Reviewerly/exHarmony huggingface dataset:
The Idea of Digital Intelligence Empowering the Creation of a Tutoring Platform for Primary and Secondary Schools in the Same City

Under the background of the "double reduction" policy, information asymmetry between supply and demand in the tutoring service industry in the same city for primary and secondary schools has led to social conflicts in the tutoring market that coexist with high and arbitrary fees and damage to the legitimate rights and interests of the service subjects (college students). In the digital era, integrating digital wisdom into the tutoring service market will help break the limitations of time and space and reduce communication barriers in tutoring services. Use big data, Internet and other technologies to create a digital smart platform for two-way selection of tutoring services to help both supply and demand parties choose and communicate directly online. This will not only help build an efficient, convenient and reasonably charged tutoring service market, but also promote tutoring. Digital transformation and development of the service industry.
Improving Understanding Regarding Dangerous Goods and Blind Spot at SMAN 7 Denpasar

It is important to know and understand about dangerous goods and the procedures for transporting dangerous goods, especially for the younger generation can help the transport of dangerous goods reduce the number of accidents in the transportation of goods. Reducing the number of freight transport accidents is one way to implement safety and security when driving. Many young people do not understand safety and security in driving, and on this basis the Bali Land Transportation Polytechnic provides an understanding of the blind spots for dangerous goods transportation. This activity uses socialization/counseling methods to participants regarding the load of dangerous goods on the road and blind spots. The target of the Community Service Program (PKM) is aimed at students of SMAN 7 Denpasar, this is closely related to the role of youth/students and driving safety when dealing with dangerous goods transportation. It is hoped that this socialization will provide an understanding of dangerous goods in order to realize the role of the younger generation in the safety and security of the transportation of dangerous goods. After conducting socialization regarding dangerous goods, participants were able to understand the explanation given and answer the quiz questions properly and correctly.
Development of A Guided Discovery Learning Model Based on E-Learning in Thematic Learning

The research objectives include several things. The aim is to develop and analyze the effectiveness of an e-learning based guided discovery learning model in thematic learning for class V elementary school. The way to answer the research objectives is to use the ADDIE Research and Development (R&amp;D) model. The school sample for testing the effectiveness of the model developed was selected based on probability sampling. After the sample was determined, the research results showed that the validity of the learning model was very good and could be used, while the results of the effectiveness of the model implementation could be understood through the posttest results and the results of filling out the questionnaire. Based on these results, it can be concluded that classes that use the guided discovery learning model have higher learning outcomes on average. The average learning outcome of students who studied with the e-learning based guided discovery learning model in the test class was 91.47 with a completion rate of 100%, while the control class which used the guided discovery learning model showed an average learning outcome of 88.33.
Digital and Network-Based Methods for Narrative Criticism

The exegesis of biblical texts is usually a manual task. However, in computational linguistics, automated and artificial-intelligence-based methods are an emerging trend. This paper discusses possible intersections between computer-based natural language processing, analysis of narrative and literary texts, and narrative exegesis of biblical texts and in particular network-based methods. The problem with applying narrative criticism is its variety. The approaches differ slightly, not only due to the different original languages between OT and NT, but also between different literary approaches and schools in different countries. However, narrative approaches are a bridge to digital and network-based methods used in the humanities and computer linguistics. Thus, this paper provides an overview of already established methods and discusses a critical evaluation of possible synergies towards linked data, social network analysis, and knowledge graph approaches. Despite limitations regarding data management and accessibility several methods could be suitable for interdisciplinary research: The detection of time and space, sentiment analysis and the integration of social network analysis into narrative exegesis. Besides, the discussion with computer linguistics may give new perspectives for narrative exegesis.
CORRELATION OF AUTOMATED CELL COUNTER RBC HISTOGRAMS AND RBC INDICES WITH PERIPHERAL SMEAR IN DIAGNOSIS OF ANEMIA.

Background: Anemia's morphological alterations can be inferred from red blood cell (RBC) indices and the histogram produced by an automated analyzer. They can be utilized to determine the cause of anemia in addition to the peripheral smear. Objective: The current study aimed to improve the method for diagnosing anemia by correlating the typing of anemia based on RBC indices and histograms acquired from an automated analyzer with peripheral smear testing. 184 anemic patients had blood samples taken, and the blood samples Materials and Method: were rst typed for anemia using parameters from a haematology analyzer (RBC indices with red cell distribution width), and then the results of a peripheral blood smear. The signicance of the mean difference in various parameters was determined by analyzing the connection between the diagnosis made by peripheral smear vs RBC indices and histogram. Based on a Results: peripheral smear test, the most common type of anemia was microcytic hypochromic (63%) followed by normocytic normochromic (35.9%) and macrocytic (1.1%). 62%, 37%, 1.1%, and microcytic hypochromic, normocytic normochromic and macrocytic respectively, were shown by RBC indices analysis. 114 of the 116 (63%) instances of microcytic hypochromic anemia on smears showed a left shift, and the other two cases displayed a normal curve. Sixty-six cases of normocytic normochromic anemia showed a normal curve. In two examples of macrocytic anemia, histograms exhibit a shift to the right. Conclusion: Although RBC and histogram indices provide useful information, peripheral smear testing is still the most crucial diagnostic method for haematological diseases.
Evaluasi Algoritma Klasifikasi Machine Learning Kategori Nilai Akhir Tunjangan Kinerja Pegawai

Allowance is a gift of appreciation for services in the form of an imbalance in work performance or performance dipsplayes. AT the moment the agency has not used the final value category for employee salary allowances, the program needed to determine the final category of employee benefits with a Machine Learning approach using the C4.5 and Naive Bayes Gaussian algorithms and evaluation of prediction results using Confusion Matrix and K-FOLD Cross Validation. The purpose of this research is to results of classification predictions in the category of using the final salary of employees of Confusion Matrix and K-FOLD Cross Validation. After mining the data, the performance of each algorithm is evaluated determine mining success rate process on the C4.5 and Naive Bayes Gaussian algorithms. Then the result is obtained and the C4.5 algorithms is a better algorithm in determining the category of employee salary allowance values.
Analisis Prediksi Stroke Menggunakan Pendekatan Decision Tree dengan Seleksi Fitur dan Neural Network

Currently, stroke is the second cause of death globally. According to data from the World Health Organization (WHO), 7.9% of deaths in Indonesia are caused by stroke. Based on these data, analysis of the factors influencing the case growth rate is very useful. This paper analyzes various factors in electronic health records for effective stroke prediction with different machine-learning algorithms including Decision Tree and Neural Networks. This research uses a dataset consisting of 12 features, namely ID, gender, age, history of hypertension, history of heart disease, marital status, type of work, type of residence, average glucose level, BMI (Body Mass Index) number, and status. smoking, and prediction of stroke. These features were analyzed using the Neural Network and Decision Tree methods so that selected features were produced for further analysis using the Neural Network method. The feature selection results consist of 5 features: age, history of hypertension, marital status, average glucose level, and BMI (Body Mass Index) number. The highest accuracy results were obtained using the Neural Network method with a feature selection of 88.75, the second highest was obtained with the neural network method of 87.1875, and the lowest accuracy was obtained with the Decision Tree method which had an accuracy result of 81.25. Based on these accuracy results, it can be obtained that the most optimal results are shown by the Neural Network method with feature selection.
DEVELOPMENT OF THE ETHNOCULTURAL COMPETENCE AMONG STUDENTS IN THE PROCESS OF USING QR TECHNOLOGIES

The article presents an analysis of the inclusion of QR technologies in the educational process, which help students become acquainted with the culture of the peoples living in the Chelyabinsk region, as well as with the heritage of cultures of other countries. The relevance of the study is due to the need to get acquainted with the cultural heritage of different ethnic groups to strengthen relationships in the modern world. Informatization of society and mobile technologies are adjusting the requirements for organizing the educational process, making it possible to use interactive learning tools such as QR codes in the learning process. The purpose of the study is to analyze the inclusion of QR technologies in the educational process that contribute to the formation of ethnocultural competence among students. The novelty of the research is presented as the development of specifi c educational tactics aimed at getting to know the national culture, which can be used in extracurricular activities and in German language classes. The methodological basis was the research of Zh. Z. Zarkenova, Yu. A. Komarova, E. V. Volkanova, Yu. A. Uzlov, S. A. Chernyavskaya, devoted to the formation of ethnocultural competence. The main research methods, in addition to the analysis of scientifi c literature, were methods of observation, personal involvement in the learning process, and generalization of one’s own teaching experience. The pedagogical experiment was organized and conducted among students of the Faculty of Foreign Languages of the South Ural State Humanitarian Pedagogical University and students of the training direction “Recreation and Sports and Health Tourism” of the Ural State University of Physical Education. In classes, as well as as part of extracurricular educational work with students in experimental groups, QR technologies were used to promote the development of ethnocultural competence. The results of the analysis of the pedagogical experiment confi rmed that the formation of ethnocultural competence in students is possible with a special thematic organization of training sessions and extracurricular activities. The use of QR technologies makes it possible to make classes interactive and attract students’ attention to the problem
ANALYZING THE RESULTS OF THE STUDY OF STUDENTS’ MOTIVATION TO STUDY ENGLISH AT THE GYMNASIUM

This article describes the main methods and factors infl uencing the formation of positive sustainable motivation for educational activities of students. The problem is that children studying from 7th to 9th grade are characterized by a drop in the level of motivation to learn a foreign language at school. There are so-called “risk groups” - children who have an extremely low level of motivation to learn English. The purpose of this study is to examine the level of motivation development of students (optimal, suffi cient or low) in order to improve the learning process and identify effective methods to increase the motivation of students and, consequently, their performance in this subject. A study was conducted among students in grades 7–9 at a gymnasium in the city of Kirov through questionnaires using various methods. As a result of the questionnaires, 15% of students were found to have a low level of learning motivation development, and the types of learning activity organization in which students were more interested and which stimulate them to study English were identifi ed. The most effective types of organizing educational activities were games, group work, project activities and others. Ultimately, based on the analysis of the students’ responses in grades 7, 8 and 9, ways, methods and techniques for working with students included in the “risk group” were developed, and recommendations were given for organizing the educational process of students from 7th to 9th grade.
On the role of professional standards in assessing the readiness of future social educators for work

The article provides a study of the Republic of Kazakhstan's "Social Pedagogue" professional standard in terms of the measurability and non-measurability of skills and abilities by meters that are currently utilized in the country as part of the National Qualification Tests (NQT). This is the sole qualification examination administered in the field of education. In the context of the NQT, specialists in the field of education (teachers working in schools; future teachers, i.e., graduates of pedagogical universities; social educators, etc.) are subjected to testing in which their subject-matter knowledge in particular fields is evaluated. The goal of this article is to determine if the format of the present qualifying exam is consistent with the expected results of the professional standard, which outlines the required knowledge, skills, and abilities of social educators. An review of these requirements revealed that the current instrument for assessing the readiness of social educators to engage in professional activities is insufficient for determining the specialists' degree of preparedness. Within the context of our article, we present our solution to this issue. A focus group study was conducted, in which 190 future social educators studying at universities of the Republic of Kazakhstan took part. As a result of the study, three most common problems were identified: the inability to control children's visits to social networks; the difficulty of working with migrant families; the increase in autistic children. A social pedagogue interacts with students, their parents, teachers, social workers, psychologists, juvenile inspectors, and many others in the course of his profession. Due to this, it is vital to pay close attention to the training of specialists and to change the instrument used to determine their professional level. Key words: qualifying exam, qualification, professional standard, assessment of the readiness of specialists, measurability and non-measurability of skills, assessment procedure.
Use of cutting-edge technologies: incorporation and efficiency in journalism education

Rapid advancements in technology have revolutionized various aspects of our lives, and journalism education is no exception. As classrooms or lecture halls embrace digital tools, academic disciplines of journalism and media practitioners have the opportunity to reimagine teaching and news reporting experiences, making them more engaging, personalized, and effective. This article aims to highlight the diverse ways in which cutting-edge technology can be leveraged to enhance educational outcomes, promote digital literacy, and equip learners, including aspiring journalists, with the skills needed to thrive in a rapidly evolving world and succeed in journalism practice. A survey of 200 students from two universities in Kazakhstan revealed that the majority were satisfied with the integration of high technologies in the education system. However, challenges such as technical issues, inadequate training, and concerns about overreliance on technology were identified. This research has scientific significance as it can inform future studies on digitalization in education. It also has practical significance for journalism institutions, helping them improve the implementation of advanced technologies by considering student feedback. In conclusion, the study contributes to the development of integration of innovative technologies in journalism education since it provides detailed information about students’ opinions, who are directly affected by the process of digitalization.&nbsp
Intuitionistic fuzzy level operators related to degree of uncertainty

Two new intuitionistic fuzzy operators of level type are introduced and some of their properties are studied. They are related to the degree of uncertainty of a given intuitionistic fuzzy set. Geometrical interpretations onto the intuitionistic fuzzy interpretation triangle are provided.
Attitudes of the Jordanian Public towards Advertisements by Artists in Satellite Stations and their Impact on their Purchasing Behavior: A Field Study

This study aimed to identify the Jordanian public’s attitudes towards advertisements by artists in satellite stationsand their impact on their purchasing behavior. The study falls within the scope of descriptive research, employing a survey methodology. A questionnaire was distributed among a sample of 491 Jordanian individuals residing in the Northern region, chosen using convenience sampling. The study applied the Dependency Theory and the AIDA model, reflecting them in the study's questions and objectives. The study reached the following results: It was found that there was an effect of advertisements by artists on satalleite stations on the purchasing decision, as the Jordanian public preferred advertisements of Arab artists and watched them on Arab satalleite stations in a large percentage, and that the most important factors attracting attention are colored photographs, the product presentation method, and the celebrity's personal charisma. Key factors in arousing interest included the presentation method, clear and appealing product display, and the use of a concise method to express the product suitable for various ages and education levels. The cognitive effects on the sample population included an increase in their knowledge of different cultures and a proper assessment of the product. Emotional effects involved a sense of satisfaction, and behavioral effects stimulated them towards making a purchase. A statistically significant relationship resulted between the degree of Jordanian audience engagement with celebrity advertisements on the stations and the existence of a statistically significant relationship between the effects (cognitive, emotional, and behavioral) of artists’ advertisements on satellite stations on the Jordanian public and the purchasing behavior.
Selected aspects of UAV group flight trajectory modeling

In this work, we present the methodology for creating a model of the movement of five flying UAVs that fly in a set formation. The movement of the UAV is modeled in the geocentric coordinate system (ECEF - Earth-Centered, Earth-Fixed). Such models are suitable for planning the movement of several UAVs when monitoring the terrain of interest or searching for objects. The methodology of creating models includes the creation of algorithms for the movement of five UAVs in the selected coordinate system and the selected assembly. The flight trajectories of five UAVs were formed by a straight flight section and several curvilinear flight sections. UAVs were assumed to fly in formations with a designated group leader. Also, the flight parameters of the UAV wm be similar to those of the General Atomics MQ - 9 Reaper type UAV, while the flight height wm be constant. In the presented work, we present one of the possible approaches to the creation of UAV movement models in a specified assembly. Flight simulations of five UAVs were performed using Matlab software.
Evolutionary Computation for Intelligent Data Analytics

Artificial Intelligence has been widely used during the last two decades and has remained a highly-researched topic, especially for complex real-world problems. Evolutionary Computation (EC) techniques are a subset of artificial intelligence, but they are slightly different from the classical methods in the sense that the intelligence of EC comes from biological systems or nature in general. The efficiency of EC is due to their significant ability to imitate the best features of nature which have evolved by natural selection over millions of years. The central theme of this presentation is about EC techniques and their application to complex real-world problems. On this basis, first I will talk about an automated learning approach called genetic programming. Applied evolutionary learning will be presented, and then their new advances will be mentioned. Here, some of my studies on big data analytics and modelling using EC and genetic programming, in particular, will be presented. Second, EC will be presented including key applications in the optimization of complex and nonlinear systems. It will also be explained how such algorithms have been adopted to engineering problems and how their advantages over the classical optimization problems are used in action. Optimization results of large-scale towers and many-objective problems will be presented which show the applicability of EC. Finally, heuristics will be explained which are adaptable with EC and they can significantly improve the optimization results.
Reparameterization for Improved Training and Weight Optimization in Single Image Super-Resolution Networks

In the field of Single Image Super-Resolution, convolutional neural networks have demonstrated notable advancements. While the integration of batch normalization, dropout, and other layers, which were previously detrimental, has led to larger, more proficient models, the efficacy of extant training pipelines for Super-Resolution models is still inadequate, even for smaller networks. We propose that the state-of-the-art training procedure is insufficient in identifying optimal weights for even a single convolutional layer. Our research reveals that the weights generated by the baseline training pipeline for all trained models conform to a specific space. We utilize the reparameterization technique to derive improved weights outside this designated space, leading to significantly enhanced performance and stability in prominent models, particularly in large kernel convolutions. We further highlight the importance of reparameterization in SR models and advocate its further exploration in future research.