Репозиторий Евразийского национального университета имени Л.Н. Гумилева
Репозиторий Евразийского национального университета имени Л.Н. Гумилева
Репозиторий Евразийского национального университета имени Л.Н. Гумилева
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Отображаемые элементы 1-20 из 74

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    • A Traffic Analysis and Node CategorizationAware Machine Learning-Integrated Framework for Cybersecurity Intrusion Detection and Prevention of WSNs in Smart Grids 

      ZHUKABAYEVA, TAMARA; PERVEZ, AISHA; MARDENOV, YERIK; OTHMAN, MOHAMED; KARABAYEV, NURDAULET; AHMAD, ZULFIQAR (IEEE Access, 2024)
      Smart grids are transforming the generation, distribution, and consumption of power, marking a revolutionary step forward for contemporary energy systems. Communication in smart grid environments is majorly performed through Wireless Sensor Networks (WSNs). The WSNs enable real-time monitoring and management inside smart grids. However, the integration of digital technologies ...
      2026-03-13
    • A Traffic Analysis and Node CategorizationAware Machine Learning-Integrated Framework for Cybersecurity Intrusion Detection and Prevention of WSNs in Smart Grids 

      ZHUKABAYEVA, TAMARA; PERVEZ, AISHA; MARDENOV, YERIK; OTHMAN, MOHAMED; KARABAYEV, NURDAULET; AHMAD, ZULFIQAR (IEEE Access, 2024)
      Smart grids are transforming the generation, distribution, and consumption of power, marking a revolutionary step forward for contemporary energy systems. Communication in smart grid environments is majorly performed through Wireless Sensor Networks (WSNs). The WSNs enable real-time monitoring and management inside smart grids. However, the integration of digital technologies ...
      2026-03-10
    • A Traffic Analysis and Node CategorizationAware Machine Learning-Integrated Framework for Cybersecurity Intrusion Detection and Prevention of WSNs in Smart Grids 

      ZHUKABAYEVA, TAMARA; PERVEZ, AISHA; MARDENOV, YERIK; OTHMAN, MOHAMED; KARABAYEV, NURDAULET; AHMAD, ZULFIQAR (IEEE Access, 2024)
      Smart grids are transforming the generation, distribution, and consumption of power, marking a revolutionary step forward for contemporary energy systems. Communication in smart grid environments is majorly performed through Wireless Sensor Networks (WSNs). The WSNs enable real-time monitoring and management inside smart grids. However, the integration of digital technologies ...
      2026-03-18
    • An Edge-Computing-Based Integrated Framework for Network Traffic Analysis and Intrusion Detection to Enhance Cyber–Physical System Security in Industrial IoT 

      Zhukabayeva, Tamara; Ahmad, Zulfiqar; Adamova, Aigul; Karabayev, Nurdaulet; Abdildayeva, Assel (Sensors, 2025)
      Industrial Internet of things (IIoT) environments need to implement reliable security measures because of the growth in network traffic and overall connectivity. Accordingly, this work provides the architecture of network traffic analysis and the detection of intrusions in a network with the help of edge computing and using machine-learning methods. The study uses k-means and ...
      2026-02-20
    • An Edge-Computing-Based Integrated Framework for Network Traffic Analysis and Intrusion Detection to Enhance Cyber–Physical System Security in Industrial IoT 

      Zhukabayeva, Tamara; Ahmad, Zulfiqar; Adamova, Aigul; Karabayev, Nurdaulet; Abdildayeva, Assel (Sensors, 2025)
      Industrial Internet of things (IIoT) environments need to implement reliable security measures because of the growth in network traffic and overall connectivity. Accordingly, this work provides the architecture of network traffic analysis and the detection of intrusions in a network with the help of edge computing and using machine-learning methods. The study uses k-means and ...
      2026-03-04
    • An Edge-Computing-Based Integrated Framework for Network Traffic Analysis and Intrusion Detection to Enhance Cyber–Physical System Security in Industrial IoT 

      Zhukabayeva, Tamara; Ahmad, Zulfiqar; Adamova, Aigul; Karabayev, Nurdaulet; Abdildayeva, Assel (Sensors, 2025)
      Industrial Internet of things (IIoT) environments need to implement reliable security measures because of the growth in network traffic and overall connectivity. Accordingly, this work provides the architecture of network traffic analysis and the detection of intrusions in a network with the help of edge computing and using machine-learning methods. The study uses k-means and ...
      2026-03-18
    • An Edge-Computing-Based Integrated Framework for Network Traffic Analysis and Intrusion Detection to Enhance Cyber–Physical System Security in Industrial IoT 

      Zhukabayeva, Tamara; Ahmad, Zulfiqar; Adamova, Aigul; Karabayev, Nurdaulet; Abdildayeva, Assel (Sensors, 2025)
      Industrial Internet of things (IIoT) environments need to implement reliable security measures because of the growth in network traffic and overall connectivity. Accordingly, this work provides the architecture of network traffic analysis and the detection of intrusions in a network with the help of edge computing and using machine-learning methods. The study uses k-means and ...
      2026-03-26
    • An Edge-Computing-Based Integrated Framework for Network Traffic Analysis and Intrusion Detection to Enhance Cyber–Physical System Security in Industrial IoT 

      Zhukabayeva, Tamara; Ahmad, Zulfiqar; Adamova, Aigul; Karabayev, Nurdaulet; Abdildayeva, Assel (Sensors, 2025)
      Industrial Internet of things (IIoT) environments need to implement reliable security measures because of the growth in network traffic and overall connectivity. Accordingly, this work provides the architecture of network traffic analysis and the detection of intrusions in a network with the help of edge computing and using machine-learning methods. The study uses k-means and ...
      2026-03-10
    • An Intrusion Detection System for Multiclass Classification Across Multiple Datasets in Industrial IoT Using Machine Learning and Neural Networks Integrated with Edge Computing 

      ZHUKABAYEVA, Tamara; AHMAD, Zulfiqar; KARABAYEV, Nurdaulet; BAUMURATOVA, Dilaram; ALI, Mushtaq (Data, Information and Computing Science, 2025)
      With the rapid expansion of industrial IoT (IIoT), maintaining robust cybersecurity is essential for the smooth operation of industrial processes. Industrial environments require adaptive solutions to effectively mitigate evolving cyber threats and protect sensitive operations. This research aims to improve the cybersecurity of industrial IoT environments. The research ...
      2026-03-10
    • An Intrusion Detection System for Multiclass Classification Across Multiple Datasets in Industrial IoT Using Machine Learning and Neural Networks Integrated with Edge Computing 

      ZHUKABAYEVA, Tamara; AHMAD, Zulfiqar; KARABAYEV, Nurdaulet; BAUMURATOVA, Dilaram; ALI, Mushtaq (Data, Information and Computing Science, 2025)
      With the rapid expansion of industrial IoT (IIoT), maintaining robust cybersecurity is essential for the smooth operation of industrial processes. Industrial environments require adaptive solutions to effectively mitigate evolving cyber threats and protect sensitive operations. This research aims to improve the cybersecurity of industrial IoT environments. The research ...
      2026-03-18
    • An Intrusion Detection System for Multiclass Classification Across Multiple Datasets in Industrial IoT Using Machine Learning and Neural Networks Integrated with Edge Computing 

      ZHUKABAYEVA, Tamara; AHMAD, Zulfiqar; KARABAYEV, Nurdaulet; BAUMURATOVA, Dilaram; ALI, Mushtaq (Data, Information and Computing Science, 2025)
      With the rapid expansion of industrial IoT (IIoT), maintaining robust cybersecurity is essential for the smooth operation of industrial processes. Industrial environments require adaptive solutions to effectively mitigate evolving cyber threats and protect sensitive operations. This research aims to improve the cybersecurity of industrial IoT environments. The research ...
      2026-03-25
    • An Intrusion Detection System for Multiclass Classification Across Multiple Datasets in Industrial IoT Using Machine Learning and Neural Networks Integrated with Edge Computing 

      ZHUKABAYEVA, Tamara; AHMAD, Zulfiqar; KARABAYEV, Nurdaulet; BAUMURATOVA, Dilaram; ALI, Mushtaq (Data, Information and Computing Science, 2025)
      With the rapid expansion of industrial IoT (IIoT), maintaining robust cybersecurity is essential for the smooth operation of industrial processes. Industrial environments require adaptive solutions to effectively mitigate evolving cyber threats and protect sensitive operations. This research aims to improve the cybersecurity of industrial IoT environments. The research ...
      2026-02-23
    • Analysis of Formal Concepts for Verification of Pests and Diseases of Crops Using Machine Learning Methods 

      TUSSUPOV, JAMALBEK; YESSENOVA, MOLDIR; ABDIKERIMOVA, GULZIRA; AIMBETOV, AIDYN; BAKTYBEKOV, KAZBEK; MURZABEKOVA, GULDEN; AITIMOVA, ULZADA (IEEE Access, 2024)
      This article is devoted to a set of important areas of research: the analysis of formal representations and verification of pests and pathogens affecting crops using spectral brightness coefficients (SBR) for the period from 2021 to 2023. The database contains about 10,000 records covering the growing season, types of diseases and pests, as well as their growth phases in a ...
      2024-12-25
    • Analysis of Formal Concepts for Verification of Pests and Diseases of Crops Using Machine Learning Methods 

      TUSSUPOV, JAMALBEK; YESSENOVA, MOLDIR; ABDIKERIMOVA, GULZIRA; AIMBETOV, AIDYN; BAKTYBEKOV, KAZBEK; MURZABEKOVA, GULDEN; AITIMOVA, ULZADA (IEEE Access, 2024)
      This article is devoted to a set of important areas of research: the analysis of formal representations and verification of pests and pathogens affecting crops using spectral brightness coefficients (SBR) for the period from 2021 to 2023. The database contains about 10,000 records covering the growing season, types of diseases and pests, as well as their growth phases in a ...
      2024-11-21
    • Analysis of Formal Concepts for Verification of Pests and Diseases of Crops Using Machine Learning Methods 

      TUSSUPOV, JAMALBEK; YESSENOVA, MOLDIR; ABDIKERIMOVA, GULZIRA; AIMBETOV, AIDYN; BAKTYBEKOV, KAZBEK; MURZABEKOVA, GULDEN; AITIMOVA, ULZADA (IEEE Access, 2024)
      This article is devoted to a set of important areas of research: the analysis of formal representations and verification of pests and pathogens affecting crops using spectral brightness coefficients (SBR) for the period from 2021 to 2023. The database contains about 10,000 records covering the growing season, types of diseases and pests, as well as their growth phases in a ...
      2024-12-05
    • Analysis of Formal Concepts for Verification of Pests and Diseases of Crops Using Machine Learning Methods 

      TUSSUPOV, JAMALBEK; YESSENOVA, MOLDIR; ABDIKERIMOVA, GULZIRA; AIMBETOV, AIDYN; BAKTYBEKOV, KAZBEK; MURZABEKOVA, GULDEN; AITIMOVA, ULZADA (IEEE Access, 2024)
      This article is devoted to a set of important areas of research: the analysis of formal representations and verification of pests and pathogens affecting crops using spectral brightness coefficients (SBR) for the period from 2021 to 2023. The database contains about 10,000 records covering the growing season, types of diseases and pests, as well as their growth phases in a ...
      2026-03-13
    • Analysis of Formal Concepts for Verification of Pests and Diseases of Crops Using Machine Learning Methods 

      TUSSUPOV, JAMALBEK; YESSENOVA, MOLDIR; ABDIKERIMOVA, GULZIRA; AIMBETOV, AIDYN; BAKTYBEKOV, KAZBEK; MURZABEKOVA, GULDEN; AITIMOVA, ULZADA (IEEE Access, 2024)
      This article is devoted to a set of important areas of research: the analysis of formal representations and verification of pests and pathogens affecting crops using spectral brightness coefficients (SBR) for the period from 2021 to 2023. The database contains about 10,000 records covering the growing season, types of diseases and pests, as well as their growth phases in a ...
      2026-03-18
    • Analysis of Formal Concepts for Verification of Pests and Diseases of Crops Using Machine Learning Methods 

      TUSSUPOV, JAMALBEK; YESSENOVA, MOLDIR; ABDIKERIMOVA, GULZIRA; AIMBETOV, AIDYN; BAKTYBEKOV, KAZBEK; MURZABEKOVA, GULDEN; AITIMOVA, ULZADA (IEEE Access, 2024)
      This article is devoted to a set of important areas of research: the analysis of formal representations and verification of pests and pathogens affecting crops using spectral brightness coefficients (SBR) for the period from 2021 to 2023. The database contains about 10,000 records covering the growing season, types of diseases and pests, as well as their growth phases in a ...
      2026-03-10
    • Application of a Hybrid Model for Data Analysis in Hydroponic Systems 

      Bakirov, Kuanysh; Tussupov, Jamalbek; Tussupov, Akhmet; Shayea, Ibraheem; Shoman, Aruzhan (Technologies, 2025)
      This study presents a hybrid data analysis approach to optimize the growing conditions for beetroot and tarragon microgreens cultivated in hydroponic systems. Maintaining precise microclimate control is essential, as even minor deviations can significantly affect the yield and product quality, but traditional monitoring methods fail to adapt promptly to changing conditions. ...
      2026-03-18
    • APPLICATION OF AI AND MACHINE LEARNING TO THE THEORY OF COMPOSITE MATERIALS 

      Mityushev, V.V.; Nurtazina, K.B.; Nauryzbayev, N.Zh. (COMPOSITES THEORY AND PRACTICE, 2025)
      The homogenization for classifying composites and determining their effective properties is an important optimal design problem of material sciences studied by mathematical modeling. The application of artificial intelligence (AI) and machine learning (ML) in the theory of composite materials is discussed. One of the main problems is the choice of characteristic ML features ...
      2026-03-13

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      Евразийский национальный университет имени Л.Н. Гумилева | Научная библиотека | Контакты
      Яндекс.Метрика
      Научная библиотека | Контакты