Reviewerly/exHarmony huggingface dataset:
TRAINING OF FUTURE SPECIALISTS TO FORM A HISTORICAL AND ANALYTICAL VIEW OF GROWTH OF IT

The article substantiates the need for future specialists in computer science, as well as students who study in higher educational institutions and receive the profession of computer science teacher, to develop the skills of historical and analytical thinking regarding the development of information technologies. The importance of forming students’ historical consciousness is demonstrated, in particular, the skills of analyzing the most significant scientific and historical facts that contributed to the emergence of information technologies. We are talking about the importance of transferring knowledge about the basic prerequisites for their development, as well as about all the characteristic processes and patterns of progress in specific IT areas. An analytical approach to historical knowledge contributes to a deep immersion of students in the problems of the relevant field, and this can help teachers in stimulating young people to scientific and practical achievements, setting them up for professional growth, and also helps to form their digital competencies and key professional skills.
METHODS OF DEVELOPING CRITICAL THINKING IN STUDENTS IN PHYSICS LESSONS IN GENERAL SECONDARY EDUCATION INSTITUTIONS

The article describes the methods of developing critical thinking, which were developed based on the improvement of existing methods and their adaptation to the teaching of physics in institutions of general secondary education. The new Ukrainian school envisages the formation of key competencies and the ability to think critically in students. Therefore, it is important that future physics teachers possess competence-oriented technologies and teaching methods based on which critical thinking and appropriate competences can be formed in students. It is shown how the described methods can be used to develop critical thinking in gymnasium and lyceum students in physics lessons.
CONSTRUCTION OF A METHODOLOGICAL TRAINING SYSTEM FUTURE SCIENCE TEACHERS

The article convincingly proves the importance of creating an effective methodological system for training future teachers of natural sciences. The main task of the modern education system is to master the method of purposeful organization of the educational process, which provides an opportunity for multifaceted self-development of the individual, increases motivation for obtaining quality education. The components of the proposed system for the formation of the professional qualities of a teacher differ from other training systems in the following features: adaptability to modern educational requirements, goal-oriented organization of the training of a future specialist, content, the use of a competence-oriented approach to planning the educational process and evaluating the results of such activities. The issue of prospects for the use of innovative systems of professional training in the educational process gained further development. Their content includes training classes using both tradi tional teaching methods and those conducted with the help of modern tools and equipment. The possibilities of goal-oriented management of the professional training of future teachers are analyzed under the condition of creating an educational environment based on the introduction of research educational technologies into the educational process, which are materially provided with modern teaching aids, appropriate methodological developments and teaching aids.
MODEL OF FORMATION OF DIGITAL COMPETENCE OF FUTURE PHYSICS TEACHERS IN THE CONDITIONS OF STEM EDUCATION

The article discusses the concept of STEM education, its key properties. The main advantages and fundamental differences of this type of education in comparison with traditional methods, which include the main component of information, communication and digital technologies, have been formed. The content of the concept of digital competence, the acquisition of which is one of the qualitative results of the introduction of STEM education into the educational process, is analyzed. Based on the research of scientists, the main criteria for the formation of digital competence were determined and the main directions of the development of digital competences in future physics teachers were formed. Which include the use of digital technologies and various application programs to provide theoretical and practical material, the introduction of mobile devices, robotics tools, virtual laboratories, specialized software and hardware into the educational process.
SKILLS, ABILITIES, BELIEFS: HIGHEST LEVELS COMPETENCES AND OUTLOOK OF THE INDIVIDUAL

The multi-disciplinarily of STEM-integration innovations of the modern system of natural science education focuses on effective and high-quality formation of the future specialist through the prism of the formation of one’s own author’s credo as an essential indicator of his competence and worldview. Since the end of the 1990s, the problem of improving the quality of education of specialists in the field of natural sciences has become quite relevant in the educational policy of many European countries. Experience [3–13; 15; 17–22] confirms: the reform of science education on the basis of competency-based and worldview approaches can be fully resolved only under the condition of a comprehensive understanding of this problem, which involves updating state standards (learning content and educational environment), curricula, textbooks, manuals, tools, practical training etc. The formation of an individual’s natural and scientific competence takes place in the process of his mastering a set of sciences that study nature and its laws. STEM-integration of education prompts modern multi-disciplinarily to the need to optimize the process of solving the problem of managing the competence-viewpoint formation of a future specialist of any profile. The publication proves that the development of the New Ukrainian School focuses on the implementation of technologies of binary goal orientations (a specific academic discipline + its teaching method) as a means of forming a holistic natural and scientific credo of an individual: ensuring the readiness of a teenager, a young person, a specialist of any profile to study throughout all life and mastering the experience of mankind regarding the creation and use of high technologies in all possible scientific and industrial spheres of safe innovative human activity.
USING BYOD TECHNOLOGY AS AN EFFECTIVE MEANS OF FORMING STUDENT MOTIVATION IN STEM EDUCATION

The article analyzes the formation of research skills of participants in the educational process based on the use of augmented reality tools using the BYOD (Bring Your Own Device) approach: to increase the motivation of students in STEM education. The directions of using BYOD technologies in physics lessons in general secondary education institutions are determined and the methods of their use in practice are shown. During the preparation of the article, the following research methods were used: comparative analysis of the theoretical provisions of the developed scientific and educational and methodological literature; observation of the educational process in physics at the national school. Attention was drawn to the fact that the introduction of BYOD technologies in tandem with the principles of STEM education in the educational space contributes to the creation of a fundamentally new model of learning, with new opportunities for teachers and students. It is noted that the BYOD direction contributes to the fact that the educational process becomes more flexible, the individual educational needs of each child are taken into account, and favourable conditions are created for their education. Various forms of student activity based on the BYOD concept, which is based on the priority of using students’ personal mobile devices, are proposed. he perspective of further research in the development of the methodology for the introduction of BYOD technologies and the development of a system for the formation of research skills based on the principles of STEM physics education is determined. He perspective of further research in the development of the methodology for the introduction of BYOD technologies and the development of a system for the formation of research skills based on the principles of STEM physics education is determined.
Developing Web-Based Point of Sales Application with SHA-512 Encryption on DBMS for Indonesian MSME’s Culinary Industry

Efficiency and effectiveness are crucial in the food &amp; beverage industry. Conventional methods employed by companies often lead to discrepancies between actual stock and the stock available for sale, resulting in significant losses. To address this issue, a point-of-sales-based system has been implemented, enabling companies to monitor transaction activities seamlessly. The research utilized the RAD (Rapid Application Development) method to develop a concise and fast software application. Furthermore, hashing and encryption methods have been incorporated to enhance database security, utilizing the SHA-512 algorithm for hashing and data encryption. This research has yielded a point-of-sales website-based application that supports various business processes. The website has been tailored to meet the specific requirements outlined by the company owner. The UAT test results have demonstrated that the application encompasses
Modified Genetic Algorithm and Association Rule Mining for the Retail Sector

This paper concentrates on the optimization of elementary association rule mining. The basic approach of association rule mining generates the positive association rule but focusing on both positive and negative association rule mining to find out efficient results is lacking. Thus our aim is to provide an approach to optimize all positive and negative association rules with the help of a modified genetic algorithm. A genetic algorithm is an optimization technique that provides the best possible solutions that are stronger than the other solutions. The present approach focuses on the importance of population through mean fitness value for further genetic algorithm operation. This paper also shows a comparison between normal Apriori, the Genetic Algorithm, and our proposed algorithm. Where in as a result the proposed approach worked better than others. We believe that the proposed methodology would increase the efficiency of the Decision support system of retail stores.
IoT and Edge Computing Technologies as Security Option for Train Service in Nigeria

The revival of rail transport service in Nigeria in recent years came at a critical moment of insecurity in Nigeria, it promised not only to serve as an alternative to overloaded vehicles on the roads but was also thought to be a safer means of transportation. Due to kidnapping on many roads, both high and low-class Nigerians patronized rail transport. However, train attacks and terrorism are major challenges that have impacted the sector negatively. Though the government has tried to improve surveillance along train routes, however, the result has not been impressive. The current level of insecurity in Nigeria is beyond the use of traditional surveillance and monitoring systems. It requires the adoption of technology to fight attacks and to monitor the health of train facilities. While the insecurity challenges that have overwhelmed the security forces will not permit the assignment of more personnel to the rail tracks that stretch several kilometres across the country, the incorporation of IoT and edge computing can be an optimal solution to the challenges of constant security problems. Among the trending technologies, IoT is a viable option that the country can adopt to improve security in the sector. It will increase the confidence of passengers and improve revenue and growth in rail transport.
Cartographic representation of the efficiency of distribution of primary education services in Al-Maimuna District for the year 2021

The study research includes the representation of primary education services in the district of Al-Maimuna maps, and modern technologies have been used in the use of information and data in the preparation of maps with high accuracy in drawing, design and information as well as deduction, updating and analysis, the research has indicated that the total number of primary schools in the district of Al-Maimuna for the year 2021 ( 101 ) schools, the center of elimination ranked first with the largest number of schools and then the side of peace in second place while the area of Sayed Ahmed Rifai came in The third and last rank, and the research proved that the number of primary schools is not commensurate with the number of students in the judiciary according to the global standard for the number of students in one class, through this study it was concluded that the district of Maimuna needs (13) schools for the purpose of achieving the ideal number of schools.
Metric and Pitch Tension in Gustav Holst's "Mars, the Bringer of War"

Abstract: Although authors recognize the war-like nature of rhythm and meter in "Mars," their observations are mostly superficial. For example, Richard Greene briefly suggests the 5/4 ostinato is a metaphor for battle, but he does not detail the extent of this metaphor. Michael Short prescribes the persistent 5/4 meter as the movement's "most striking feature" and briefly mentions the hemiola created by the superposition of 5/2 over two bars of 5/4, but he does not detail the metric features of "Mars" any further. Dickinson and Gibbs claim the quintuple meter "precludes a dull monotony and makes a firm basis for theme and counter-theme." They point to musical features that deserve more attention, including "twisting trochees, trumpeted declamation, and uneven bar-rhythm."
End-PolarT: Polar Representation for End-to-End Scene Text Detection

Deep learning has achieved great success in text detection, where recent methods adopt inspirations from segmentation to detect scene texts. However, most segmentation based methods have high computation cost in pixel-level classification and post refinements. Moreover, they still faces challenges like arbitrary directions, curved texts, illumination and so on. Aim to improve detection accuracy and computation cost, we propose an end-to-end and single-stage method named as End-PolarT network by generating contour points in polar coordinates for text detection. End-PolarT not only regress locations of contour points instead of pixels to relieve high computation cost, but also fits with intrinsic characteristics of text instances by centers and contours to suppress mislabeling boundary pixels. To cope with polar representation, we further propose polar IoU and centerness as key parts of loss functions to generate effective paradigms for text detection. Compared with the existing methods, End-PolarT achieves superior results by testing on several public datasets, thus keeping balance between efficiency and effectiveness in complicated scenes.
ACTUALIZATION NATIONAL-PATRIOTIC EDUCATION IN THE SYSTEM OF PEDAGOGICAL PROFESSIONAL PRE-UNIVERSITY EDUCATION: MANAGEMENT ASPECT

International scientific conference «Modern strategies of sustainable development of the state and society in the context of global challenges (August 2–3, 2023 Wloclawek, the Republic of Poland)». Riga, Latvia : «Baltija Publishing», 2023. 44 pages.
Tests of difference: more than two samples

This chapter explores tests of differences on two or more samples of unrelated data, particularly the parametric one-way Anova and the nonparametric Kruskal—Wallis test. Neither test works if the data in the samples are measured at a nominal level, but the Kruskal—Wallis test can cope with ordinal data. Both tests work with scale data. The independent variable can technically be measured at any level, provided it can be used to distinguish a small number of categories. The chapter then offers guidance on what sample sizes to use when planning to collect data for use in these tests, demonstrates how to perform each test by hand and with SPSS using real data sets, and illustrates how to identify and report the key results of both tests. It also differentiates between model I and model II Anovas.
Relationship between Predicate-Argument Structure and Emotionality in Text

&#x0D; &#x0D; &#x0D; Emotions, which are responses to salient events, can be realized in text implicitly, for instance with mere references to facts (e.g., “That was the beginning of a long war”). Interpreting affective meanings thus relies on the readers’ background knowledge, but that is hardly modeled in computational emotion analysis. Much work in the field is focused on the word level and treats individual lexical units as the fundamental emotion cues in written communication. We shift our attention to word relations. We leverage Frame Semantics, a prominent theory for the description of predicate-argument structures, which matches the study of emotions: frames build on a “semantics of understanding” whose assumptions rely precisely on people’s world knowledge. Our overarching question is whether and to what extent the events that are represented by frames possess an emotion meaning. To carry out a large corpus-based correspondence analysis, we automatically annotate texts with emotions as well as with FrameNet frames and roles, and we analyze the correlations between them. Our main finding is that substantial groups of frames have an emotional import. With an extensive qualitative analysis, we show that they capture several properties of emotions that are purported by theories from psychology. These observations boost insights on the two strands of research that we bring together: emotion analysis can profit from the event-based perspective of frame semantics; in return, frame semantics gains a better grip of its position vis-a`-vis emotions, an integral part of word meanings.&#x0D; &#x0D; &#x0D;
Unravelling Filter Bubbles in Recommender Systems: A Comprehensive Review

The prevalence of filter bubbles in recommender systems has raised concerns about the potential impact on user experiences and information exposure. This systematic literature review aims to deliver a thorough analysis for the study conducted on filter bubbles in recommender systems and its implications for user experiences and information exposure. Through a thorough bibliometric analysis using VOSViewer, the research landscape is mapped, influential authors are identified, and recurring themes are examined. The review delves into theoretical frameworks, empirical studies, and algorithmic approaches to highlight the challenges and opportunities associated with detecting and mitigating filter bubbles. Key findings encompass the identification of filter bubbles, their impact on user behavior, and proposed solutions. Additionally, an analysis of datasets used in this context is presented, alongside notable solutions developed to address filter bubbles in recommender systems. The review investigates the unresolved obstacles in the domain of filter bubbles within recommender systems. The review also explores potential future directions and solutions to mitigate filter bubbles, underscoring the significance of understanding their implications for user decision-making and information diversity. By contributing to the ongoing discourse on recommendation systems, this research offers valuable insights to researchers, practitioners, and policymakers seeking to address the filter bubble phenomenon and enhance user experiences in the realm of recommender systems.
Data Analysis Method for Recognition of AI Education Based on Education Data

Based on the 4th Industrial Revolution, AI Education, which is closely related to Software Education, has begun to grow up into an important sector for core competencies of the future. Nevertheless, the significance of AI Education does not make up a great portion of diverse academic fields, and even the general public, teachers, and learners do not recognize its weight. Therefore, this study is to analyze reputation and recognition levels based on Unstructured Data mentioned online regarding AI Education and to present a methodology to seek development directions in the AI Education sector in the medium and long term. It is anticipated to contribute to the establishment of effective policies for future education and talent training, based on the general recognition of AI Education, in preparing for the 4th Industrial Revolution.
Determinants of Technological Innovation Adoption and Banking Operations of Some Selected Commercial Banks in Somalia

It's amazing to see how technology is transforming the financial industry. From accounting to management, technology has revolutionized all aspects of banking, and customers are benefiting from better and more streamlined services. The aim of this study is to explore the impact of technological innovations on the operations of commercial banks in Somalia. Through a cross-sectional survey of licensed bank employees, this study investigates the relationships between perceived ease of use, compatibility, and IT infrastructure in shaping banking operations. Employing the Yaro Yamane formula, a sample size of 196 was determined for the survey. Data was analyzed using SPSS and SmartPLS, revealing that IT infrastructure and perceived ease of use have a significantly positive influence on banking operations, while compatibility had insignificant relations with banking operations. These findings align with previous research, indicating that advanced technology enhances customer experience, interconnects banking systems, improves efficiency, and fortifies security measures. This study recommends collaborative efforts between the Somali government and the Central Bank to enhance security measures and combat fraud in electronic banking, thereby fostering investor confidence and facilitating economic growth. The research contributes to the ongoing transformation of the Somali banking sector through insightful determinants of technological innovation adoption.
A Systematic Review on Natural Language Processing and Machine Learning Approaches to Improve Requirements Specification in Software Requirements Engineering

This systematic literature review (SLR) examines the current practices, challenges, proposed solutions, and limitations of natural language processing (NLP) and machine learning (ML) approaches in improving requirements specification in software requirements engineering. The review focuses on research conducted in the last five years and includes a selection of papers that discuss the use of NLP and ML techniques for enhancing the accuracy and clarity of requirements, particularly in the context of functional and non-functional requirements. The findings highlight the benefits and challenges associated with the integration of NLP and ML approaches, such as improved classification and identification of requirements. However, it is observed that there is a greater emphasis on non-functional requirements, with a limited representation of research on functional requirements. Comparison of this review and the recent two reviews has been done to observe the differences and highlight the novelty and contribution. The review also identifies limitations, potential bias in assuming that problems related to requirements documentation or specification can be easily resolved through simple changes as well as the need to address the functional requirements. The insights from this SLR contribute to the understanding of the current state of research in this field and provide a foundation for future research directions and practical applications in leveraging NLP and ML approaches to enhance requirements specification in software requirements engineering.