Browsing by Author "Kadyrov Sh."
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Item Open Access 2D face recognition using PCA and triplet similarity embedding(Bulletin of Electrical Engineering and Informatics, 2023) Bazatbekov B.; Turan C.; Kadyrov Sh.; Aitimov A.The aim of this study is to propose a new robust face recognition algorithm by combining principal component analysis (PCA), Triplet Similarity Embedding based technique and Projection as a similarity metric at the different stages of the recognition processes. The main idea is to use PCA for feature extraction and dimensionality reduction, then train the triplet similarity embedding to accommodate changes in the facial poses, and finally use orthogonal projection as a similarity metric for classification. We use the open source ORL dataset to conduct the experiments to find the recognition rates of the proposed algorithm and compare them to the performance of one of the very well-known machine learning algorithms k-Nearest Neighbor classifier. Our experimental results show that the proposed model outperforms the kNN. Moreover, when the training set is smaller than the test set, the performance contribution of triplet similarity embedding during the learning phase becomes more visible compared to without it.Item Open Access A novel recommender system for adapting single machine problems to distributed systems within MapReduce(Bulletin of Electrical Engineering and Informatics, 2024) Orynbekova K.; Kadyrov Sh.; Bogdanchikov A.; Oktamov S.This research introduces a novel recommender system for adapting singlemachine problems to distributed systems within the MapReduce (MR) framework, integrating knowledge and text-based approaches. Categorizing common problems by five MR categories, the study develops and tests a tutorial with promising results. Expanding the dataset, machine learning models recommend solutions for distributed systems. Results demonstrate the logistic regression model's effectiveness, with a hybrid approach showing adaptability. The study contributes to advancing the adaptation of single-machine problems to distributed systems MR, presenting a novel framework for tailored recommendations, thereby enhancing scalability and efficiency in data processing workflows. Additionally, it fosters innovation in distributed computing paradigms.Item Open Access Application of ROC Curve Analysis for Predicting Students’ Passing Grade in a Course Based on Prerequisite Grades(MDPI Mathematics, 2022) Orynbassar A.; Sapazhanov Y.; Kadyrov Sh.; Lyublinskaya I.Determining prerequisite requirements is vital for successful curriculum development and student on-schedule completion of the course of study. This study adapts the Receiver Operating Characteristic (ROC) curve analysis to determine a threshold grade in a prerequisite course necessary for passing the next course in a sequence. This method was tested on a dataset of Calculus 1 and Calculus 2 grades of 164 undergraduate students majoring in mathematics at a private university in Kazakhstan. The results showed that while the currently used practice of setting prerequisite grade requirements is accurately identifying successful completions of Calculus 2, the ROC method is more accurate in identifying possible failures in Calculus 2. The findings also indicate that prior completion of Calculus 1 is positively associated with success in a Calculus 2 course. Thus, this study contributes to the field of mathematics education by providing a new data-driven methodology for determining the optimal threshold grade for mathematics prerequisite courses.Item Open Access Automated Reading Detection in an Online Exam(International Journal of Emerging Technologies in Learning (iJET), 2022) Bakhitzhan K.; Kadyrov Sh.; Makhmutova A.In this article we study a deep learning-based reading detection problem in an online exam proctoring. Pandemia-related restrictions and lockdowns lead many educational institutions to go online learning environment. It brought the exam integrity challenge to an online test-taking process. While various commercial exam proctoring solutions were developed, the online proctoring challenge is far from being fully addressed. This article is devoted to making a contribution to the exam proctoring system by proposing an automated test-taker reading detection method. To this end, we obtain our own dataset of short video clips that resemble a real online examination environment and different video augmentation methods utilized to increase the training dataset. Two different deep learning techniques are adapted for training. The experiments show quite satisfactory results with model accuracy varying from 98.46% to 100%. The findings of the article can help educational institutions to improve their online exam proctoring solutions, especially in language speaking tests.Item Open Access CANTOR SETS AND TOTAL SELF-SIMILARITY(ISCIENCE.IN.UA «Актуальные научные исследования в современном мире», 2025) Kadyrov Sh.; Keulimzhayev A.We study overlapping Cantor sets with parameter and classify the situations when these fractal sets are totally self-similar. More precisely, we consider iterated function system consisting of three functions , and and the fractal set it generates in the real line. We define what totally self-similar means and show for that the fractal set is totally self-similar if and only if it is in the form for some positive integer . We mainly rely on the recent work of Dajani, Kong, and Yao where they consider the analogous problem for .Item Open Access CORRELATION BETWEEN OIL PRICES AND CURRENCY EXCHANGE RATES.(СДУ хабаршысы - 2018, 2018) Abdimanapov D. ; Kadyrov Sh. ; Rozakhunova E.Abstract. In this article, we study how oil prices affect the USD vs. KZT exchange rates. Our methods base on elementary statistical data analysis. For this purpose, we collect Brent oil prices and US dollar exchange rates in Kazakh tenge for entire year of 2016, in a weekly basis. Our findings suggest that there is a strong correlation between two variables. Besides, we use simple linear regression analysis to provide a formula that predicts the USD rate given the oil price. To make the paper accessible to High school students, we keep most of the analysis as elementary as possible and self-contained.Item Open Access DEVELOPMENT AND OPTIMIZATION OF PHYSICS-INFORMED NEURAL NETWORKS FOR SOLVING PARTIAL DIFFERENTIAL EQUATIONS(Vol. 1 No. 1 (2025): Journal of Emerging Technologies and Computing (JETC), 2025) Sharimbayev B.; Kadyrov Sh.; Kavokin A.This work compares the advantages and limitations of the Finite Difference Method with Physics-Informed Neural Networks, showing where each can best be applied for different problem scenarios. Analysis on the L2 relative error based on one-dimensional and two-dimensional Poisson equations suggests that FDM gives far more accurate results with a relative error of 7.26 × 10-8 and 2.21 × 10-4 , respectively, in comparison with PINNs, with an error of 5.63 × 10-6 and 6.01 × 10-3 accordingly. Besides forward problems, PINN is realized also for forward-inverse problems which reflect its ability to predict source term after its sufficient training. Visualization of the solution underlines different methodologies adopted by FDM and PINNs, yielding useful insights into their performance and applicabilityItem Open Access Diophantine approximation with restricted numerators and denominators on semisimple groups(Journal de Théorie des Nombres de Bordeaux 29, 2017) Kadyrov Sh.; Gorodnik A.We consider the problem of Diophantine approximation on semisimple algebraic groups by rational points with restricted numerators and denominators and establish a quantitative approximation result for all real points in the group by rational points with a prescribed denominator and an almost prime numerator.Item Open Access DIOPHANTINE APPROXIMATION WITH RESTRICTED NUMERATORS AND DENOMINATORS ON SEMISIMPLE GROUPS(arXivLabs, 2014) Gorodnik A.; Kadyrov Sh.We consider the problem of Diophantine approximation on semisimple algebraic groups by rational points with restricted numerators and denominators and establish a quantitative approximation result for all real points in the group by rational points with a prescribed denominator and an almost prime numerator.Item Open Access EFFECTIVE EQUIDISTRIBUTION OF PERIODIC ORBITS FOR SUBSHIFTS OF FINITE TYPE(arXivLabs, 2016) Kadyrov Sh.We study equidistribution of certain subsets of periodic orbits for subshifts of finite type. Our results solely rely on the growth of these subsets. As a consequence, effective equidistribution results are obtained for both hyperbolic diffeomorphisms and expanding maps on compact manifolds.Item Open Access Endemic coexistence and competition of virus variants under partial cross-immunity(AIMS Electronic ResearchArchive, 2025) Kadyrov Sh.; Haydarov F.; Mamayusupov K.; Mustayev K.In this study, we developed a mathematical framework, based on the SIR model, to study the dynamics of two competing virus variants with different characteristics of transmissibility, immune escape, and cross-immunity. The model includes variant-specific transmission and recovery rates and enables flexible parameterization of partial and waning cross-immunity. We conducted stability and bifurcation analyses and numerical simulations to explore the conditions of coexistence, dominance, and extinction of the variants, studying variations in epidemiological parameters that affect endemic prevalence and infection ratios. Our results indicated that transmission rates, levels of crossimmunity, and immunity waning rates are critical in determining disease outcomes, which influence variant prevalence and competitive dynamics. The sensitivity analysis provided the relative importance of these parameters and provided valuable insight into designing intervention strategies. This work contributes to furthering our understanding of multi-variant epidemic dynamics and lays the bedrock for tackling complex interactions involving arising virus variants, finding applications in real-world public health planning.Item Open Access ENTROPY AND ESCAPE OF MASS FOR HILBERT MODULAR SPACES(arXivLabs, 2011) Kadyrov Sh.We study the relation between metric entropy and escape of mass for the Hilbert modular spaces with the action of a diagonal element.Item Open Access ENTROPY AND ESCAPE OF MASS FOR SL3(Z)\ SL3(R)(arXivLabs, 2010) Einsiedler M.; Kadyrov Sh.We study the relation between measure theoretic entropy and escape of mass for the case of a singular diagonal flow on the moduli space of three-dimensional unimodular lattices.Item Open Access Exceptional sets in homogeneous spaces and Hausdorff dimension(Dynamical Systems An International Journal, 2015) Kadyrov Sh.In this paper, we study the dimension of a family of sets arising in open dynamics. We use exponential mixing results for diagonalizable flows in compact homogeneous spaces X to show that the Hausdorff dimension of set of points that lie on trajectories missing a particular open ball of radius r is at most dim X + C rdim X log r , where C > 0 is a constant independent of r > 0. Meanwhile, we also describe a general method for computing the least cardinality of open covers of dynamical sets using volume estimates.Item Open Access Factors Affecting Mathematics Achievement in Central Asian Specialized Universities(International Journal of Emerging Technologies in Learning (iJET), 2020) Sapazhanov Y.; Sydykhov B.; Kadyrov Sh.; Orynbassar A.This study examines variables explaining student’s academic performances in mathematics from the specialized engineering institutions. A survey consisting of 42 items was conducted from 127 students and statistical multiple regression was carried out to analyze the data set. Based on FennemaSherman Mathematic Attitude Scales followed by the result of stepwise linear regression, found a significant impact of high school geometry grades in the mathematics performance. Authors suggest that mathematics instructors in higher education should pay attention to improve their student’s confidence, which in turn would decrease the anxiety level towards mathematics. The high school teachers should not advise their students to go to technical sciences in higher education unless the student’s confidence and high school math grade are sufficiently high.Item Open Access Fractal Dimension of Exceptional Sets in Semi-Regular Continued Fractions(faculty of engineering and natural sciences, 2025) Kadyrov Sh.; Kazin A.; Duisen S.This paper examines how the average value of the sequence bn in the Lehner expansion of a real number x influences its box dimension. Our primary objective is to analyze how variations in the average of bn impact the box dimension, which serves as a measure of the complexity of the sequence. Using the box-counting method, we numerically estimate the box dimension and explore its relationship with the fractal nature of Lehner expansions.Item Open Access IMPACT OF THE ACTIVE LEARNING STRATEGIES ON STUDENT’S ACHIEVEMENT WITH RESPECT TO DOUBLE INTEGRALS IN MATHEMATICAL ANALYSIS(Қазақ ұлттық қыздар педагогикалық университетінің Хабаршысы № 3, 2019) Almas A.; Kadyrov Sh.; Kaymak S.Active learning is useful to engage and make an interest for the students in learning of mathematics, where the educators face many difficulties in teaching mathematics. This paper aims to address how to apply active learning strategies on the subject of double integral in advanced mathematics. We chose some suitable active learning strategies for using in the subject of double integral to show its designs. We also applied the active learning strategies which is shown in the introduction part for two groups from second year students in the faculty of science education at Suleiman Demirel University to reveal the of impact of achievement on the students. Comparing the achievement of experimental group to the control group, the authors deduce that the experimental group significantly outperform than the control group in the subject of double integral in mathematical analysisItem Open Access Integer Prime Factorization with Deep Learning(Vol 2 No 1 (2021): Advances in Interdisciplinary Sciences, 2021) Murat B.; Kadyrov Sh.; Tabarek R.Prime factor decomposition is a method that is used in number theory and in cryptography, as well. The security of the message depends on the difficulty of factorization. In other words, to hack the RSA system, factorization of N is needed, where N is a product of two prime (generally large) numbers. This paper analyzes the approaches which are already used to solve the problem, and proposes a new method which is expected to increase the efficiency of prime number factorization with the help of neural networks. The results in this paper can be used to develop and improve the security of cryptosystems.Item Open Access LAGRANGE’S THEOREM AND 2- CONTINUED FRACTION EXPANSION(СДУ хабаршысы - 2019, 2019) Kadyrov Sh. ; Mashurov F.Abstract. The simple continued fraction theory is a sub-branch of number theory that is well developed. One of the classical results is due to Lagrange which states that the simple continued fraction expansion of a real number has eventually periodic expansion if and only if it is quadratic irrational. Similar results are not available when one considers N-continued fraction expansion which is not so well developed theory. In this article, authors aim to provide computational evidence when a quadratic irrational may not necessarily have eventually periodic 2-continued fraction expansion. Moreover, a proof is provided for a special type of real numbers for which Lagrange’s theorem does hold.Item Open Access MapReduce Solutions Classification by Their Implementation(The International Journal of Engineering Pedagogy (iJEP), 2023) Orynbekova K.; Bogdanchikov A.; Cankurt S.; Adamov A.; Kadyrov Sh.Distributed Systems are widely used in industrial projects and scientific research. The Apache Hadoop environment, which works on the MapReduce paradigm, lost popularity because new, modern tools were developed. For example, Apache Spark is preferred in some cases since it uses RAM resources to hold intermediate calculations; therefore, it works faster and is easier to use. In order to take full advantage of it, users must think about the MapReduce concept. In this paper, a usual solution and MapReduce solution of ten problems were compared by their pseudocodes and categorized into five groups. According to these groups’ descriptions and pseudocodes, readers can get a concept of MapReduce without taking specific courses. This paper proposes a five-category classification methodology to help distributed-system users learn the MapReduce paradigm fast. The proposed methodology is illustrated with ten tasks. Furthermore, statistical analysis is carried out to test if the proposed classification methodology affects learner performance. The results of this study indicate that the proposed model outperforms the traditional approach with statistical significance, as evidenced by a p-value of less than 0.05. The policy implication is that educational institutions and organizations could adopt the proposed classification methodology to help learners and employees acquire the necessary knowledge and skills to use distributed systems effectively.