals in the process of studying at higher school. The features of design activity and the specifics of learning environmental design are considered. Objective and subjective reasons for the lack of formation of the ability to set goals in mastering professional design knowledge and skills are revealed. The specific features of the goal setting in the qualitative acquisition of higher professional education among the younger generation are analyzed. The approaches to solving the identified tasks are defined and the provisions contributing to improving the quality of professional training of university graduates in the field of environmental design are summarized.
A SWOT and Impact Analysis of Chat GPT

Chat GPT is a potent natural language processing technology that can produce replies to user inputs that resemble those of a human being. Several businesses have used it successfully, including customer service, education, and entertainment. This paper intends to thoroughly examine Chat GPT’s advantages, disadvantages, possibilities, risks, and effects on the economies of India and other countries. As AI technology advances, Chat GPT will need to adapt and develop to maintain its competitiveness in the market.
METHOD OF CONTROL CHARTS FOR STUDYING CHAOTIC DYNAMICS OF RR INTERVALS

The article analyzes literature on the use of Shewhart control charts for various purposes and presents examples of applying a proposed statistical method in medicine. The study demonstrates that it is possible to identify situations common for the transferring stage from one functional condition to another (including pathologic one) using Shewhart control charts for prediction of critical conditions in the biosystem and its parameters (on the example of time series of cardiovascular system’s RR intervals).
Object Detection Using TensorFlow

What do you think can redefine clarity to the world? By bringing the potential of AI into our lives, we can unlock the power of object detection, which allows computer systems to see their environment in visual images. Object detection is a rapidly developing field with many potential future directions and there is still much to explore and discover in this exciting area of research. It is an essential aspect of computer vision that has numerous practical applications, including autonomous driving, robotics, and surveillance. In this study, we present an object detection framework that combines real-time performance with high detection accuracy. We conducted a comprehensive analysis of various deep learning models for object detection within the TensorFlow framework. The TensorFlow library offers a variety of machine learning models through its TensorFlow Model Gardens, which can be used for further studies and experimentation purposes by instructing and re-instructing their behaviour. The input image is passed through the SSD architecture, which is used to find objects based on deep neural networks for accurate identification. This system is fully implemented using the Python programming language because Python is a multitasking tool and needs relatively fewer lines of code to perform operations. As deep learning models and AI technologies continue to progress, there is a huge potential to enhance the precision, capability, and performance even more of real-time object detection methods. This research paper presents an object detection approach using the TensorFlow framework and demonstrates its effectiveness and potential for practical applications.
THE USE OF MIND MAPS IN PRIMARY SCHOOL

The article is devoted to an actual problem – the use of mind maps, an innovative way of organizing information, in the educational process of an elementary school. The possibility of using mind maps in the educational process has been investigated. The relevance of using mind maps in today’s conditions is described, the advantages of using this technology in educational institutions are analyzed. A review of the literature of foreign and Ukrainian scientists was made, a conclusion was made about the lack of research on mind maps as a means of intensifying the educational process in Ukrainian language classes in primary school. The method of using mind maps in native (Ukrainian) language lessons in the 3rd grade is described. The results of an experimental study are presented, the effectiveness of the proposed method using memory cards is proven. The study showed that the method of using mind maps in Ukrainian language lessons in primary school is useful, effective, and interesting. Mind maps make it possible to properly learn educational material in a concise verbal and figurative form, because they reflect the natural way of thinking of the human brain, correspond to the structure of human thinking (associative, visual, hierarchical). It was concluded that the use of mind maps in native language lessons in primary school contributes to the intensification of the educational process. The possibility of using mind maps for learning any language, as well as for other educational subjects, was noted. Prospective directions for the use of mind maps, in particular for teaching children with dyslexia, have been determined.
Retrospective and Prospective Analysis of Chinese Foreign Language Education Policies (1949-2018)

With the deepening of globalization, foreign language proficiency has gradually become an indispensable skill for individuals. Foreign language education policies have also evolved in tandem with societal development. In China, early foreign language education primarily served the nation's international communication and cooperation needs, meeting the demands of economic and trade collaboration. With the deepening of reform and opening-up, foreign language education policies have continuously improved, and the reasons for individuals learning foreign languages have shifted from serving the nation to enhancing personal capabilities, ultimately contributing to the country. This paper explores the relationship between Chinese foreign language education policies and societal development. Using a literature review approach, it retrospectively examines the development of policies from 1949 to 2018, summarizes factors influencing foreign language education policy development, and analyzes how policies respond to changes in societal demands, contributing to China's societal development. The paper also provides prospects for policy development to adapt to evolving societal needs. In conclusion, the paper asserts that updating foreign language education policies requires not only keeping pace with economic developments but also demands a deeper focus on enhancing disciplinary content, optimizing educational resource allocation, and innovating educational approaches to comprehensively optimize foreign language education policies.
Nonlinear Modeling and Control of 3-DOF Gyroscope Actuated Furuta Pendulum by Takagi-Sugeno Fuzzy Systems

This paper presents the derivation of the equations of motion of a 3-DOF gyroscope with a pendulum attachment through the Euler-Lagrange approach, followed by a conversion into a Takagi-Sugeno Fuzzy Model. First, suitable coordinate frames and generalized coordinates are defined, followed by the definition of the kinetic energy of each body frame of the gyroscope. Next, the kinetic and potential energy of the pendulum attachment is described. The derived equations of motion are then validated by simulation and compared to the behavior of a testbed system (see Figure 1). The conversion to the Takagi-Sugeno fuzzy model is done by a weighted combination of locally valid linear models. A set of adequate premise variables and membership functions represent the nonlinear system. Finally, a controller synthesis through parallel distributed compensation and LMIs satisfying local quadratic Lyapunov functions is conducted and validated by simulation.
From Graph Theory to Graph Neural Networks (GNNs): The Opportunities of GNNs in Power Electronics

Graph theory within power electronics, developed over a 50-year span, is continually evolving, necessitating ongoing research endeavors. Facing with the never-been-seen explosion of graph-structured data, the state-of-the-art deep learning technique-Graph Neural Networks (GNNs), becomes the leading trend in machine learning within just recent five years and demonstrated surprisingly broad and prominent benefits covering from new drug discovery to better IC design. However, its promising applications in Power Electronics are still rarely discussed and its full potential remains unexplored. Addressing this gap, this review paper is the first to outline GNNs’ general workflow in power electronics, laying the groundwork and examining current GNN methodologies within the field. To bridge the gap in the sparse GNN literature within this domain, we also provide extended discussions on leveraging insights from GNN-aided circuit design to enrich power electronics research. Our work includes in-depth GNN-based case studies that demonstrate promising applications from converters to system-level power electronics, showcasing GNNs’ unique benefits and untapped possibilities (e.g., accurate component design, voltage predictions on IEEE-13 bus and 118 bus systems). Additionally, we provide a comprehensive survey of GNNs’ latest and successful applications, emphasizing their impact on energy-centric sectors, such as transportation electrification, smart grids. Considering the interdisciplinary nature of power electronics in modern energy systems, our review highlights the potential of GNNs emerge as a promising tool to decode the intricate behavior and dynamics of power electronics systems, and we hope such synergies between advanced AI methodologies like GNNs with the ever-evolving graph theory can lead to more powerful tools, novel methodologies, and advancements in the power electronics community.
LinkFND: Simple Framework for False Negative Detection in Recommendation Tasks with Graph Contrastive Learning

Self-supervised learning has been shown to be effective in various fields, proving its usefulness in contrastive learning. Recently, graph contrastive learning has shown state-of-the-art performance in the recommendation task. They created two views and learned node embeddings so that target nodes in the two views attract each other based on the target node, and non-target nodes in the two views repel each other. However, they overlooked the fact that false negatives can occur when negative pairs are repelled. It has been shown through various studies that false negatives in contrastive learning in various fields can have a negative impact on model training, but research on the impact of false negatives in link prediction tasks, such as recommendation tasks, where classes cannot be clearly defined, is still hardly explored. In this paper, we propose an approach to define false negatives in link prediction tasks and fully utilize them in learning. Learning by defining false negatives and removing them from negative pairs showed consistent improvements over existing graph contrastive learning on five benchmark datasets. In addition, we found through comprehensive experimental studies that learning by removing false negatives is of great advantage, especially for low-density datasets. On top of these advantages, our false negative detection and false negative elimination can be naturally integrated into any graph contrastive learning architecture.
Basic Elements and Characteristics in Building an Expert System

The basic elements and characteristics of an expert system are important in the application of an expert system, so that in the application of a makar expert system, the basic elements and characteristics of an expert system are first known. By knowing the basic elements and characteristics of an expert system, the goals and benefits of making an expert system can be more focused and have good fundamentals.This journal is a learning system in designing and knowing expert systems that have fundamental characteristics, so that the utilization that is carried out can run well.
Inspecting the efficiency of cryptocurrency markets: New evidence

The purpose of this study is to examine the market efficiency of cryptocurrencies, specifically at a weak level. The study focuses on six prominent cryptocurrencies selected based on their significant market capitalization: Bitcoin (BTC), Tether (USDT), Ethereum (ETH), Binance Coin (BNB-USD), Ripple (XRP-USD), and Cardano USD (ADA-USD). The analysis utilizes unit root, Ljung–Box, variance ratio, runs, and the Brock–Dechert–Scheinkman (BDS) tests to assess different aspects of market efficiency. The data spans from September 2017 to April 2023, encompassing a wide time frame to capture potential shifts in market behavior. The results of all the tests, except the BDS test, indicate that the tested cryptocurrencies' markets are inefficient. However, the BDS test yielded different results, suggesting that BTC and ETH exhibit market efficiency compared to the other cryptocurrencies. This discrepancy indicates that the BDS test may be capturing different aspects of the time series behavior. The practical implication is that investors and market participants should exercise caution and consider the varying levels of efficiency when making decisions regarding these cryptocurrencies. Also, investors should consider a range of factors, including technical and fundamental analyses, when making investment decisions in a dynamic and evolving market.
Penerapan Media Interaktif dengan Model Discovery Learning pada Pembelajaran Tematik untuk Meningkatkan Keaktifan dan Hasil Belajar Peserta Didik Kelas VI SDN 62 Lebong

This study aims to describe the application of interactive media in discovery learning (DL) model in thematic learning, describe the activity and learning outcomes of learners with interactive media using DL model in learning in sixth grade VI SDN 62 Lebong. This type of research is classroom action research. The subjects of this study were teachers and students of sixth grade SDN 62 Lebong the research instruments used were observation sheets and evaluation tests. Observation data analysis techniques using the formula average score, highest score, lowest score, difference score and range of values for each criterion while the analysis of test data using the formula to find the average value and the percentage of completion of learning. The application of learning using the learning model Discovery Learning with interactive media runs smoothly and can improve the liveliness and learning outcomes of students proved by the results of the study showed the liveliness and learning outcomes of students in the first cycle of good predicate and increased in the second cycle with the predicate very good . Thus it can be concluded that learning with interactive media with discovery learning model can increase the liveliness and learning outcomes of students in thematic learning in sixth grade SDN 62 Lebong Keywords: thematic learning, Interactive learning media; learners activity; and discovery learning.
The perplexities of E-Discovery in the Indian healthcare system - A narrative review &amp;nbsp;

With the rapid advances in medical technology and the digitization of healthcare systems, the importance of collecting and analyzing digital evidence in the medical field has grown significantly. This evidence plays a crucial role in investigating medical malpractice cases and preparing for legal proceedings in India. As medical devices and electronic health records become more prevalent, vast amounts of data are generated, stored, and accessed. While having substantial evidence to support medical claims is beneficial, it is essential to find a balance between retrieving and admitting digital evidence while respecting patient privacy. This article examines the use of electronic evidence in Indian medical litigation, the challenges it presents, and the initiatives taken to manage these challenges. However, the absence of clear legal guidelines on electronic discovery in medical cases exacerbates the problem. Medical procedure rules often fail to address electronic discovery, resulting in inconsistent case law across different courts in India and the world. Consequently, healthcare practitioners are left to develop ad hoc solutions through informal discussions and negotiations. Thus, this paper highlights the necessity for a comprehensive legal framework and active judicial management to handle electronic discovery in the medical domain.
A Study of the Characteristics of Elected Presidents of the Major National University (1988-2023)

Objectives The purposes of this study is to analyze the characteristics of presidents appointed at major national universities in South Korea over a period of 35 years since the introduction of the direct presidential appointment system in 1988. The research questions are as follows: First, what are the demographic characteristics, academic backgrounds, and career experiences of presidents at major national universities? Second, are there any differ-ences in the demographic characteristics, academic backgrounds, and career experiences of presidents based on the universities they lead?&#x0D; Methods To achieve the study’s objectives, data on 78 presidents of nine major national universities appointed since 1988 were collected from various sources, including the university websites, the Korea Research Foundation's Korean Researcher Information, the Korea University Newspaper, Naver Person Information, and the Korea Press Promotion Foundation's BIG KINDS. The collected data were analyzed using the SPSS 27.0 program. Descriptive statistics were initially calculated to identify the overall trends, and ANOVA and chi-square tests were conducted to detect differences between groups.&#x0D; Results Most of the presidents of national universities were male and were appointed in their late 50s. They often had regional connections. All the elected presidents were professors, and most of them had prior experience in executive-level positions at the university. These characteristics were consistent across the nine major uni-versities studied. However, the ratio of presidents from their alma mater and the characteristics of the president's academic field exhibited slight variations depending on the university. Notably, the proportion of presidents from their alma mater sometimes exhibited significant differences between universities.&#x0D; Conclusions This study analyzes who became president by examining the characteristics of elected presidents rather than explaining why they became president. The study results simply illustrate the characteristics of elect-ed presidents over the past 35 years. To explain why someone became president, further research is needed to understand how these characteristics influence the presidential election process.
The Effect of Early Childhood Teachers’ Digital Literacy and Digital Play Teaching Efficacy on the Implementation of Digital Play Based on the 2019 Revised Nuri Curriculum

Objectives The purpose of this study was to examine the effects of early childhood teachers' digital literacy and digital play teaching efficacy on the implementation of digital play based on the 2019 revised Nuri curriculum.&#x0D; Methods For data collection, 378 early childhood teachers in Gyeongnam, Daegu, Seoul, Incheon, and Sejong were surveyed by questionnaires about teachers’ digital literacy, digital play teaching efficacy and the implementation of digital play based on the 2019 revised Nuri curriculum from 27 Jan 2023 to 7 Mar. For data analysis, descriptive statistics, Pearson’s correlation, and hierarchical multiple regression analysis were used by SPSS 27.0.&#x0D; Results First, early childhood teachers' digital literacy was in high level, and digital play teaching efficacy and the implementation of digital play based on the 2019 revised Nuri curriculum were above medium level. Second, there were found some significant positive correlations among early childhood teachers’ digital literacy, digital play teaching efficacy and the implementation of digital play based on the 2019 revised Nuri curriculum. Third, early childhood teachers’ digital literacy and digital play teaching efficacy was found to influence on the implementation of digital play based on the 2019 revised Nuri curriculum.&#x0D; Conclusions In order to promote early childhood teachers' implementation of digital play based on the 2019 re-vised Nuri curriculum, it is important to increase the level of digital literacy and digital play teaching efficacy, and teacher education is required to support this.