Now showing items 901-920 of 5785

    • Development of an Artificial Vision for a Parallel Manipulator Using Machine‑to‑Machine Technologies 

      Nussibaliyeva, Arailym; Sergazin, Gani; Tursunbayeva, Gulzhamal; Uzbekbayev, Arman; Zhetenbayev, Nursultan; Nurgizat, Yerkebulan; Bakhtiyar, Balzhan; Orazaliyeva, Sandugash; Yussupova, Saltanat (Sensors, 2024)
      This research focuses on developing an artificial vision system for a flexible delta robot ma‑ nipulator and integrating it with machine‑to‑machine (M2M) communication to optimize real‑time device interaction. This integration aims to increase the speed of the robotic system and improve its overall performance. The proposed combination of an artificial vision system with M2M ...
      2026-03-11
    • Development of an Ankle Exoskeleton: Design, Modeling, and Testing 

      Sergazin, Gani; Ozhiken, Assylbek; Zhetenbayev, Nursultan; Ozhikenov, Kassymbek; Tursunbayeva, Gulzhamal; Nurgizat, Yerkebulan; Uzbekbayev, Arman; Ayazbay, Abu-Alim (Sensors, 2025)
      This research presents the results of conceptual design and modeling of an exoskeleton. It is intended for ankle joint rehabilitation in patients with musculoskeletal disorders. The exoskeleton design includes three screw actuators that smoothly control motion in the planes of dorsal and plantar flexion, inversion, and eversion. The results of the virtual tests performed on ...
      2026-03-11
    • Development of an algorithm for identifying the autism spectrum based on features using deep learning methods 

      Amirbay, Aizat; Mukhanova, Ayagoz; Baigabylov, Nurlan; Kudabekov, Medet; Mukhambetova, Kuralay; Baigusheva, Kanagat; Baibulova, Makbal; Ospanova, Tleugaisha (International Journal of Electrical and Computer Engineering (IJECE), 2024)
      The presented scientific work describes the results of the development and evaluation of two deep learning algorithms: long short-term memory with a convolutional neural network (LSTM+CNN) and long short-term memory with an autoencoder (LSTM+AE), designed for the diagnosis of autism spectrum disorders. The study focuses on the use of eye tracking technology to collect ...
      2026-03-11
    • Development of a Flexible Information Security Risk Model Using Machine Learning Methods and Ontologies 

      Barlybayev, Alibek; Sharipbay, Altynbek; Shakhmetova, Gulmira; Zhumadillayeva, Ainur (Applied Sciences, 2024)
      This paper presents a significant advancement in information security risk assessment by introducing a flexible and comprehensive model. The research integrates established standards, expert knowledge, machine learning, and ontological modeling to create a multifaceted approach for understanding and managing information security risks. The combination of standards and ...
      2026-03-11
    • Development of a Discrete Algorithm for Interpreting Ground-Penetrating Radar Data in Vertically Heterogeneous Media 

      Iskakov, Kazizat; Tatin, Almaz; Glazyrina, Natalya; Kussainova, Ainur; Uzakkyzy, Nurgul; Sagindykov, Kakim (Applied Sciences, 2025)
      This study presents the development of a discrete algorithm for interpreting groundpenetrating radar (GPR) data in vertically inhomogeneous media for the diagnostics of road structures. Experimental data were obtained using an OKO-2 GPR system, followed by primary radargram processing using the CartScan software. This included noise and interference filtering, as well as the ...
      2026-03-11
    • Development of a decision-making module in the field of real estate rental using machine learning methods 

      Mukhanova, Ayagoz; Baitemirov, Madiyar; Ignatovich, Artyom; Bayegizova, Aigulim; Tanirbergenov, Adilbek; Tynykulova, Assemgul; Bapiyev, Ideyat; Mukhamedrakhimova, Galiya (International Journal of Electrical and Computer Engineering (IJECE), 2024)
      The research is aimed at developing a prototype of a decision support information system for managers of a company operating in the real estate rental industry. The system provides tools for data analysis, the use of mathematical models and expert knowledge to solve complex problems. The work analyzes the practical aspects of the design and use of decision support systems ...
      2026-03-11
    • Development of a Knowledge Graph-Based Model for Recommending MOOCs to Supplement University Educational Programs in Line With Employer Requirements 

      RAMAZANOVA, VALIYA; SAMBETBAYEVA, MADINA; SERIKBAYEVA, SANDUGASH; SADIRMEKOVA, ZHANNA; YERIMBETOVA, AIGERIM (IEEE Access, 2024)
      The modern labor market demands that educational institutions prepare specialists capable of effectively responding to rapidly changing professional standards and technologies. In this regard, the use of innovative approaches to adapt educational programs has become a key factor. This study is dedicated to developing a methodology for using heterogeneous knowledge graphs to ...
      2026-03-11
    • Development of a Geographical Question-Answering System in the Kazakh Language 

      MUKANOVA, ASSEL; BARLYBAYEV, ALIBEK; NAZYROVA, AIZHAN; KUSSEPOVA, LYAZZAT; MATKARIMOV, BAKHYT; ABDIKALYK, GULNAZYM (IEEE Access, 2024)
      The study presents a detailed framework designed to develop a Question-Answering System (QA System) for the Kazakh language, highlighting its importance in the field of Low Resource Languages (LRL) Text Processing. This effort aims to fill the gap in resources for languages that lack substantial digital tools. Specifically, the project focuses on geographical questions about ...
      2026-03-11
    • Development of system for generating questions, answers, distractors using transformers 

      Barlybayev, Alibek; Matkarimov, Bakhyt (International Journal of Electrical and Computer Engineering (IJECE), 2024)
      The goal of this article is to develop a multiple-choice questions generation system that has a number of advantages, including quick scoring, consistent grading, and a short exam period. To overcome this difficulty, we suggest treating the problem of question creation as a sequence-to-sequence learning problem, where a sentence from a text passage can directly mapped to ...
      2026-03-11
    • Development of fault detection system in irrigation pumping systems using machine learning methods with consideration of energy and water consumption 

      Zholdangarova, Gulnar; Wójcik, Waldemar (JOURNAL OF ELECTRONICS AND TELECOMMUNICATIONS, 2025)
      Pumping systems play an important role in agriculture because they provide the necessary level of irrigation needed to increase crop yields. Pump malfunctions result in equipment downtime, reduced efficiency of agricultural production and significant financial losses. Thus, the development of an early fault detection and diagnosis system leveraging sensor analytic, ...
      2026-03-11
    • Development of an Artificial Vision for a Parallel Manipulator Using Machine‑to‑Machine Technologies 

      Nussibaliyeva, Arailym; Sergazin, Gani; Tursunbayeva, Gulzhamal; Uzbekbayev, Arman; Zhetenbayev, Nursultan; Nurgizat, Yerkebulan; Bakhtiyar, Balzhan; Orazaliyeva, Sandugash; Yussupova, Saltanat (Sensors, 2024)
      This research focuses on developing an artificial vision system for a flexible delta robot ma‑ nipulator and integrating it with machine‑to‑machine (M2M) communication to optimize real‑time device interaction. This integration aims to increase the speed of the robotic system and improve its overall performance. The proposed combination of an artificial vision system with M2M ...
      2026-03-11
    • Development of an Ankle Exoskeleton: Design, Modeling, and Testing 

      Sergazin, Gani; Ozhiken, Assylbek; Zhetenbayev, Nursultan; Ozhikenov, Kassymbek; Tursunbayeva, Gulzhamal; Nurgizat, Yerkebulan; Uzbekbayev, Arman; Ayazbay, Abu-Alim (Sensors, 2025)
      This research presents the results of conceptual design and modeling of an exoskeleton. It is intended for ankle joint rehabilitation in patients with musculoskeletal disorders. The exoskeleton design includes three screw actuators that smoothly control motion in the planes of dorsal and plantar flexion, inversion, and eversion. The results of the virtual tests performed on ...
      2026-03-11
    • Development and investigation of a porous metal-ceramic substrate for solid oxide fuel cells 

      Opakhai, Serikzhan; Kuterbekov, Kairat; Zeinulla, Zhasulan; Atamurotov, Farruh (International Journal of Thermofluids, 2024)
      The process of creating a porous metal-ceramic material based on Ni-Al alloy and gadolinium-doped cerium oxide (CGO) using the thermal explosion method has been investigated. This study aims to analyze the effect of CGO on the thermal explosion parameters and the architecture of the resulting Ni-Al-CGO materials. In this regard, the influence of adding CGO powder to the ...
      2026-03-11
    • Developing Teacher Digital Competence through Mobile and Interactive Technologies: A Systematic Review Using the TPACK Framework 

      Azimkhan, Shynar; Abildinova, Gulmira; Khamzina, Akmaral; Karymsakova, Anara; Karaca, Celal (International Journal of Engineering Pedagogy, 2025)
      The systematic review uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to explore the development of teacher digital competence (TDC) through various digital technologies. With an emphasis on the technological pedagogical content knowledge (TPACK) framework, the study synthesizes findings from recent peer-reviewed articles to ...
      2026-03-11
    • Design, Simulation and Functional Testing of a Novel Ankle Exoskeleton with 3DOFs 

      Sergazin, Gani; Zhetenbayev, Nursultan; Tursunbayeva, Gulzhamal; Uzbekbayev, Arman; Sarina, Aizada; Nurgizat, Yerkebulan; Nussibaliyeva, Arailym (Sensors, 2024)
      This paper presents a study on developing a new exoskeleton for ankle joint rehabilitation with three degrees of freedom (3 DOFs). The primary attention is paid to the process of designing and modelling the device aimed at restoring the lost functions of joint mobility. The authors conducted a complex analysis of the functional requirements of the exoskeleton based on research ...
      2026-03-11
    • Design of QazSL Sign Language Recognition System for Physically Impaired Individuals 

      Zholshiyeva, Lazzat; Zhukabayeva, Tamara; Baumuratova, Dilaram; Serek, Azamat (Journal of Robotics and Control (JRC), 2025)
      Automating real-time sign language translation through deep learning and machine learning techniques can greatly enhance communication between the deaf community and the wider public. This research investigates how these technologies can change the way individuals with speech impairments communicate. Despite advancements, developing accurate models for recognizing ...
      2026-03-11
    • Design of Conical Foundations with Increased Bearing Capacity in Areas of Undermined Soils 

      Zhussupbekov, Askar; Sarsembayeva, Assel; Bazarov, Baurzhan; Omarov, Abdulla (Applied Sciences, 2024)
      This article discusses the foundations of a conical shape directed with their apex downwards to increase the cross-sectional area and, accordingly, the bearing capacity during settlement and under the influence of horizontal tensile strains in undermined areas. To simulate the deformability of undermined and seismically exposed foundations, a three-dimensional expandable box ...
      2026-03-11
    • Forecasting creditworthiness in credit scoring using machine learning methods 

      Mukhanova, Ayagoz; Baitemirov, Madiyar; Amirov, Azamat; Tassuov, Bolat; Makhatova, Valentina; Kaipova, Assemgul; Makhazhanova, Ulzhan; Ospanova, Tleugaisha (International Journal of Electrical and Computer Engineering (IJECE), 2024)
      This article provides an overview of modern machine learning methods in the context of their active use in credit scoring, with particular attention to the following algorithms: light gradient boosting machine (LGBM) classifier, logistic regression (LR), linear discriminant analysis (LDA), decision tree (DT) classifier, gradient boosting classifier and extreme gradient ...
      2026-03-11
    • Fire detection using deep learning methods 

      Bayegizova, Aigulim; Abdikerimova, Gulzira; Kaliyeva, Samal; Shaikhanova, Aigul; Shangytbayeva, Gulmira; Sugurova, Laura; Sugur, Zharkynay; Saimanova, Zagira (International Journal of Electrical and Computer Engineering (IJECE), 2024)
      Fire detection is an important task in the field of safety and emergency prevention. In recent years, deep learning methods have shown high efficiency in solving various computer vision problems, including detecting objects in images. In this paper, monitoring wildfires was considered, which allows you to quickly respond to them and prevent their spread using deep learning ...
      2026-03-11
    • Exploring the synergistic effect of recycled glass fibres and agricultural waste ash on concrete strength and environmental sustainability 

      Mkilima, Timoth; Sabitov, Yerlan; Shakhmov, Zhanbolat; Abilmazhenov, Talgat; Tlegenov, Askar; Jumabayev, Atogali; Turashev, Agzhaik; Kaliyeva, Zhanar (Cleaner Engineering and Technology, 2024)
      In today’s age, finding harmony between construction endeavors and safeguarding the environment is of utmost importance. Consequently, there is a substantial requirement to explore the feasibility of utilizing waste mate rials as a replacement for traditional construction substances. Unfortunately, there is a lack of information regarding the possibilities of incorporating ...
      2026-03-11