A STRUCTURAL MODEL FOR BUILDING A SYSTEM FOR THE DEVELOPMENT OF METHODOLOGICAL COMPETENCE AND METHODS FOR EVALUATING ITS EFFECTIVENESS

paper develops a structural model for building a system for developing methodological competence. The structural model is built based on a service-oriented approach to developing large software complexes and includes six subsystems. Each subsystem is implemented as a separate microservice, which allows system scaling. The paper describes a technique that allows you to build a teacher’s competency map and evaluate its eight components: cognitive, didactic, project, informational, communication, reflective, monitoring, and personal-motivational. A four-level scale is proposed for assessing the level of competencies. A methodology for evaluating the effectiveness of the methodical competence development system based on the hierarchical expert method has been developed. The system was verified and implemented. According to the results of the system implementation, the intensification of the educational process and the improvement of the training quality of students were recorded. Students’ success in studying subjects has increased significantly. Namely, the number of bad students has decreased by 15 %, the number of «excellent» students has increased by 10 %, and the number of «good» students has increased by 18 %. The paper touches upon creating information technologies adequate for improving the higher education system. The goal is the targeted development and implementation of information technologies in educational institutions and the creation and operation of integrated, flexible software to support a mixed system for organizing the educational process, as well as increasing the efficiency of implementing a mixed system for organizing the educational process


Mariia Nastenko
Vinnytsia National Technical University, Vinnytsya, Ukraine ORCID: https://orcid.org/0000-0001-6311-6850 The efficiency of work of a large part of the motor transport enterprises of Ukraine is unsatisfactory.For the most part, this situation is associated with significant wear and tear of the fixed assets of enterprises, both rolling stock and the production and technical base.One of the ways to solve this problem is technical development.
Under modern conditions, technical development requires a systemic approach, which involves a comprehensive renewal of rolling stock and the production and technical base, taking into account all the interrelationships between these subsystems.To solve this problem,  The object of this research is a combinatorial optimization problem arising in the problem of the route of goods delivery vehicles.
In this study, the proposed method for solving combinatorial opti- Yurii Kosovtsov Scientific Center of the Ground Forces, Lviv, Ukraine ORCID: https://orcid.org/0000-0001-8047-1424 The object of this study is the process of determining the optimal strategy for choosing a certain element of the grouping to perform a certain task.
The problem solved was the contradiction between the need to take into account various types of adverse conditions when determining the optimal strategy for assigning a certain type of forces and means for a certain task to the existing approach to maximizing the result.
The improved scientific and methodical apparatus includes optimal selection criteria and an improved procedure for optimal selection of a certain grouping element.
Existing approaches to the selection of optimal strategies for assigning forces and means to perform tasks were analyzed, in particular the criteria of Wald, Hurwitz, and Savage.
The peculiarity of this analysis is the examination of the criteria in view of the types of adverse conditions they take into account.The application of these criteria will make it possible to take into account the conditions of uncertainty of the input data and minimize the influence of adverse conditions during distribution.
The field of practical use of the analysis results is management processes during preparation for the operation.
A procedure of optimal selection of a certain element of the grouping for the performance of a certain task has been improved by using several criteria for choosing the optimal strategy and harmonizing the results of this selection in accordance with the conditions.
The proposed procedure guarantees the performance of tasks, and the increase in the value of the objective function can reach 40 %.
A feature of the proposed procedure is that the result of choosing the optimal strategy is determined according to the conditions of a certain operation and takes into account various types of adverse conditions.This makes it possible to take into account the factors that significantly affect the uncertainty and minimize the expenditure of resources when performing a certain set of combat tasks.
The scope of practical use of the methodology is the process of planning and allocation of forces and means among tasks in the operation.The possibility of using the results obtained from the identification to increase the clinics' efficiency in making decisions is shown.

Keywords
The results obtained in this study can be used to improve the clinics' performance according to public opinion.This opportunity involves the crowdsourcing of opinions about the clinic in the medical social media environment and the collection of opinions in a structured way.
Keywords: medical social media, decision-making, patient opinions, clinic activity, sentiment analysis.
The technology of processing clothing elements is very mobile and changes with the appearance of new materials and equipment.

18 .DOI
Zhuldybayeva, G. Zh. (2019).Professional development of teachers in the context of modernization of education.Bulletin of KazNU named after Al-Farabi: Pedagogical series, 2 (81), 68-71.19.Zhambulova, S. K. (2017).Formation of methodological competence of university teachers in the process of professional training.Bulletin of the M. Auezov South Kazakhstan State University, 2, 122-126.20.Nurhalieva, D., Omirbaev, S., Turebekova, B., Bopiyeva, Z. (2017).Process approach in results-oriented public administration.Journal of Advanced Research in Law and Economics, 8 (3), 950-955.Available at: https://journals.aserspublishing.eu/jarle/article/view/1474University, Vinnytsya, Ukraine ORCID: https://orcid.org/0000-0002-6878-7183 model of technical development of motor vehicle enterprises was developed in the work, which allows to identify promising strategies, and for their implementation to form and research technical development projects.To select the optimal technical development project, the objective function is substantiated in the work, which includes a technical indicator -the technical readiness ratio and economic indicators -net present value and the payback period of the project.The selection of the optimal project is proposed to be carried out on the basis of the «worst case method».Using this me thod, the weighting coefficients of the objective function criteria were determined, which corresponded to: for the coefficient of technical readiness -0.333, for the net present value -0.556, for the payback period -0.111.Based on the developed models and algorithms, strategies were determined and technical development projects of the Vinnytsia branch of the private enterprise «Avtotranskom» were developed.Based on the developed objective function and the «worst case method» the optimal technical development project among the developed ones was determined.Implementation of this project allows to increase the technical level, work efficiency and competitiveness of the enterprise.Keywords: technical development, rolling stock, production and technical base, technical operation of cars, commercial operation of cars, strategy of technical development, complex motor vehicle enterprise, decision-making, technical readiness, efficiency of use of rolling stock.
mization problems consists of several stages: Data Cleaning, Data Preprocessing, K-NN and Cavacity Vehicle Routing Problem model.The results show that the machine learning approach can optimise combinatorial optimization problems, especially in generating vehi-cle route points and delivery capacity.The characteristics in determining vehicle routes by considering latitude and longitude points.This research builds a framework and implements it in a multi-class optimization model to reduce overfitting and misclassification results caused by unbalanced multiclassification from the influence of the number of 'nodes' on vehicle routes with machine learning.The purpose of the model in general is to gain an understanding of the mechanism in the problem so that it can classify unbalanced vehicle route data based on Jalur Nugraha Ekakurir delivery routes.So that with the availability of the model can be a model in determining vehicle routes based on the capacity limit of the number of shipments of goods.The results of research with machine learning models and vehicle routing problems with testing K values 11, 13, 15.Where it has a percentage of K = 11 accuracy 57.3265 % and K = 13 accuracy 57.3265 % and K = 15 accuracy 81.8645 %.From the test results with odd K values have better accuracy and the K 15 K = 15 value is better with a percentage of 81.8645 % compared to K 11 K = 11, and 13 K = 13.As a result, the developed model in terms of accuracy of the cavacity vehicle routing problem model has an accuracy of 93.80 % and the time series achieves an average precision of 93.31 % and with a recall value of 93.80 %.The results obtained can be useful in developing a more modern model, Cavacity Vehicle Routing Problem with Machine Learning.Keywords: vehicle routing problem, machine learning, classification, unbalanced data.Aviation, Almaty, Republic of Kazakhstan ORCID: https://orcid.org/0000-0002-7339-4907The problem solved in the research is to increase the efficiency of decision making in the tasks of professional training of pilots while ensuring the specified reliability, regardless of the hierarchy of the system of evaluation indicators.The object of the research is the professional training system for civil aviation pilots.The subject of the research is the process of assessing the qualities of civil aviation pilots using fuzzy cognitive maps.The hypothesis of the research is to increase the number of indicators for assessing the quality of training of civil aviation pilots with restrictions on the efficiency and reliability of decision making.A method has been developed for assessing the preparedness of aviation personnel involved in ensuring flight safety.The method consists of the following sequence of actions: -input of initial data; -standardization of numerical values of concepts of a fuzzy cognitive model of preparedness of aviation personnel involved in ensuring flight safety; -transition of numerical values of concepts of a fuzzy cognitive model of preparedness of aviation personnel involved in ensuring flight safety; -building a fuzzy cognitive model; -determination of quantitative estimates (ranks) of the importance of model elements; -calculation of importance indices of model elements.Based on the results of the analysis of the effectiveness of the proposed method, it is clear that the proposed assessment method increases the accuracy of the assessment of aviation personnel involved in ensuring flight safety by 23 % compared to the known 107 Abstract and References.Control processes ones.It is advisable to use the developed method in decision making support systems for assessing the quality of professional training of aviation personnel in order to increase the efficiency and reliability of decisions made.Keywords: flight safety, preparation, stress resistance, aviation personnel, civil aviation, psychophysiological state.

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optimal strategy, Wald criterion, Hurwitz criterion, Savage criterion, combat tasks.Technology, Baku, Azerbaijan ORCID: https://orcid.org/0000-0002-2205-1023Zarifa Jabrayilova Institute of Information Technology, Baku, Azerbaijan ORCID: https://orcid.org/0000-0002-9661-5805Nargiz Shikhaliyeva Institute of Information Technology, Baku, Azerbaijan ORCID: https://orcid.org/0000-0002-5427-0765The object of the study is the decision-making modeling in the context of medical social media to increase the clinics' effectiveness.The problem is to classify the patient reviews collected in the patient-clinic segment of the medical social media and to identify the situation related to the clinics' activity by revealing the criteria characterizing the clinics' activity out of the opinions.The proposed technique refers to lexicon-based sentiment analysis of opinions, the classification based on Valence Aware Dictionary and Sentiment Reasoner (VADER), the verification of the results accuracy with Multinomial Naive Bayes and Support Vector Machine, the manual sentiment analysis of opinions to detect criteria and the classification of opinions according to each criterion.Using this technique, out of 442587 patient reviews obtained from database cms_hospital_satisfaction_2020 of the Kaggle company generated on the basis of crowdsourcing of patient reviews on medical social media, 218914 patient reviews are classified as positive, 190360 -as neutral, and 33313 -as negative.The results accuracy is verified, and the clinics are rated by the «positive» opinions.6 new criteria characterizing the clinics' activity are discovered, and the identification of the situation related to the clinics' activity based on the comparison of «positive» and «negative» opinions according to each criterion is presented.

DOI: 10.15587/1729-4061.2023.289470 MATHEMATICAL MODEL OF A RAILROAD GRAIN CARGO RIDESHARING SERVICE IN THE FORM OF COALITIONS IN CONGESTION GAMES (р. 35-48)
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