Қазақ ұлттық қыздар педагогикалық университеті / Казахский национальный женский педагогический университет

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  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    MANAGEMENT OF THE WORKPLACES BY THE FACILITIES OF OPERATIONS RESEARCH
    (Lublin University of Technology, 2022-09-30)
    Nataliia Geseleva
    ;
    Ganna Proniuk
    ;
    Olexander N. Romanyuk
    ;
    Ольга Вікторівна Акімова
    ;
    Tetiana Troianovska-Korobeynikova
    The optimal location of workplaces plays an important role in the structure of occupational safety. The design of the workspace should ensure the optimal distribution of functions between person and machine in order to create safe working conditions, reduce the severity of work and the level of production injuries. Most often, workplace planning is carried out manually, by simple calculation, and then the rationality of workplace planning is evaluated, based on statistics of industrial accidents and occupational diseases, as well as indicators of labor productivity, for example, the ratio of compliance with norms. To solve the problem of optimal placement in the work mathematical models are built that can take into account various regulatory restrictions and are simple for further software implementation. It is proposed to choose the theory of φ-functions as a basis, which can be characterized as measures of proximity of objects. Thus, the set task of optimal placement of workplaces is reduced to the task of mathematical programming. The objective function determines the criterion of optimality – the minimization of the area or perimeter that will be occupied by the objects. This formulation of the problem is relevant because the use of the smallest production area, taking into account safety requirements, is an economic condition for effective production management. The constraint on the relative location of workplaces is set using φ-functions, which defines the decision domain. That, when formalizing restrictions, you can take into account all regulatory safety distances between workplaces, equipment, walls, etc. Thus, the work explores an approach that will allow automatic planning of the placement of a large number of technological objects, workplaces in accordance with occupational safety standards. Use of the software application, which can be implemented on the basis of the φ-functions apparatus, will significantly reduce the time of workplaces planning and increase its efficiency.
  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    Technology of formation of students' skills of educational and cognitive activity through mathematical modelling
    (Science Park Research Organization and Counselling LTD, 2022-11-28) ; ; ;
    Doolotbai Babaev
    ;
    The study was examined, the technology for creating students' educational and cognitive activity skills through mathematical modelling was aimed and designed. As a model, this study was helped by the quantitative research model, and the research was carried out in the fall term of 2022–2023. 172 volunteer students who continue their education in high schools participated in the research. In the study, 3 weeks of online training was given to the students. The data collection tool was delivered to high school students by online method and collected. The analysis of the data was added to the research by tabulating the findings from the participants. When the results dimension of the study was examined comprehensively, it was concluded that the cognitive activity levels of the students were high through mathematical modelling. While this situation was determined as good for education, it was concluded that it was used by reflecting the mathematics and technology systems in the course. Keywords: High school students, mathematical modelling, cognitive activity, mathematics, independent work, cognitive impairment, mathematical modelling, problem, verbal calculation;
    Цитирования (OpenAlex) 2Цитирования (OpenCitations) 1
  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    Numerical simulation and GPU computing for the 2D wave equation with variable coefficient
    (Inderscience Publishers, 2023-01-01) ; ;
    In this paper, we present parallel numerical implementations of a 2D wave equation with a variable coefficient on GPU. We considered wave propagation simulations in shallow water areas caused by underwater movement and performed some numerical simulations at different time steps. The sequential algorithm is based on the implicit finite difference scheme and the parallel cyclic reduction (PCR) method. The parallel code was developed using CUDA technology and tested on different domain sizes. Performance analysis showed that our parallel approach showed a good speedup compared to sequential CPU code. The proposed parallel visualisation simulator can serve as a good tool for numerous water management systems in engineering practices.
    Цитирования (OpenAlex) 1Цитирования (OpenCitations) 1
  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    A GPU IMPLEMENTATION OF THE TSUNAMI EQUATION
    (Astana IT University, 2023-03-30) ; ;
    In this paper, we consider numerical simulation and GPU (graphics processing unit) computing for the two-dimensional non-linear tsunami equation, which is a fundamental equation of tsunami propagation in shallow water areas. Tsunamis are highly destructive natural disasters that have a significant impact on coastal regions. These events are typically caused by undersea earthquakes, volcanic eruptions, landslides, and possibly an asteroid impact. To solve numerically, firstly we discretized these equations in a rectangular domain and then transformed the partial differential equations into semi-implicit finite difference schemes. The spatial and time derivatives are approximated by using the second-order centered differences following the Crank-Nicolson method and the calculation method is based on the Jacobi method; the computation is performed using the C++ programming language; and the visualization of numerical results is performed by Matlab 2021. The initial condition was given as a Gaussian, and the basin profile has been approximated by a hyperbolic tangent. To accelerate the sequential algorithm, a parallel computation algorithm is developed using CUDA (Compute Unified Device Architecture) technology. CUDA technology has long been used for the numerical solution of partial differential equations (PDEs). It uses the parallel computing capabilities of graphics processing units (GPUs) to speed up the PDE solution. By taking advantage of the GPU’s massive parallelism, CUDA technology can significantly speed up PDE computations, making it an effective tool for scientific computing in a variety of fields. The performance of the parallel implementation is tested by comparing the computation time between the sequential (CPU) solver and CUDA implementations for various mesh sizes. The comparison shows that our parallel implementation gives significant acceleration in the implementation of CUDA.
  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    ГЕОГРАФИЯЛЫҚ АҚПАРАТТЫҚ ЖҮЙЕЛЕРДІ ЗЕРТТЕУДІҢ АЛГОРИТМІН ҚҰРУ
    (Mukhametzhan Tynyshbayev ALT University, 2023-10-27) ; ;
    Динара Касымова
    Жер туралы ақпаратты ауыл шаруашылығында қолданғанда аумақтың жай-күйін, автоматтандырылған талдауды қамтитын бірқатар инженерлік міндеттерді шешу үшін сол аумақтың объектілерінің жер бедерінің биіктігі туралы ақпараттар цифрлық түрде қолданылады. Геоақпараттық жүйелерде топырақтың географиялық, мелиоративтік, агрохимиялық талдауларының деректері және орындалған жұмыстардың нәтижелерін бақылау, сондай-ақ олардың тиімділігін талдау сияқты әртүрлі ақпарат болуы мүмкін. Бұл жүйе кәсіпорынның экономикалық тиімділігін шешіп, жақсарта алады, топырақтың сапасы мен күйін жақсартады, агроөнеркәсіптік өндірістің бірқатар міндеттерін жеңілдетеді. Зерттеу барысында сызықтық интерполяция әдісі қолданылды есептеу желінің басқа үшбұрыштарына тәуелсіз әр үшбұрыштың ішіндегі геоөрістің мәні, заманауи бағдарламалық жасақтаманы қолдана отырып математикалық модельдеу. Мақалада цифрлық картография, кеңістіктік деректер модельдері, кеңістіктік деректерді жинау, сақтау және талдау әдістері, алгоритмдері негізінде анықтау мәселелерін шешуге арналған географиялық ақпараттық жүйенің (ГАЖ) алгоритмін құру мүмкіндігі қарастырылады. Осы мақалада цифрлық модельдеу алгоритмі, рельефтің цифрлық моделі мен әдісі туралы мәліметтер келтірілді. Жасалған алгоритм бойынша Python тілінде бағдарлаасы жасалынып, нәтижесі алынды. Жұмыстың ғылыми жаңалығы оның қажетті нүктенің үшінші координатасын анықтау алгоритмін, сондай-ақ кеңістіктік мәліметтерді жинау, сақтау және талдау әдістерін пайдалануды ұсынуында. Келешекте қолдану аймағына және мәселенің қойылуына байланысты қосымшалар жасалуы мүмкін.
  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    Precision Diagnosis: An Automated Method for Detecting Congenital Heart Diseases in Children From Phonocardiogram Signals Employing Deep Neural Network
    (Institute of Electrical and Electronics Engineers, 2024-01-01)
    Hend Khalid Alkahtani
    ;
    Ihtisham Ul Haq
    ;
    Yazeed Yasin Ghadi
    ;
    Nisreen Innab
    ;
    Masoud Alajmi
    According to the World Health Organization (WHO), congenital heart disorders (CHDs) impact a significant proportion of babies worldwide, with prevalence rates ranging from 0.8% to 1.2%. Phonocardiography (PCG) is the leading non-invasive method for detecting congenital heart defects (CHDs), offering important information about cardiac signals i.e. S1, S2, S3, and S4 and heartbeat patterns. This research study focuses on developing a strong binary classification system for congenital heart diseases (CHDs) utilizing deep neural networks. The system will be trained on a combined dataset that includes both local and publicly available repositories. The local dataset (LD) consists of 583 signals containing both normal and aberrant PCG recordings, while the public dataset (PD) obtained from Michigan University consists of 23 PCG recordings. In order to achieve consistency and compatibility, both datasets are subjected to down-sampling, resulting in a frequency of 8 kHz. A well-engineered band-pass filter efficiently removes signals outside the 20-650 Hz range, allowing for exclusive processing of the desired frequencies. The signals are divided into segments, each lasting exactly 4 seconds. The study utilizes data augmentation techniques, specifically pitch-shifting, to boost the model’s robustness. This is accomplished by implementing a 1D convolutional neural network (CNN). The most notable outcomes are achieved in case C, exhibiting a sensitivity of 99.0%, specificity of 98.0%, F1 score of 98.56%, precision of 98.57%, and an accuracy of 98.56%. This study enhances the progress of automated techniques for detecting congenital heart disease (CHD), demonstrating the potential of deep neural networks in precision medicine for pediatric cardiology.
    Цитирования (OpenAlex) 27Цитирования (OpenCitations) 21
  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    Numerical simulation and GPU computing for the 2D wave equation with variable coefficient
    (Inderscience Publishers, 2024-01-01) ; ;
    In this paper, we present parallel numerical implementations of a 2D wave equation with a variable coefficient on GPU. We considered wave propagation simulations in shallow water areas caused by underwater movement and performed some numerical simulations at different time steps. The sequential algorithm is based on the implicit finite difference scheme and the parallel cyclic reduction (PCR) method. The parallel code was developed using CUDA technology and tested on different domain sizes. Performance analysis showed that our parallel approach showed a good speedup compared to sequential CPU code. The proposed parallel visualisation simulator can serve as a good tool for numerous water management systems in engineering practices.
  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    МЕТОДИКА ИСПОЛЬЗОВАНИЯ КОМПЬЮТЕРНОЙ ЭКСПЕРТИЗЫ В ПРОЦЕССЕ ОБУЧЕНИЯ ГЕОМЕТРИИ В УСЛОВИЯХ ЦИФРОВИЗАЦИИ ОБРАЗОВАНИЯ
    (Ablai Khan University, 2024-03-28) ;
    В статье рассматриваются проблемы преподавания геометрии в условиях цифровизации образования. Технологические инструменты, такие как компьютеры, используются в преподавании, обучении и оценивании геометрии. В этом исследовании изучалась интеграция некоторых аспектов компьютерных технологий в преподавание и изучение геометрии. С этой целью рассмотрена разработка методики применения программы «The Geometer's Sketchpad», компьютерного учебника с использованием компьютерных программ (KPUN), демонстрационных программ на различных этапах школьного обучения геометрии. Кроме того, для студентов математических факультетов педагогических вузов создан курс «Компьютерное обучение геометрии в средней школе». Во многих исследованиях, посвященных различным аспектам компьютерного обучения, компьютер рассматривается как техническая основа автоматизированной системы обучения, реализующей идеи программированного обучения. Опыт использования образовательных программ выявил ряд недостатков компьютерного образования: компьютер позволяет преподавать только простой материал; компьютерное обучение не способствует развитию инициативы ученика; обучение посредством подкрепления реакции хуже, чем обучение, основанное на интеллектуальных упражнениях. В исследовании были применены метод сравнительного анализа, системный метод, метод категоризации и функционально-стилистического анализа медиатекстов, метод контент-анализа и эксперимента. Результаты данного исследования показывают, что использование компьютеризации как основы изменения деятельности существенно влияет на успеваемость учащихся. Он также выявил педагогический потенциал и ограничения компьютерных технологий в преподавании и изучении геометрии. Возможности компьютерного обучения использовались в преодолении трудностей учащихся, вызванных неверным или неполным пониманием содержания геометрического понятия; недостаточным владением математической терминологией.
  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    INTELLIGENT DATA ANALYSIS ON AN ANALYTICAL PLATFORM
    (Lublin University of Technology, 2024-03-31) ; ; ;
    The article discusses methods for processing unstructured data using an analytical platform. The authors analyze existing methods and technologies used to implement data processing and propose new approaches to solving this problem. The possibilities of using analytical platforms to solve the problem of processing source data are considered. The purpose of the article is to explore the possibilities of data import, partial preprocessing, missing data recovery, anomaly removal, spectral processing and noise removal. The authors explored how analytics platforms can function without a data warehouse, obtaining information from any other sources, but the most optimal way is to use them together, and how big data and unstructured data can be processed using an analytics platform. The authors solved a specific problem related to processing problems and proposed ways to solve them using an analytical platform. Particular attention is paid to a complete set of mechanisms that allows you to obtain information from any data source, carry out the entire processing cycle and display the results. Overall, the paper represents an important contribution to the development of raw data processing technologies. The authors plan to continue research in the field of processing big unstructured data.
    Цитирования (OpenAlex) 1Цитирования (OpenCitations) 4
  • Некоторые метрики заблокированы вашими 
    Тип записи:Публикация,
    НЕЙРОННЫЕ АРХИТЕКТУРЫ ДЛЯ ОПРЕДЕЛЕНИЯ ПОЛА ИИДЕНТИФИКАЦИИ ГОВОРЯЩЕГО
    (2024-06-01) ; ;
    В этой статье мы исследуем две нейронные архитектуры для задач определения пола и идентификации говорящего, используя функции мелкочастотных кепстральных коэффициентов (MFCC), которые не охватывают характеристики, связанные с голосом. Одна из наших целей –сравнить различные нейронные архитектуры, многослойный персептрон (MLP) и сверточные нейронные сети(CNNS) для обеих задач с различными настройками и автоматически изучить особенности, характерные для пола/ говорящего. Экспериментальные результаты показывают, что модели, использующие z-оценку и преобразование матрицы Грамиана, дают лучшие результаты, чем модели, использующие только максимальную-минимальную нормализацию MFCC. С точки зрения времени обучения, MLP требует больших периодов обучения для сходимости, чем CNN. Другие экспериментальные результаты показывают, что MLP превосходят CNN в решении обеих задач с точки зрения ошибок обобщения.