Computer Science: Недавние поступления

  • Data generation using generative adversarial networks to increase data volume 
    Aitimova, Ulzada; Aitimov, Murat; Mukhametzhanova, Bigul; Issakulova, Zhanat; Kassymova, Akmaral; Ismailova, Aisulu; Kadirkulov, Kuanysh; Zhumabayeva, Assel (International Journal of Electrical and Computer Engineering, 2024)
    The article is an in-depth analysis of two leading approaches in the field of generative modeling: generative adversarial networks (GANs) and the pixelto-pixel (Pix2Pix) image translation model. Given the growing interest ...
  • Cybersecurity Risk Assessments within Critical Infrastructure Social Networks 
    Aktayeva, Alimbubi; Makatov, Yerkhan; Kubigenova, Akku Tulegenovna; Dautov, Aibek; Niyazova, Rozamgul; Zhamankarin, Maxud; Khan, Sergey (Data, 2023)
    Cybersecurity social networking is a new scientific and engineering discipline that was interdisciplinary in its early days, but is now transdisciplinary. The issues of reviewing and analyzing of principal tasks related ...
  • Cyberbullying-related Hate Speech Detection Using Shallow-to-deep Learning 
    Sultan, Daniyar; Toktarova, Aigerim; Zhumadillayeva, Ainur; Aldeshov, Sapargali; Mussiraliyeva, Shynar; Beissenova, Gulbakhram; Tursynbayev, Abay; Baenova, Gulmira; Imanbayeva, Aigul (Computers, Materials & Continua, 2023)
    Communication in society had developed within cultural and geographical boundaries prior to the invention of digital technology. The latest advancements in communication technology have significantly surpassed the ...
  • Control of Telecommunication Network Parameters under Conditions of Uncertainty of the Impact of Destabilizing Factors 
    Kozlovskyi, Valerii; Shvets, Ivan; Lysetskyi, Yurii; Karpinski, Mikolaj; Shaikhanova, Aigul; Shangytbayeva, Gulmira (Information, 2024)
    The classification of the natural and anthropogenic destabilizing factors of a telecommunications network as a complex system is presented herein. This research shows that to evaluate the parameters of a telecommunications ...
  • Controlling Matter-Wave Smooth Positons in Bose–Einstein Condensates 
    Manikandan, Kannan; Serikbayev, Nurzhan; Vijayasree, Shunmuganathan P.; Aravinthan, Devarasu (Symmetry, 2023)
    In this investigation, we explore the existence and intriguing features of matter-wave smooth positons in a non-autonomous one-dimensional Bose–Einstein condensate (BEC) system with attractive interatomic interactions. ...
  • Continuous Sign Language Recognition and Its Translation into Intonation-Colored Speech 
    Amangeldy, Nurzada; Ukenova, Aru; Bekmanova, Gulmira; Razakhova, Bibigul; Milosz, Marek; Kudubayeva, Saule (Sensors, 2023)
    This article is devoted to solving the problem of converting sign language into a consistent text with intonation markup for subsequent voice synthesis of sign phrases by speech with intonation. The paper proposes an ...
  • Construction of a Model and Development of an Algorithm for Solving the Wave Problem under Pulsed Loading 
    Khabdolda, Bolat; Zhuzbayev; Sabitova, Diana; Aitkenova, Ailazzat A; Serikbayeva, Sandugash; Badekova, Karakoz Zh; Yerzhanova, Akbota Y (International Journal of Advanced Computer Science and Applications, 2021)
    The article considers approaches and methods for modeling the wave process resulting from blasting operations. The analysis of modeling methods has shown that in the context of the task it is advisable to conduct a study ...
  • CONCURRENTLY CONTROLLED GRAMMARS 
    Mavlankulov, Gairatzhan; Othman, Mohamed; Turaev, Sherzod; Selamat, Mohd Hasan; Zhumabayeva, Laula; Zhukabayeva, Tamara (KYBERNETIKA, 2018)
    This paper introduces a new variant of Petri net controlled grammars, namely a concurrently controlled grammar, where the control over the application of the productions of a grammar is realized by a Petri net with ...
  • Conceptual Model for Automatic Proofreading of Technical Documents 
    Ixebayeva, Zhanna S.; Jetpisov, Kabylda; Medeshova, Aigul B.; Kassymova, Akmaral Kh. (Revue d'Intelligence Artificielle, 2023)
    This study deals with a set of issues related to the development of a conceptual model for automatic proofreading of technical documentation. The purpose of this study is to investigate the prospects for creating the ...
  • APPROACH TO THE SYNTHESIS OF AN APERIODIC ROBUST AUTOMATIC CONTROL SYSTEM BASED ON THE GRADIENT-SPEED METHOD OF LYAPUNOV VECTOR FUNCTIONS 
    Beisenbi, Мamyrbek; Kaliyeva, Samal (Eastern-European Journal of Enterprise Technologies, 2023)
    One of the actual problems for the theory and practice of control of dynamic objects is the development of methods for research and synthesis of control systems of multidimensional objects. The paper proposes a universal ...
  • Approach to automating the construction and completion of ontologies in a scientific subject field 
    Sadirmekova, Zhanna; Murzakhmetov, Aslanbek; Abduvalova, Ainur; Altynbekova, Zhanar; Makhatova, Valentina; Akhmetzhanova, Shynar; Tasbolatuly, Nurbolat; Serikbayeva, Sandugash (International Journal of Electrical and Computer Engineering, 2024)
    Domain ontologies facilitate the organization, sharing, and reuse of subject areas. Building a software ontology is labor-intensive and time-consuming. In the process of obtaining a software ontology, it is required to ...
  • Applying textural Law’s masks to images using machine learning 
    Abdikerimova, Gulzira; Yessenova, Moldir; Yerzhanova, Akbota; Manbetova, Zhanat; Murzabekova, Gulden; Kaibassova, Dinara; Bekbayeva, Roza; Aldashova, Madina (International Journal of Electrical and Computer Engineering, 2023)
    Currently, artificial neural networks are experiencing a rebirth, which is primarily due to the increase in the computing power of modern computers and the emergence of very large training data sets available in ...
  • APPLYING MACHINE LEARNING TO IMPROVE A TEXTURE TYPE IMAGE 
    Tussupov, Jamalbek; Kozhabai, Kairat; Bayegizova, Aigulim; Kassenova, Leila; Manbetova, Zhanat; Glazyrina, Natalya; Mukhamedi, Bersugir; Yeginbayev, Miras (Eastern-European Journal of Enterprise Technologies, 2023)
    The paper is devoted to machine learning methods that focus on texture-type image enhancements, namely the improvement of objects in images. The aim of the study is to develop algorithms for improving images and to determine ...
  • Application of the Clahe Method Contrast Enhancement of X-Ray Images 
    Omarova, G. S; Aitkozha, Zh.Zh; Nuridinov, O; Starovoitov, V.V; Bekbolatov, S; Ostayeva, A.B (International Journal of Advanced Computer Science and Applications, 2022)
    Due to the nonlinearity of the luminance function produced by many medical recording devices, the quality of medical images deteriorates, which creates problems in the visual research work of physicians. X-rays can be ...
  • Application of Multicriteria Methods for Improvement of Information Security Metrics 
    Abdiraman, Aliya; Goranin, Nikolaj; Balevicius, Simas; Nurusheva, Assel; Tumasoniene˙, Inga (Sustainability, 2023)
    Metrics are a set of numbers that are used to obtain information about the operation of a process or system. In our case, metrics are used to assess the level of information security of information and communication ...
  • Application of informative textural Law’s masks methods for processing space images 
    Yessenova, Moldir; Abdikerimova, Gulzira; Murzabekova, Gulden; Kakabayev, Nurbol; Glazyrina, Natalya; Adikanova, Saltanat; Uzakkyzy, Nurgul; Sadirmekova, Zhanna B.; Niyazova, Rozamgul (International Journal of Electrical and Computer Engineering, 2023)
    Image processing systems are currently used to solve many applied problems. The article is devoted to the identification of negative factors affecting the growth of grain in different periods of harvesting, using a program ...
  • Application of deep learning methods for automated analysis of retinal structures in ophthalmology 
    Kassymova, Akmaral; Konyrkhanova, Assem; Issembayeva, Aida; Saimanova, Zagira; Saltayev, Alisher; Ongarbayeva, Maral; Issakova, Gulnur (International Journal of Electrical and Computer Engineering, 2024)
    This article examines a current area of research in the field of ophthalmology the use of deep learning methods for automated analysis of retinal structures. This work explores the use of deep learning methods such as ...
  • Application for Creating and Analyzing Competency-Based Curricula Using an Ontological Approach 
    NAZYROVA, AIZHAN; MILOSZ, MAREK; MUKANOVA, ASSEL; BEKMANOVA, GULMIRA; KUZIN, DMITRII; ALJAWARNEH, SHADI (IEEE Access, 2024)
    This article describes the development and implementation of cutting-edge software for creating, modifying, and analyzing curriculum plans based on a competency-based approach, structured in the form of ontologies. The ...
  • A New Approach to Solving the Problem of Atmospheric Air Pollution in the Industrial City 
    Oralbekova, Zhanar; Zhukabayeva, Tamara; Iskakov, Kazizat; Zhartybayeva, Makpal; Yessimova, Nargiz; Zakirova, Alma; Kussainova, Ainur (Hindawi Scientific Programming, 2021)
    In order to ensure optimal operation of the existing environmental monitoring information system, it has become essential to use mathematical modeling based on the data assimilation algorithm. In this paper, a data ...
  • Analyzing Disease and Pest Dynamics in Steppe Crop Using Structured Data 
    TUSSUPOV, JAMALBEK; ABDIKERIMOVA, GULZIRA; ISMAILOVA, AISULU; KASSYMOVA, AKMARAL; BELDEUBAYEVA, ZHANAR; AITIMOV, MURAT; MAKULOV, KAIYRBEK (IEEE Access, 2024)
    In this study, an analysis of the spectral brightness coefficients (SBC) of agricultural crops in the steppe regions of Kazakhstan was carried out using remote field and space measurements during the growing season. The ...

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