Reviewerly/exHarmony huggingface dataset:
Quality management in educational organizations: transformation of the environment and features of the formation of local quality management systems

Methods. Scientific results are obtained through the use of such methods as description, abstraction and induction. With the help of the method of description, aspects of the evolution of quality management in the educational organization were revealed, in particular, attention was focused on the experience of higher education institutions in Poland, the Czech Republic, and Germany. With the help of the abstraction method, certain aspects of quality management in higher education institutions of Ukraine were singled out and a list of actions was proposed that will contribute to the optimization of certain processes within the framework of ISO 9001:2015. When applying the induction method, the authors made conclusions regarding the possibilities of significant optimization and improvement of the quality management system in higher education institutions of Ukraine. Results. The article investigates and analyzes the features and aspects of the functioning of the quality management system in institutions of higher education, proposes certain elements for implementation in the system of higher education that will contribute to the optimization and improvement of the functioning of processes within the framework of ISO 9001:2015. Novelty. This study revealed and demonstrated that within the framework of the higher education system of Ukraine there are certain characteristics that in one way or another negatively affect the functioning of the educational processes of higher education institutions of Ukraine. Therefore, we have created and proposed methods that can improve and optimize processes in higher education institutions. Practical value. This study can be important and useful for the management of higher education institutions in building an effective quality management system in higher education institutions, which can lead to higher education standards and, as a result, satisfaction of all interested parties.
A Method for Training Object Scale Estimation System using Feature Extraction Enhancement with Depth Estimation

In recent years, machine learning-based object scale estimation has been growing in popularity, as the significance of the technology lies in its potential for use in many industry fields. Although several methods have been proposed, the possible applications of this technique are limited due to its insufficient accuracy. Hence, a human-level accurate system is needed for the technology to be applied in the real-world domain. This research paper proposes a novel object scale estimation system that incorporates the feature extractor, disentangled feature maps, depth estimator, object localizer, and ground truth depth map. The input of the proposed system is an image, which is inputted into the feature extractor to create disentangled feature maps. These feature maps are then extracted by the depth estimator to generate a depth map, and by the object localizer to create a predicted bounding box around the object. The trained feature extractor can extract disentangled size-related features from the inputted image by jointly training the depth estimator and object localizer. The use of disentangled features boosts the performance of the proposed system. In addition, we propose an actual scale converter module to calculate the actual size of the inputted object. Throughout the experiments, the proposed method has proven that it is superior compared to other state-of-the-art methods. The proposed method achieves an IoU (Intersection over Union) value of 0.8113 on the COCO dataset.&#x0D;
Relevance of the use of artificial intelligence in modern conditions of the educational process

The implementation of artificial intelligence in education, especially within the field of medicine, is of paramount significance, and this article explores the transformative impact of artificial intelligence on the educational process and the future of medical professionals. This analysis delves into how artificial intelligence technology is revolutionizing learning methods and aiding aspiring doctors in acquiring new skills and knowledge. The article commences with an overview of the current challenges facing medical education, highlighting the pressing need for curriculum updates and innovative teaching methods. These challenges include keeping pace with the rapid advancements in the medical field, ensuring students are adequately prepared for real-world clinical scenarios, and providing access to a diverse range of educational resources. One of the key areas where artificial intelligence plays a crucial role is in providing virtual laboratories and simulation models. These technologies offer a safe and controlled environment for medical students to practice procedures and explore complex clinical situations. Through artificial intelligence-driven simulations, students can refine their diagnostic and problem-solving skills, all while minimizing risks associated with live patient interactions. Personalized learning is another vital component of artificial intelligence in medical education. artificial intelligence algorithms analyze the progress and learning preferences of each student, tailoring the educational content to their individual needs. Moreover, the authors discuss the potential for collaboration between artificial intelligence systems and human medical educators. This partnership can leverage the strengths of both artificial intelligence-driven technologies and the expertise of experienced teachers. In this way, students can benefit from the best of both worlds, ensuring a well-rounded education that combines the efficiency of artificial intelligence with the wisdom and guidance of skilled instructors.
Evaluasi Pengalaman Pengguna Aplikasi Hiip Indonesia Menggunakan Metode USE Questionnaire dan Usability Testing

With the rapid development of mobile applications, user experience has become crucial in ensuring success and user satisfaction. This research paper presents an evaluation of the user experience of the Hiip Indonesia application, with a focus on usability assessment and user satisfaction. The research methodology employs two main methods: the USE Questionnaire and Usability Testing. The USE Questionnaire is a validated and widely used tool for assessing user satisfaction, while Usability Testing involves observing user interactions with the application and collecting qualitative and quantitative data. The research findings indicate that the usability level of the Hiip Indonesia application falls into the "acceptable" category, with a total feasibility percentage of 73.91%. The hypothesis testing shows a significant influence on satisfaction between the variables of usefulness, ease of use, and ease of learning. However, on a partial level, only the variables of usefulness and ease of use significantly influence satisfaction. In contrast, the ease of learning variable does not have a considerable impact. Furthermore, the user experience evaluation data through task scenario testing indicates that the Hiip Indonesia application is highly effective to use, with a task completion success rate of 100% and an average task completion time of approximately 46.77 seconds. After reviewing the identified issues, recommendations for improvements to the Hiip Indonesia application have been formulated. Some of these recommendations include adding features to the "campaign" menu, adding a menu to the home screen, adding features to the "social media" menu, and adding features for chatting with administrators.&#x0D; &#x0D; Keywords: User experience, UX evaluation, USE Questionnaire, usability testing, mobile application, PT. Hiip Inovasi Indonesia.
Spatial geometric thinking and its articulation with the visualization and manipulation of objects in 3D

This paper aims to build a conceptual framework that addresses spatial geometric thinking and the respective visualization skills required at different levels of the schooling process. Studies indicate that spatial geometric sills are essential for scientific thinking. It encompasses a set of cognitive processes through which humans can construct and manipulate mental representations of objects in space and is a skill directed towards understanding objects and their relations in the 2D and 3D worlds. The use of these spatial reasoning skills involves drawing, manipulating, and explaining objects and their relationships and should be developed from the first years of schooling. Based on this theoretical context, partial research results on surface representations that can be manipulated in three dimensions (3D) and obtained through GeoGebra will be presented in this paper. The underlying theory was Duval's Theory of Registers of Semiotic Representation, which allowed the analysis of activities developed by graduate students in Mathematics Education by observing and physically manipulating such representations to obtain the respective graphic and algebraic records. The conceptual framework constructed and presented in this article contributed to identifying other skills required in this study for the development of spatial geometric thinking.
Transforming Regulatory Reporting with AI/ML: Strategies for Compliance and Efficiency

In today's complex regulatory landscape, financial institutions face significant challenges in meeting reporting requirements while maintaining operational efficiency. This paper explores the transformative potential of Artificial Intelligence (AI) and Machine Learning (ML) technologies in enhancing regulatory reporting processes. By leveraging AI/ML, organizations can streamline data collection, analysis, and submission, leading to improved compliance and operational efficiency. This paper discusses key strategies for integrating AI/ML into regulatory reporting frameworks, including data standardization, predictive analytics, anomaly detection, and automation. Moreover, it examines the benefits, challenges, and best practices associated with implementing AI/ML solutions in regulatory reporting. Through real-world examples and case studies, this paper provides insights into how AI/ML technologies can revolutionize regulatory reporting practices, enabling financial institutions to navigate regulatory complexities effectively while optimizing resource utilization and decision-making processes.
Innovations in the personnel training of the highest professional qualifications for universities in the Republic of Kazakhstan

The contents of the article are the analysis results of scientific personnel training rate inthe Republic of Kazakhstan since 1991. Particularly, attention is paid to the following parameters: the rateof change in the supply of universities with teachers with scientific degrees in Russia and Kazakhstan; thedynamics of the number of doctoral students (including doctoral students in the profile and PhD doctors)and postgraduate students, indicators of their graduation quality; performance indicators of candidates’scientific activities of the candidate of sciences scientific degree. The analysis of the listed parameters wascarried out for 1991-2017 period. Indicators for a doctoral program are considered since the beginning ofits functioning in the Republic of Kazakhstan. In the analysis course there are conclusions reflecting thespecificity of trends in the indicators under consideration formulated. There are problems in the rate ofscientific personnel training are identified and there are measures on their solution proposed.
Effect of the HDD drilling mud on the environment

Horizontal Directional Drilling (HDD) is a trenchless method commonly used for laying various types of pipelines and cables. It is a common way of routing a technological line from one point to another by directional drilling under obstacles or in ecologically sensitive areas. The HDD can be used, for example, under rivers, roads or slopes where conventional excavation technologies would not be cost effective, reliable or may be environmentally invasive. One of the important elements influencing the success of horizontal directional drilling is a drilling fluid appropriately selected for the drilling conditions. The mentioned drilling fluid may, however, be a threat to the environment, therefore, in order to prevent it, it must be properly stored and disposed of.
DIJAGNOSTIKA STANjA VISOKONAPONSKIH PREKIDAČA NA BAZI ON-LINE MONITORINGA

High voltage circuit breakers are very important switchgear in the power system. They are the only ones that can interrupt fault currents, for that reason their proper monitoring and maintenance is very important. The results of monitoring high voltage circuit breakers used in this paper are: measuring insulation resistance, checking oil dielectric strength, vacuum degree or gas density SF6, checking position of contacts in open - closed state, checking contact stroke by recording space - time diagram, measuring coil current for switching on and off, measuring the start-up time of the drive mechanism and checking the number of operations and measuring the contact resistance. This paper presents an innovative algorithm for the application of autoencoder neural networks(ANN) and an algorithm for creating a health index. The application of the presented methods enables on-line diagnostics of high voltage circuit breakers and decision- making on their further maintenance, repair or replacement in real time.
THE PROJECT METHOD AND ITS USE IN THE UNIVERSITY WHEN TEACHING A FOREIGN LANGUAGE (ENGLISH)

The article discusses the theoretical foundations of using the design methodology in the educational process with an emphasis on the personality, interests, independence and characteristics of the student. This method is based on the development of the cognitive, creative ability of students, independent design of their educational path, on the development of critical thinking. Also, the projective method allows you to optimally solve many problems associated with the study of a foreign language. Here the authors try to reveal the relevance of the design methodology, the features and usefulness of this method in the study of foreign languages (English) and focus on the practical application of this methodology in higher education.
COMPUTER VISUALIZATION IN THE PROCESS OF TEACHING MATHEMATICS

This article is devoted to one of the urgent problems of our time, the problem of improving the quality of the process of teaching mathematics with the use of information technologies, the literature on their solution is studied, as well as practical work in this direction is considered. The tasks of using computer technologies in the learning process are outlined, emphasis is placed on the advantages of developing independent work of participants, illustrating concepts, objects of the mathematics course, accessible explanation of educational material, enhancing visibility, simultaneous connection to several sources of information. The possibilities of computer programs in teaching mathematics are considered and studied. The implementation of visualization in the classroom provides for the organization of lessons based on applications developed by the Math Learning Center (USA).
THE USE OF ELECTRONIC BOOKS IN EDUCATIONAL PROCESS

The article considers the issue of disclosing accessible, simple and convenient ways to improve the knowledge of students of secondary schools of the Kyrgyz Republic with the help of electronic textbooks. It is noted that self-improvement of knowledge allows students to enhance mental activity. In this case, students receive additional time for independent study of educational materials. The article focuses on the learning activity in which the student works without the participation of the teacher. In this case, the student needs additional time to study the educational material. In the case when a student does not understand this or that educational material, he can find the necessary information in an electronic textbook..
Microphone as a meaningful tool for the interviewer

The purpose of the article is to fill the gap in the professional information field.The scientific significance of the article is that for the first time in the theory of Kazakhstanijournalism, there have been analyzed all types of lavalier-type microphones and their accessories. Interms of research methods, there were used two main types of reviews such as systematic andnarrative. This provided the most complete picture. For instance, a systematization of existingknowledge about lavalier microphones and an evaluation of that knowledge. As a result of thestudy, seven categories of lapel microphones have been derived and the characteristics of each ofthem are briefly presented. The value of the work lies in summing the main points in a short andsimple way. The practical significance of the work’s results lies in the collection of informationnecessary for the daily work of a journalist on television or on the Internet. There were derived five"golden rules”, which a journalist must always apply for high-quality sound recording andaesthetic picture in the frame. Previously, there were no such reviews in the Kazakhstani scientificliterature, so this work contributes to the development of the domestic special literature.
GBI Treebanks as a Resource for New Applications

Global Bible Initiative (GBI) have developed Hebrew OT treebanks and Greek NT syntactic treebanks. The treebanks were first generated with a parser using computerized Hebrew and Greek grammars and then proofed verse by verse by Hebrew and Greek Scholars. All the corrections made by the scholars were kept as disambiguation data.&#x0D; The phrase structures in the trees have been used to build interlinears, concordances, and translation memories which operate not only on the word level, but on the phrase and clause levels as well. The syntactic relations (dependencies) in the trees have also been used to do smart search where we can find texts that are different in form but similar in meaning.&#x0D; Recently, we have also used the trees to improve the accuracy of automatic word alignment and explore tree-based interactive machine translation of the Bible. The auto aligner can be used to the Hebrew and Greek texts to translations in various languages. The interactive machine translation will speed up Bible translation without compromising quality by providing real time suggestions and checking.&#x0D; We have already contributed two sets of Greek trees to Creative Commons, the Nestle 1904 version and the SBLGNT version. We also have trees for NA27 and NA28, but we do not own the texts. The Hebrew OT treebank we developed was owned by the Groves Center. We are also capable of creating new treebanks with the parser, grammar, and disambiguation data we own if we are given a text that is morphologically tagged.
Tyndale STEPBible Data development for machine analysis and computational linguistics

The development of STEPBible.org by Tyndale House Cambridge, which aimed to provide study tools for the disadvantaged world, resulted in creating datasets which are useful for many other purposes. In particular, computational linguistics and other machine analysis can benefit from the more stringent and varied ways in which data has been refined and presented. Much of this data resulted from a project supported by ETEN to automatically tag Bibles to Greek and Hebrew. A public repository is gradually being populated with the results of this work.
Problem-oriented Corpus Annotation and the Hebrew Bible

In this contribution, I argue that the exegetical and stylistic study of the Hebrew Bible would benefit from the creation and storage of qualitative and quantitative annotations using problem-oriented corpus annotation (de Haan 1984). Within Biblical studies exegetes are used to static interfaces which allow them retrieve information, but not enhance it with anything more elaborate than user notes. I present a roadmap for the development of an annotation tool tailored to the Hebrew Bible with the sole objective of enriching the data that is already present in open source datasets like that of the ETCBC. Based on my experience with a dataset to annotate conceptual metaphors in the book of Job (bibliametaphorica.com) and the literature on corpus annotation (Sinclair 2004; Leech 2005; Fort et al. 2012), I argue that data creation and enrichment is a challenging, yet rewarding endeavour. It is challenging because it is circular, viz. labels are informed by the data are hence difficult to a priori define. Furthermore, it is difficult to be consistent and the actual, manual labelling of the text requires interpretative choices that cause editorial fatigue. Fort et al. (2012) suggest that annotation campaigns have differing degrees of difficulty which can be mitigated not just by inter-annotator rating, but by conscious decisions to lower the annotation complexity. A user interface is needed that limits annotation complexity and that allows researchers to annotate the text with minimal effort. The end-result is an XML document, for instance, that contains both the text and the annotations, in a format that can be merged back into the original database, but need not be. The existence of a tool for the manual annotation of open data will increase the replicability of research as well as its democratisation, as students world-wide can create and share their data.
Unrestricted Original Language Resources

The unfoldingWord project exists in a new paradigm of Bible translation that has dual needs of access to content in Gateway Languages and the legal freedom to use, translate, and modify them to suit their context. The benefit of providing original language materials in the Gateway Languages is that it removes the barrier of needing to learn English to deepen one’s understanding of the text. This paper investigates whether or not restricted texts provide the legal freedom that Church-Centric Bible Translation (CCBT) needs, whether “All Rights Reserved”, Creative Commons NoDerivatives, or Creative Commons NonCommercial licenses. The only adequate public licenses for an original language resource to be translated are CC0, Creative Commons Attribution (CC BY), Creative Commons Attribution-ShareAlike (CC BY-SA), or possibly the Free Translate license.
KOMPARASI ALGORITMA KLASIFIKASI DATA MINING UNTUK MEMPREDIKSI TINGKAT KEMATIAN DINI KANKER DENGAN DATASET EARLY DEATH CANCER

Cancer is something big in the world. Cancer is a malignant disease that is difficult to cure if the spread is too wide. However, detecting cancer cells as early as possible can reduce the risk of death. This study aims to predict the level of early detection of disasters in European countries using 5 classification algorithms, namely: Desecion Tree, Naïve Bayes, k-Nearset Neighbor, Random Forest and Neural Network of which algorithm is the best for this study. Tests carried out with several stages of research include: dataset (data contains), initial data processing, proposed method, credit method using 10 times cross validation, test results and t-test different tests. The alpha value is 0.05. if the probability is&gt; 0.05 then H0 is accepted. If the probability is &lt;0.05 then Ho is rejected. The results of the research that obtained performance with an accuracy value of 98.35% were the Neural Network algorithm. Whereas, the results of the research using the algirtic t-test with the best models are: Random Forest algorithm and Neural Network, the relatively good Naïve Bayes algorithm, the Desecion Tree algorithm is quite good and the poor algorithm is the K-Nearset Neighbor (K-NN) algorithm.