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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Abduvalova, Ainur
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Computer Science & IT Electrical & Electronics Engineering

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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 (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3064-3072

Abstract

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 analyze a huge number of scientific publications relevant to the software being modeled. The process of ontology replenishing with information from a huge number of scientific publications can be facilitated and accelerated through the use of lexical-syntactic patterns of ontological design. In this paper, we consider the possibility of automated construction of scientific subject area ontologies based on a heterogeneous patterns system of ontological design. This system includes ontological design patterns and is intended for ontology developers. System also includes automatically built lexical and syntactic patterns, which help to automatic replenishment of the ontology with information extracted from natural language texts.
An internet of things-enabled wearable device for stress monitoring and control Tyulepberdinova, Gulnur; Abduvalova, Ainur; Kunelbayev, Murat; Amirkhanova, Gulshat; Adilzhanova, Saltanat
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9599

Abstract

The development of a wearable sensor device integrated into the internet of things (IoT) infrastructure is presented, with functionality aimed at continuous measurement of the user's physiological parameters and their intelligent processing for real-time stress level assessment. The system enables continuous monitoring of physiological parameters, allowing early detection of stress signals and supporting adaptive behavioral responses. The hardware platform is designed to consolidate various biomedical sensors, enabling continuous acquisition and intelligent processing of physiological data in real time. During testing, heart rate (HR) ranged from 68 to 89 beats per minute (bpm), respiratory rate varied from 11 to 15 breaths per minute, and skin conductivity ranged from 63 to 77 µS. Acquired physiological data were uploaded to a cloud-based infrastructure to enable advanced processing and analysis. The system achieved an overall stress detection accuracy of 87%, and signal stability remained high even under changing conditions. The proposed wearable solution demonstrates strong potential for use in healthcare, education, and occupational environments. It also offers scalability through the integration of intelligent algorithms and additional sensor modules.
Co-Authors Adilzhanova, Saltanat Akhmetzhanova, Shynar Altynbekova, Zhanar Amirkhanova, Gulshat Kunelbayev, Murat Makhatova, Valentina Murzakhmetov, Aslanbek Sadirmekova, Zhanna Serikbayeva, Sandugash Tasbolatuly, Nurbolat Tyulepberdinova, Gulnur