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    О ЛОКАЛЬНОЙ МОНОТОННОСТИ ОДНОМЕСТНЫХ ФУНКЦИЙ ОПРЕДЕЛИМЫХ В КОНЕЧНО ПРОСТЕГАННЫХ УПОРЯДОЧЕННЫХ СТРУКТУРАХ
    (СДУ хабаршысы - 2020, 2020) Вербовский В.В
    Аннотация. Как было доказано Б. Кулпешовым, любое сечение в слабо о-минимальной структуре может иметь максимум два расширения до полных типов, причем множества всех реализаций этих типов являются выпуклыми в любых элементарных расширениях. В данной статье мы обобщаем понятие слабой о-минимальности и получаем следующее понятие n-стеганых структур: линейно упорядоченная структура называется n -стеганой, если любое сечение имеет не более n расширений до полного типов. Обратите внимание, что мы здесь опускаем условие, что множество всех реализаций типа должно быть выпуклым. В этой статье мы исследуем свойство локальной монотонности для одноместных функций, определимых в конечно простеганных структурах..
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    ОБЗОР УГРОЗ ИНФОРМАЦИОННОЙ БЕЗОПАСНОСТИ В ПРЕДПРИЯТИИ
    (СДУ хабаршысы - 2020, 2020) Атымтаева Л. ; Баймуратов О. ; Хашимова Д.А.
    Аннотация. В данной статье представлены результаты анализа по выявлению групп угроз, специфичных для инфраструктуры и систем предприятии которое является одним из основных этапов в прогнозировании. Рассмотрены состояние информационной безопасности на предприятиях, проанализированы квалификации угроз безопасности и методов классификации, основанные на методах атак и на воздействии угроз. Оценены угрозы по безопасному использованию Интернета и взламыванию сайтов, краж данных, атакам фишинга и социальной инженерии; выявление угроз безопасности облачных вычислений, которые встречаются в интернет сетях предприятии. Изучены преимущества и недостатки Файрвол веб-приложений (WAF), который применяются для защиты атак, такие как DDoS-атаки, SQL-инъекции, межсайтовый скриптинг (XSS), и др. Представлены работы для обеспечения защиты с применением искусственного интеллекта и машинного обучения.
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    ANALYZE AND DEVELOPMENT SYSTEM WITH MULTIPLE BIOMETRIC IDENTIFICATION
    (СДУ хабаршысы - 2020, 2020) Baimuratov O. ; Dadakhanov Sh.
    Abstract. Cause of a rapid increase in technological development, increasing identity theft, consumer fraud, the threat to personal data is also increasing every day. Methods developed earlier to ensure personal the information from the thefts was not effective and safe. Biometrics were introduced when it was needed technology for more efficient security of personal information. Old-fashioned traditional approaches like Personal identification number (PIN), passwords, keys, login ID can be forgotten, stolen or lost. In biometric authentication system, user may not remember any passwords or carry any keys. As people they recognize each other by the physical appearance and behavioral characteristics that biometric systems use physical characteristics, such as fingerprints, facial recognition, voice recognition, in order to distinguish between the actual user and scammer. In order to increase safety in 2005, biometric identification methods were developed government and business sectors, but today it has reached almost all private sectors as Banking, Finance, home security and protection, healthcare, business security and security etc. Since biometric samples and templates of a biometric system having one biometric character to detect and the user can be replaced and duplicated, the new idea of merging multiple biometric identification technologies has so-called multimodal biometric recognition systems have been introduced that use two or more biometric data characteristics of the individual that can be identified as a real user or not.
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    RFID TECHNOLOGY AS A PART OF MONITORING SYSTEMS
    (СДУ хабаршысы - 2020, 2020) Baimuratov O. ; Mamatnabiyev Zh. ; Dadakhanov Sh. ; Berlikozha B.
    Abstract. The Internet of Things (IoT) technologies are getting more popular and being implemented as a solution for many relevant problems in information technology purposing low-costed, secure, and controlled remotely systems. Radio Frequency Identification (RFID) system is used as a type of IoT technology, which has three basic parts: tags, reader and system that manages tag identification (ID) number and its real time location. RFID systems are used in financial institutions, healthcare industry, mobile phones, cars, supply chain management, smart retails, smart house, object localization, security systems and various types of applications for positioning, managing people, assets, and inventory. This paper discusses performances of RFID technologies that use passive tags. Role of RFID technologies in monitoring systems and system architecture are reviewed and compared. Significance of RFID technologies and challenges are also considered for future works.
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    ANALYSIS OF QUANTUM CRYPTOGRAPHY AND TECHNOLOGIES IN INDUSTRIES
    (СДУ хабаршысы - 2020, 2020) Habiburahman Sh.; Baimuratov O. ; Abdinurova N.
    Abstract. In today’s connected world it’s crucial to make sure telecommunication is not a risk. Eavesdroppers will always find a way to attack and harm big companies systems or governmental databases. It’s very important to find the best possible way to keep our services safe. Quantum cryptography is one the best way since it’s based on rules of quantum physics. In this paper we are going to analyse the best solutions, protocols and different aspects of encryption. Real life implementations by different IT companies and investors will also be included in this paper. Weakness and pros always exist in every system and it’s impossible to indicate the system we are proposing is not breakable but it’s going to be the best possible solution for now. Why? It’s going to be discussed in later sections.
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    ПРЕОБРАЗОВАНИЕ БАНКА В ОТКРЫТУЮ ЭКОСИСТЕМУ API
    (СДУ хабаршысы - 2020, 2020) Жолдасов Б.К. ; Рысмендеева Г.С.
    Аннотация. Работа посвящена преобразованию банка в открытую экосистему API. В статье будет рассматриваться факторы внедрения открытой экосистемы API в банки, связанные с этим возможности и банковской отрасли и описываются успешные API стратегии.
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    COMPUTER ANALYSIS OPTICAL COHERENCE TOMOGRAPHY IMAGES BY USING UNSUPERVISED MACHINE LEARNING ALGORITHM
    (СДУ хабаршысы - 2020, 2020) Amirgaliev Y. ; Tastembekov A. ; Bertailak Sh.
    Abstract. In recent years, computer image analysis has been developing rapidly. In the field of medicine has been identified to a new level that has greatly helped for the diagnostic system. There are many information systems in the field of ophthalmology and cardiology. Advanced technologies not only accelerate the work of doctors but also help to diagnose the disease in a timely manner and prescribe the treatment. In this research paper was carried out an analysis of the machine learning algorithm using a database of tomographic images of blood vessels in the eye system. Were studied the used methods for calculating several reasons in order to select a specific model, methods for calculating its properties and advantages. The main goal of this research is that doctors can not only check the current condition of the patient’s eye but also diagnose certain diseases, such as diabetes and anemia
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    USING ARTIFICIAL INTELLIGENCE TO IMPROVE DIGITAL MARKETING STRATEGIES
    (СДУ хабаршысы - 2020, 2020) Kaiyp K. ; Alimanova M.
    Abstract. The use of artificial intelligence (AI) will provide huge advantages in the digital marketing strategy of each company. This is a new face of productivity, efficiency and profitability. Making decisions about the start of a new era based on artificial intelligence should not replace the work of marketers or advertisers. It is here to unleash their true strategic and creative potential. For a business executives and marketers, the time has come to identify the problems facing the business or the marketing campaign, and how accurate ideas can solve these problems. This study discusses how AI could affect to effective of marketing strategies, shows real cases of using AI tools, and how companies could increase their profit.
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    IMPROVING INDICATORS OF DIGITAL MARKETING USING ARTIFICIAL INTELLIGENCE
    (СДУ хабаршысы - 2020, 2020) Kaiyp K. ; Alimanova M.
    Abstract. In recent years, artificial intelligence (AI) has become a growing trend in various fields: medicine, education and the automotive industry. AI also reached a business, namely the marketing department of various businesses. The goal of the article is to research how deeply AI is used in digital marketing. The authors asked two research questions - which areas of AI are used in marketing and what are the positive effects of chat bots on a business. To answer these questions, the authors conducted a study of secondary data with examples of AI used for marketing purposes. An analysis of the collected examples shows that AI is widely implemented in the field of marketing, although applications are at the operational level. This may be the result of the careful implementation of the new technology, still at the level of experimentation with it. The uncertainty of the results of the implementation of AI can also affect caution when applying these innovations in practice. The collected examples proved that AI affects all aspects of the marketing structure, affecting both consumer value and the organization of marketing and business management. This document is important for the business, especially the idea of introducing artificial intelligence into marketing, developing innovation, and ideas on how to incorporate new skills into the marketing team needed for new technology
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    INTRODUCE PREDICTIVE ANALYTICS USING THE NEXT BEST ACTION (NBA) MODELS INTO THE BANKING SYSTEM
    (СДУ хабаршысы - 2020, 2020) Dauylov S. ; Bogdanchikov A.
    Abstract. NBA - is an approach in which each client is initially considered purely individual. It has a close correlation with Predictive analysis. Predictive or prognostic analytics is a set of techniques and methods for analyzing data to build a forecast of future events. The banking system is currently using the method to obtained certain business results from its customers and has increased loyalty, increased income, found new growth points, etc. The classical model of marketing was rather different, it repelled from its existing product line and its parameters. But new models repels from customer’s inclination to purchase a particular product. The aim of this project is to investigate the field of deposit accounts of the banking system by using NBA approach and to show the benefits and possible outcomes. This approach was tested on various aspects of the banking system and showed a number of solutions which can predict the probability of a customer to create a term deposit account.
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    PRINCIPAL COMPONENT ANALYSIS AND A MULTILINGUAL CONSTRUCT TO DETERMINE THE UNDERGRADUATE MAJOR SELECTION FACTORS
    (СДУ хабаршысы - 2020, 2020) Assanbayeva G. ; Kadyrov Sh.
    Abstract. In this article, we review mathematics behind well-known Principal Component Analysis from Linear Algebra implemented in various applied fields. As an application, we develop a construct to measure factors that affect college students in their major selection. This is a multilingual construct given in three languages, namely Kazakh, Russian, and English. To this end, we prepare a survey consisting of 27 Likert scale items in three languages and it is conducted among 314 undergraduate students in Kazakhstan. For dimensionality reduction, Principal Component Analysis is carried in python programming language which resulted in 9 major scales with only 22 elements. The overall reliability of the test is calculated to be 0,856. The nine scales are the effect of Uniform National Testing, state grant affect, personal interest affect, skills affect, occupation salary affect, teacher affect, external affect, university cost affect, parent’s affect.
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    TRAINING A SINGLE MACHINE LEARNING AGENT USING REINFORCEMENT LEARNING AND IMITATION LEARNING METHODS IN UNITY ENVIRONMENT
    (СДУ хабаршысы - 2020, 2020) Urmanov M. ; Alimanova M.
    Abstract. This paper provides a research of Unity plugin that helps to develop Machine Learning Agents within Unity engine environment. This work introduces training a single Machine Learning Agent using both Reinforcement Learning and Imitation Learning methods, comparing the results and effectiveness.
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    SUPERCONDUCTIVITY
    (СДУ хабаршысы - 2020, 2020) Sadyk U. ; Adil B.C.
    Abstract. The aim of this article is to provide a general information about superconductors. Superconductivity is the weird phenomenon of zero electrical resistance that occurs when some materials are cooled below a critical temperature. To get cold enough liquid helium or nitrogen (often as low as -250 °C or -480 F) are used. This article primarily focuses on the history, the invention and the properties and the areas of usage of superconductors. The phenomena of superconductivity was first observed by Heike Kamerlingh Onnes in 1908 in Netherlands. Experimental physicists are now trying to find superconductors at room temperature. This article also intends to arouse curiosity among physics students
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    FORECASTING OIL PRODUCTION USING LSTM NETWORKS CONFINED TO DECLINE
    (СДУ хабаршысы - 2020, 2020) Zhumekeshov A. ; Bogdanchikov A.
    Abstract. Natural resources are limited and very important in our industrial life and development. Oil is considered as the black gold and it is included in hundreds of industrial fields. Therefore, forecasting future oil production performance is an important aspect for oil industry. In this study, we proposed improvements to the existing deep learning model in order to overcome limitations associated with the original model. For evaluation purpose, proposed and original deep learning models were applied on a real case oil production data. The empirical results show that the proposed adjustments to the existing deep learning model achieves better forecasting accuracy.
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    СНИЖЕНИЕ ШУМА ДЕРЕВООБРАБАТЫВАЮЩИХ СТАНКОВ РЕВЕРБЕРАЦИОННОЙ КАМЕРОЙ
    (СДУ хабаршысы - 2020, 2020) Курманбекова Э.Б. ; Шалтабаева С.Т.; Сатылган К.Н.
    Аннотация. Вопросы снижения шума в деревообрабатывающих производствах усугубляются с каждым годом. Подавление шума стало релевантной проблемой современности, так как ее урегулирование может, с одной стороны, гарантировать нормальные условия труда, высвободить вспомогательные ресурсы для увеличения продуктивности труда, что в окончательном счете целиком оправдывает материальные трудозатраты на борьбу с шумом. Сейчас для владельца бизнеса выигрышнее не инвестировать резервы в инженерно-техническое обновление своих предприятий, а применить устаревшее деревообрабатывающее оборудование, регулярно проводя штатный ремонт. Повышение условий труда на малых деревообрабатывающих предприятиях по шумовому критерию - главному вредному производственному критерию - является актуальной. В публикации приводится образец снижения шума на дереворежущих станках с помощью реверберационной камеры
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    ВЛИЯНИЕ ПРИМЕСЕЙ Al и Mn НА ПРОЦЕССЫ СТРУКТУРНЫХ ПРЕВРАЩЕНИЙ В СПЛАВАХ МЕДИ
    (СДУ хабаршысы - 2020, 2020) Лободюк В.А.; Мукашев К.М. ; Толен Д.E.
    Аннотация. В работе на конкретных примерах с привлечением реальных сплавов на основе меди, содержащего 14 вес.%Al и 3вес.%Mn, описываются результаты исследования процесса восстановления формы материала, который подвергался деформации по схеме трехточечного изгиба. Исследования проводились методом измерения изменения температурной зависимости электросопротивления и прогиба образца, а также путем получения микроэлектронограмм с помощью электронного микроскопа. Поскольку сплавы с ЭПФ работают в условиях обязательного термоциклирования, выяснение термостабильности этих материалов имеет важный практически интерес. Установлено, что в мартенситных кристаллах, возникающих в закаленных образцах, наблюдаются высокая плотность дефектов упаковки и тонкие двойники, образующиеся на плоскости (121) γ´. Одной из важных особенностей мартенситного механизма является обязательное образование мартенсита с дефектами, представляющего тонкую структуру. Путем сопоставления кривых электросопротивления и прогиба было установлено, что температурный интервал возрастания прогиба при охлаждении совпадает с интервалом температур прямого мартенситного превращения. Кроме дефектов упаковки в мартенситных кристаллах наблюдаются и тонкие двойники толщиной 0,01-0,04 мкм. При анализе было установлено, что двойникование в мартенсите происходит по плоскости 121γ´. Показано, что возникающая при мартенситных превращениях полосчатость обусловлена дефектами упаковки, которые лежат в плоскости 121 при высокой плотности дефектов упаковки.
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    EXPLORING THE IMPACT OF MACHINE LEARNING ON KYC COMPLIANCE COSTS AND CUSTOMER EXPERIENCE
    (СДУ хабаршысы - 2023, 2023) Sattarbek A. ; Zhumashev B.; Parmanov S.
    Abstract. The Know Your Customer (KYC) compliance process is a critical requirement for financial institutions to prevent money laundering, fraud, and terrorist financing. Machine learning algorithms have the potential to improve the efficiency and accuracy of KYC compliance checks. In this study, we explored the effectiveness of several classification algorithms for KYC compliance checks using a dataset with 3000 rows collected from a famous banking system in Kazakhstan. We compared the performance of four commonly used algorithms: Decision Tree, Random Forest, Logistic Regression, and Support Vector Machines. Our results showed that all four algorithms achieved high accuracy rates, with Random Forest performing the best, achieving an accuracy rate of 92.1%. These findings suggest that machine learning algorithms can effectively classify KYC checks, with Random Forest being the most effective algorithm in our study. This study provides further evidence of the potential of machine learning for KYC compliance checks in the banking industry, but also highlights the need for ongoing monitoring and validation of machine learning models and concerns about explainability and transparency.
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    ANALYSIS OF PROGRAMMING EDUCATION AT THE PRIMARY EDUCATION LEVEL
    (СДУ хабаршысы - 2023, 2023) Saimassay G. ; Zhaparov M. ; Mukhiyayeva A. ; Zhalgassova Zh.
    Abstract. Programming education has traditionally been provided at the undergraduate level worldwide. However, in recent years, there has been a growing trend in developed countries to introduce programming education at earlier ages with the aim of promoting software literacy, improving programming skills, and making programming education accessible to a wider audience. While some countries are updating their informatics lessons to include programming, others are incorporating programming lessons into their primary education curriculum for the first time. The level at which programming training is offered also differs between countries. The objective of this research is to explore how countries have integrated programming education into their curricula and to identify the differences between countries in terms of programming education. The study aims to answer the question of how programming education is provided at the primary education level both domestically and abroad. The research has found that programming education is increasingly recognized as important and many countries are now allowing programming lessons in their education curriculum, with some countries even introducing programming education in kindergarten. However, there are variations in the programming languages used and the skills taught to students across different countries.
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    COMPARISON OF DIFFERENT CLASSIFICATION MODELS FOR SENTIMENT ANALYSIS
    (СДУ хабаршысы - 2023, 2023) Makhul M.
    Abstract. In this work, we explored sentiment analysis techniques of texts using the example of product comments in the Kazakh language. To do this, we used machine learning methods such as Naive Bayes, Random Forest, Logistic Regression and Support Vector Machine, as well as text processing tools: CountVectorizer and TfidfVectorizer. In the process of work, experiments were carried out with different configurations of models and parameters of vectorizers. To assess the quality of the models, we used accuracy, precision, recall and F1-score metrics. The research findings indicated that the application of machine learning techniques make it possible to achieve high accuracy in sentiment analysis of comments. The best results were obtained using the Support Vector Machine and TfidfVectorizer. This study can be used to further improve the systems for sentiment analysis of comments in the Kazakh language, which can be useful in monitoring public opinion in various areas, including business.
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    DEVELOPMENT OF LONG RANGE ANIMAL TRACKING SYSTEM USING IOT TECHNOLOGIES
    (2022 International Young Scholars' Conference, 2022) Aitkulov A. ; Mamatnabiyev Zh.
    Abstract The population of our planet is growing at a rapid pace, with an annual growth of 1.1 percent. The population is expected to continue to grow and reach 8.4 billion by 2030. Although this is a fairly positive fact, this phenomenon carries with it enough negative aspects. And one of which is the lack of food, which requires the rapid development of agriculture. Agriculture will have to increase its production massively by 70 percent. The solution to this problem is the technology of the Internet of things. With the help of technology we can avoid morbidity in livestock, excess in power consumption and generally make life easier for the farmers. In this work, a strong focus will be placed on tracking the location of animals, which will be quite cheap and of high quality. This research aims to find the most optimal technologies to track animals on long ranges, while being low-priced and effective enough.