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Item Open Access EQUITY IN ACCESS TO KAZAKHSTANI HIGHER EDUCATION(СДУ хабаршысы - 2019, 2019) Yenikeyeva A.Abstract. The purpose of this study, which is conducted using document analysis and primary data collectionin order to understand the policy and problems of access and equity in Kazakhstani higher education in terms of financial issues. The absence of adequate financial support is the most major obstacle to accessing the education in Kazakhstan. At the same time higher education instituions are not allowed to raise funds and help students with decreasing the fees.In addition to inequity, the high-income cities of Almaty and Astana usually achieve the highest scores on the UNT. Thus means citizens from reacher parts of Kazakhstan have more access to grants issued by government than poorer regions. The main answer of the question who pays and who should pay for higher education in Kazakhstan is revealed.The aim of this study, which is conducted using document analysis is to understand the policy and problems of access and equity in Kazakhstani higher education in terms of financial issues and unified national test (UNT) which is used to make access more transparent and fair. The absence of adequate financial support is the most major obstacle to accessing the education in Kazakhstan. At the same time higher education instituions are not allowed to raise funds and help students with decreasing the fees.In addition to inequity, the high-income cities of Almaty and Astana usually achieve the highest scores on the UNT. Thus means citizens from reacher parts of Kazakhstan have more access to grants issued by government than poorer regions. Future researches may be divided by financing polices and access to higher education by UNT. Identification the affect of improved version of UNT on access and equity in higher education.Item Open Access Solution of differential equations with vertical asymptotes(Suleyman Demirel University, 2011) Uxikbayev K.B.This article investigates the kernel of the inverse operator associated with the third-order differential operator defined by Ly = −y'' + q(x)y under periodic-type boundary conditions. Using Kolmogorov widths and s-number theory, we establish estimates for the operator’s properties and demonstrate that the inverse operator is a kernel operator when q(x) is continuous and satisfies q(x) ≥ 1. Several supporting lemmas are proven, including inequalities for the operator and relationships between s-numbers and Kolmogorov widths. The results provide a theoretical framework for understanding the behavior of higher-order differential operators in Hilbert and Banach spaces.Item Open Access Some properties of ordered algebraic structures(Faculty of engineering and natural sciences, 2019) Dauletiyarova A.Quantifier elimination is one of the most important tools in model theory. Indeed, if a theory allows quantifier elimination, then this theory is complete, and the description of all definable subsets can be reduced to describing only those subsets that are defined by a quantifier-free formula. One of the most important mathematical structures is the linearly ordered set of real numbers. On it, you can set an ordered group and field. It is known that the elementary theory of these structures admits quantifier elimination, and since these theories are computably axiomatizable, quantifier elimination implies their solvability.Item Open Access USING THE GINI COEFFICIENT TO BUILD A CREDIT SCORING MODEL(СДУ хабаршысы - 2021, 2021) Sultanova N. ; Tulegenova A. ; Suleimen B.Abstract. The credit scoring model is widely used to predict the likelihood of a customer default. To measure the quality of such scoring models, you can use quantitative indicators such as the GINI index, KolmogorovSmirnov (KS) statistics, Lift, Mahalanobis distance, information statistics. This article discusses and illustrates the practical use of the GINI index.Item Open Access ARTIFICIAL AI IN TEST AUTOMATION: SOFTWARE TESTING OPPORTUNITIES WITH OPENAI TECHNOLOGY - CHATGPT(СДУ хабаршысы - 2023, 2023) Talasbek A.Abstract. One of the most important and significant stages of the software development life cycle is software testing. Automated testing reduces testing costs and increases productivity, resulting in a high-quality and stable end product. To ensure that software is bug-free and delivers the desired user experience, test automation is critical. As technology advances, test automation becomes more complex. However, advanced Al technologies will soon become commonplace thanks to powerful tools like ChatGPT that, among countless other things, can chat with you and teach you how to read and write code like a human. In this article, we will try to consider the possibilities of automation with chatgpt. Starting with writing test plans, and test scripts by using Python and Selenium WebDriver. How ChatGPT can improve our tasks and make them more feasible. By leveraging the capabilities of ChatGPT, software testing engineers can enhance their skills, improve testing capabilities, and achieve better quality and accuracy of test results. The opportunities presented by ChatGPT can lead to improved efficiency, productivity, and overall performance in the field of software testing engineering.Item Open Access COMPARATIVE ANALYSIS OF SORTING ALGORITHMS USED IN COMPETITIVE PROGRAMMING(СДУ хабаршысы - 2021, 2021) Mamatnabiyev Zh. ; Zhaparov M.Abstract. Sorting is one of the most used and fundamental operation in computer science since the first time it had been tried to arrange list of items in some sequence. A large number of sorting algorithms were designed in order to have best performance in terms of computational complexity, memory usage, stability, and methods. In addition, in algorithmic problem solving, not all algorithms have same efficiency. This paper makes comparison research and discusses four different types of sorting algorithms: bubble sort, quick sort, insertion sort, and merge sort. The algorithms are tested and compared for data usage and time spent for sorting given amount of data.Item Embargo The Art of Personalized Student-Supervisor Matchings(ADAL Kitap, 2025) Serek A.G.; Berlikozha B.A.The process of student-supervisor matching is a critical yet complex task in higher education institutions, directly influencing research productivity, student satisfaction, and workload distribution. The ability to assign students to the most suitable supervisors is essential for fostering strong academic relationships, optimizing institutional resources, and improving research outcomes. However, traditional manual assignment methods often lead to inefficiencies, subjective biases, and an imbalance in workload distribution. As a result, automated recommendation systems have emerged as a promising solution to enhance the efficiency and fairness of student-supervisor pairings. This study evaluates three recommendation algorithms—Singular Value Decomposition (SVD)-based collaborative filtering, graph-based matching using the Hungarian Algorithm, and machine learning via Random Forest Regression—to determine their effectiveness in optimizing student-supervisor assignments. A rigorous empirical analysis is conducted across five key performance metrics: accuracy, fairness, stability, scalability, and computational efficiency. The findings reveal that while collaborative filtering performs well with established datasets, it struggles with novel cases due to its dependence on prior interactions. The Hungarian Algorithm guarantees optimal matching but faces scalability challenges, particularly in large academic institutions with thousands of students and supervisors. Meanwhile, Random Forest Regression effectively captures complex compatibility patterns but requires extensive labeled data, limiting its applicability in cases where historical matching data is sparse or unavailable. To overcome these limitations, the study proposes an adaptive hybrid framework that integrates the strengths of all three approaches. The hybrid model leverages collaborative filtering’s ability to recognize patterns in existing data, the Hungarian Algorithm’s precision in optimal pairings, and the predictive power of machine learning. By combining these methodologies, the proposed system enhances match accuracy, ensures fair workload distribution, and remains computationally efficient for large-scale institutional implementation. Additionally, the framework introduces dynamic adaptation mechanisms that allow the system to update recommendations based on real-time changes in student preferences and supervisor availability, making it more practical for real-world applications. The research contribution is a comprehensive, empirically validated hybrid framework that improves student-supervisor matching by balancing accuracy, fairness, and efficiency. This study provides educational institutions with actionable guidelines for scalable and equitable assignment processes, ultimately contributing to more effective mentorship experiences, improved research collaborations, and enhanced academic outcomes.Item Open Access STUDY OF SQUARE EQUATIONS IN THE 8TH GRADE USING MODULAR TECHNOLOGY(СДУ хабаршысы - 2019, 2019) Sabyrbayeva D. ; Borambayeva S.Abstract. The article gives a description of one embodiment of the modular technology in teaching students math. The analysis of the requirements for learning outcomes, the study objectives and data integration capabilities in the process of the study. Just a list of tasks and issues for study in each of the lessons in both integrated classes, and the framework of the modular study. The question of the use and visualization tools as well as the combination on of this material and other items.Item Open Access IMPLEMENTING COURSE SCHEDULE GENERATION APPLICATION FOR UNIVERSITY(СДУ хабаршысы - 2021, 2021) Zhuniskhanov M. ; Suliyev R.Abstract. This work is about researching and implementing Course Schedule Generation Application for university. She compares other similar applications in this area and explores important points. Through UML diagrams, important concepts and development progress are explained. Screenshots of using the application will also be provided. Dataset, configuration and rules explained. In the end, we will talk about the importance of such an application and facilitate planning for the university.Item Open Access HANDWRITTEN OPTICAL CHARACTER RECOGNITION: IMPLEMENTATION FOR KAZAKH LANGUAGE(СДУ хабаршысы - 2021, 2021) Kalken M.Abstract. Many documents, including as invoices, taxes, memoranda, and surveys, historical data, and test replies, still require handwriting with the transformation to digital information interchange. Handwritten text recognition (HTR), which is an automatic approach to decode records using a computer, is required in this aspect. For this proposal, I present a study of the implementation of optical recognition algorithms for handwritten text in the Kazakh language, using a recently collected database. The database, called the Kazakh Autonomous Handwritten Text Dataset (KOHTD), contains more than 140,335 segmented images of handwritten exam papers. As an algorithm, I used the proposed model by Harald Scheidl, which consists of several layers of neural networks and an CTC decoder. The trained model by putting an interval of Ir = 0.01 and a batch size of 60 showed effective results with indicators of about 85% accuracy.