Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
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This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
Madina Mansurova
Al-Farabi Kazakh National University
Computer Science & IT Engineering

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Development of a wearable monitor to identify stress levels using internet of things Nurassyl Zholdas; Octavian Postolache; Madina Mansurova; Baurzhan Belgibaev; Murat Kunelbayev; Talshyn Sarsembayeva
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 3: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i3.pp1486-1499

Abstract

Modern life's ubiquitous component of stress has a significant impact on many facets of human existence. This article presents the development of a wearable device integrated with internet of things (IoT) technology, aiming to identify and quantify stress levels in real-time. This technology provides a possible means of improving stress assessment, enabling prompt treatments and individualized stress management techniques. ESP32-PICO computation platform was used as part of wearable stress monitor. The developed wearable monitor also includes a high-sensitivity pulse oximeter and heart-rate sensor (MAX30102) and galvanic skin response (GSR) sensors to acquire physiological signals associated with stress status. The wearable monitor device delivers data to the firebase platform via Wi-Fi. The benefits and prospective uses of the IoT-enabled wearable device are also covered in the article. It demonstrates the mobile wearable monitor adaptability in a variety of scenarios, such as offices, classrooms, and healthcare facilities, where stress management is vita and required for activity optimization. Continuous monitoring capabilities allow users to learn about their stress levels and take proactive self-care measures. During the validation experiments, the accuracy of measurement capabilities of the developed wearable monitor were evaluated reduced errors of heart rate and respiratory rate being observed.
Random access memory page caching: a strategy for enhancing shared virtual memory multicomputer systems performance Stepan Vyazigin; Madina Mansurova; Victor Malyshkin; Aygul Shaykhulova
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1879-1892

Abstract

This study examines a modified approach to optimizing the performance of support vector machine (SVM)-type multicomputer systems through a distinct type of caching method that allocates space in the random access memory (RAM) of a computing node for caching pages. The article extensively describes research on enhancing the performance of the SVM system through memory page caching in RAM at the hardware level by implementing the SVM system based on field-programmable gate arrays (FPGA). A systematic comparative evaluation highlights a discernible enhancement in system performance relative to systems not equipped with the revised caching algorithm. These findings could prove instrumental for subsequent studies focused on optimizing the performance of SVM systems, providing empirical data to inform future investigations and potential applications in multicomputer system performance enhancement.
Research themes and trends in the field of blockchain engineering: a topic modelling analysis Dinara Zhaisanova; Madina Mansurova
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i2.pp1863-1875

Abstract

This study employed topic modeling to identify key research themes in blockchain engineering and examined how these themes have evolved over time. The dataset of collected abstracts from 3,665 relevant papers of Web of Science (WoS) core collection for the period from 2019 to 2024 was analyzed with latent Dirichlet allocation (LDA) approach. Based on the results of the topic development trends analysis, the topics collectively highlight the evolving landscape of technologies such as blockchain, smart contracts, the internet of things (IoT), and edge computing, focusing on their integration and impact across sectors like finance, healthcare, supply chain management, and energy systems. It offers valuable insights and implications for research related to blockchain engineering. Latent semantic indexing (LSI) provided further understanding by highlighting strong connections between specific topics, such as energy trading, supply chains, and medical applications. A comparison of LDA and LSI topics revealed overlapping themes, which supports the reliability of the topic structure identified by LDA.
Co-Authors Aygul Shaykhulova Baurzhan Belgibaev Dinara Zhaisanova Murat Kunelbayev Nurassyl Zholdas Octavian Postolache Stepan Vyazigin Talshyn Sarsembayeva Victor Malyshkin