Defense of the dissertation of Муканова Жанна Аскаровна for the degree of Doctor of Philosophy (PhD) in the specialty «6D070400 - Есептеу техникасы және бағдарламалық қамтамасыз ету»
L.N. Gumilyov Eurasian National University, a dissertation defense for the degree of Doctor of Philosophy (PhD) by Муканова Жанна Аскаровна on the topic «Development of a hardware-software system of high-frequency scanning with intelligent data processing» by specialty «6D070400 – Есептеу техникасы және бағдарламалық қамтамасыз ету».
The dissertation was carried out at the «Computer and Software Engineering» of L.N. Gumilyov Eurasian National University.
The language of defense is russian
Official reviewers:
Kalimoldaev Maksat Nuradilovich – Doctor of Physical and Mathematical Sciences, professor, Advisor to the General Director of RSE «Institute of Information and Computational Technologies» of the Science Committee of MSHE RK, specialty: 05.13.16 - Application of Computer Technology, Mathematical Modeling, and Mathematical Methods in Scientific Research (Almaty, Republic of Kazakhstan).
Beloshchitsky Andrey Alexandrovich – Doctor of Technical Sciences, professor, Vice-rector for Science and Innovation, Astana IT University, specialty: 05.13.22 - Project and Program Management (Astana, Republic of Kazakhstan).
Temporary members of the dissertation council:
Matkarimov Bakhyt Turganbayevich – Doctor of Technical Sciences, professor, leading researcher, Private Institution «National laboratory Astana», Nazarbayev university, specialty: 05.13.15 - Computing Machines and Systems (Astana, Republic of Kazakhstan).
Ismailova Aisulu Abzhapparovna - Doctor of Philosophy (PhD), associate professor, S. Seyfullin Kazakh agrotechnical research university, specialty: 6D070300 - Information Systems (Astana, Republic of Kazakhstan).
Akhmetzhanov Maksat Akanovich - Doctor of Philosophy (PhD), acting associate professor of the Department of Mathematical and Computer Modeling, al-Farabi Kazakh national university, specialty: 6D070500 - Mathematical and Computer Modeling (Almaty, Republic of Kazakhstan), instead of Yedilkhan Didar - Doctor of Philosophy (PhD), associate professor, Director of SIC Smart City, Astana IT University, specialty: 6D070400- Computer Science and Software (Astana, Republic of Kazakhstan), according to the decision of the Dissertation Council of the L.N. Gumilyov Eurasian Nnational university in the field of personnel training 8D061 - Information and Communication Technologies", educational programs: OP "6D070400 - Computer Science and Software", "8D06104 - Computer Science and Software" (Protocol No. 3 dated July 31, 2024).
Shomanov Aday– Doctor of Philosophy (PhD), Instructor, School of Engineering and Digital Sciences, Nazarbayev university, specialty: 6D060200 - Computer Science (Astana, Republic of Kazakhstan).
Scientific consultants:
Atanov Sabyrzhan Kubeisinovich – Doctor of Technical Sciences, Professor of the Department of Computer and Software Engineering, L.N. Gumilyov Eurasian national university, specialty: 05.13.11 - Mathematical and software support of computing machines, complexes and computer networks (Astana, Republic of Kazakhstan).
Mohammad Jamshidi - Doctor of Philosophy (PhD), professor of the Department of Electrical and Computer Engineering, the University of Texas San Antonio (Texas 78249, USA).
The defense will take place on August 23, 2024, at 01:00 PM in the Dissertation Council for the training direction «8D061 – Information and communication technologies» in the specialty «6D070400 – Computer engineering and software» of L.N. Gumilyov Eurasian National University. The Dissertation council meeting will be held offline and online on the Microsoft Teams.
Address: Astana, A. Pushkin str., 11, auditorium 222.
Abstract (English): ANNOTATION dissertation work of Mukanova Zhanna Askarovna "Development of hardware-software system of high-frequency scanning with intelligent data processing", submitted for the degree of Doctor of Philosophy (PhD) in the specialty "6D070400 - Computer Science and Software" Relevance of the research topic. With the growth of technological processes in the modern world, the number of industrial plants is increasing and their safety level must meet high standards. In order to comply with safety and fire regulations, factories and enterprises must be equipped with automatically operating gas analyzers that give an alarm signal (light or sound) in advance, i.e. before reaching the gas level corresponding to the lower concentration limit of ignition. Gaseous pollutants with characteristics of easy diffusion, difficulty of detection and harsh treatment have become some of the most harmful pollutants to human health among all industrial wastes. There are many trace gases in the atmosphere, such as ozone (O3), methane (CH4), carbon monoxide (CO), nitrogen dioxide (NO2), hydrogen sulfide (H2S) and sulfur dioxide (SO2), which exist with a certain concentration and maintain a certain dynamic balance. Constant emissions of polluting gases from industry, power generation, and automobile exhaust emissions gradually lead to a decrease in the concentration of gas in the atmospheric environment. As a consequence, there are increasing air pollution problems such as the greenhouse effect and various lung diseases. For example, Shwetha et al. in their paper "MEMS based metal oxide semiconductor carbon dioxide gas sensor" write that carbon dioxide (CO2) has harmful effects on the ecosystem by causing acid rain, increasing global temperature and ultimately affecting human health. Therefore, CO2 has traditionally been considered one of the most serious atmospheric pollutants. Yin, Gao, Miao et al. in their paper "Near-infrared laser photoacoustic gas sensor for simultaneous detection of CO and H2S" note that hydrogen sulfide affects the biological process of cellular oxidation and blocks cellular respiration, which eventually leads to cell suffocation and hypoxia. Methane gas is the main component of natural gas, and it is closely related to people's daily activities and lives. Methane is also flammable, poisonous and explosive, so it is important to accurately determine the presence and concentration of methane in the air. Concentrations of hazardous gas mixtures in the air of the working area pose a serious risk to working conditions. Such mixtures can have a harmful effect on human health, and can also contribute to fires and explosions. Analysis of statistical data on occupational injuries in the Republic of Kazakhstan shows that the main leading industries with the highest rates of occupational injuries for the period from 2012-2022 are stably the manufacturing, mining and construction industries. This is primarily due to the fact that these enterprises use mostly labor resources and manual labor, which mainly determine the level of occupational injuries, which confirms their unfavorable working conditions in terms of injury safety. Enterprises of manufacturing, mining and construction industries, which are also places of increased danger, where there is a high probability of accumulation of hazardous gases in the premises. Thus, the largest number of victims at work from year to year is observed in Karaganda, East Kazakhstan, Pavlodar and Kostanay regions, these regions on average for 10 years accounted for slightly less than 50% of the total number of victims in the country. Timely detection of combustible gases and vapors in the air of industrial premises and industrial area in concentrations much lower than explosive concentrations and their localization is an important task for compliance with safety and fire regulations. One of the proposed recommendations to improve the current situation is the research and development of new air pollution monitoring methods to provide a more accurate and efficient assessment of air pollution levels. Currently, there are a number of studies on the application of artificial intelligence system in gas analysis of gas-air mixtures. However, this topic is poorly understood and research is mainly focused on determining the concentration of hazardous gases rather than its identification. The aim of the thesis research is to develop a software and hardware system of high-frequency scanning with intelligent data processing for practical industrial and manufacturing tasks. Objectives of the study: Selection and optimization of the gas detection method based on the review and study of publications on the topic of work. Development of functional circuitry on different hardware solutions. Development of methods and software implementation of algorithms for smoothing raw data. Development of methods and algorithm for determining the spectral composition of gas with a gas analyzer using an artificial neural network (ANN). Patent protection of the obtained hardware and software solutions. Publication of research results in international peer-reviewed scientific publications, journals recommended the Committee for Quality Assurance in Education and Science, in the proceedings of international conferences. The objects of the study are: wave processes in gas media and numerical methods for determining the parameters of gas mixtures in air. The subjects of the study are models, methods and algorithms for determining the concentrations of hazardous and poisonous gases in gas-air mixtures. Research Methods. In the course of the thesis research various methods were used, such as synthesis and analysis of the works of foreign and domestic researchers in the field of wave processes and the development of gas analytical systems for the detection of hazardous gas mixtures in the air environment. Theories of high-frequency electromagnetic radiation, theories and practices of artificial intelligence system development and object-oriented programming were also studied. Microsoft Visual Studio, MatLab and Google Colab software packages were actively used during the research. The main theoretical provisions and conclusions are confirmed by the results of experimental studies in laboratory conditions at the stages of development. The scientific novelty of the results consists of the following: 1. A method of gas estimation based on the joint analysis of infrared electromagnetic waves and acoustic signals is proposed. 2. A method of gas analysis based on broadband scanning of high-frequency electromagnetic signals ranging from infrared to ultraviolet is proposed. 3. A method of multispectral analysis of gas mixtures with intelligent processing of high-frequency data based on neural networks is proposed. The main provisions for defense: 1. Method of gas estimation based on joint analysis of infrared electromagnetic waves and acoustic signals. 2. Method of gas analysis based on broadband scanning of high-frequency electromagnetic signals in the range from infrared to ultraviolet radiation. 3. method of multispectral analysis of gas mixtures with intelligent processing of high-frequency data based on neural networks. Practical relevance: The proposed methods can be used in the development of a simple and budgetary device that allows rapid rapid rapid test of air mixtures for the presence of hazardous gases. The technical result of the presented schemes of the gas analyzer is an increase in the accuracy of measuring the concentration of gas compounds due to the use of a combination of spectral sensors and pressure and temperature sensors. The results of the study are implemented in the educational process of Karaganda Technical University named after A. Saginov for students of the educational program "Information Security Systems" within the discipline "Expert and Intelligent Systems", as well as the University "Turan" within the discipline "Artificial Intelligence Systems" for students of the educational program "Computer Science and Software". Also, the method of intelligent analysis of chemical air pollution described in patent No. 8288 «Intelligent gas analyzer» (publication date – 07/21/2023) was used in carrying out research tasks under the program of targeted financing of the Ministry of Internal Affairs of the Republic of Kazakhstan BR218005/0223 «Development of an automated exploration process for a robotic reconnaissance and attack marine unmanned modular type boat». Approbation of the results of the dissertation. The main results of the dissertation work were reported at seminars of L.N. Gumilev Eurasian National University, at international conferences: 1. Seminars of doctoral students of the Department of Computer and Software Engineering, Astana, 2019-2021. 2. International Scientific and Practical Conference "VIII Global Science and Innovation 2020: Central Asia", Nur-Sultan, 2020. 3. 2021 IEEE International Conference on Intelligent Information Systems and Technologies (SIST 2021), Nur-Sultan, 2021. 4. 7th International Conference on Digital Technologies in Education, Science and Industry (DTESI 2022), Almaty, 2022. 5. International Scientific Workshop "Information Technologies in Science, Technology and Education", Aktobe, 2023. Publications published based on the results of the study, including: - In scientific journals indexed in Web of Science and Scopus: 1. Mukanova Z., Atanov S., Jamshidi M. Intelligent Hardware-Software Processing of High-Frequency Scanning Data //Journal of Robotics and Control (JRC). – 2023. – Т. 4. – №. 5. – pp. 600-611. - In Proceedings of International Conferences Indexed in Scopus: 1. Z. Mukanova, S. Atanov, M. Jamshidi, "Features of Hardware and Software Smoothing of Experimental Data of Gas Sensors," 2021 IEEE International Conference on Smart Information Systems and Technologies (SIST), 2021, pp. 1-6. - Articles published in scientific journals recommended by Committee for Quality Assurance in the Sphere of Education and Science of the MES RK: 1. Муканова Ж.А. Технология электромагнитного сканирования сред // Bulletin of Science of Kostanay socio-technical university named after academician Z. Aldamzhar. - Kostanai 2018. - № 4. – pp. 95-99. 2. Муканова Ж.А., Атанов С.К. Программная реализация алгоритмов обработки зашумленных данных. // Bulletin of S. Toraigyrov Pavlodar State University. Series: Energy Series. - Pavlodar: PSU. - 2020. - №. 1. - pp. 87-94. 3. Муканова Ж.А., Атанов С.К. Высокочастотное сканирование с интеллектуальной обработкой данных для военного применения. // Scientific journal "SARDAR". - JSC Center for Military Strategic Studies. - 2023. - №. 3 (43). - pp. 81-91. 4. Муканова Ж.А., Атанов С.К. Разработка модели нейронной сети для анализа газовых смесей. // Bulletin of KazATC. – Almaty: KazATC. – 2024. – №. 3 (123). – pp. 350-360. - In the proceedings of international conferences: 1. Муканова Ж.А., Атанов С.К. Выбор метода обнаружения газов при проектировании газоанализатора. // International Scientific and Practical Journal "VIII Global Science and Innovation 2020: Central Asia" No. 3(3), Nur-Sultan, 2020. pp. 153-156. 2. Mukanova Z., Atanov S., Baydeldinov M. Development of the Multispectral Microcontroller System for Analyzing Air Quality for the Presence of the Hazardous Gas Mixtures. 7th International Conference on Digital Technologies in Education, Science and Industry, DTESI 2022 – Almaty, 2022. – pp. 56-62. - Patents, certificate of state registration for copyright object,: 1. Gas analyzer. Patent No. 5141, 2020. Date of publication -10.07.2020. 2. Intelligent gas analyzer. Patent No. 8288, 2023. Date of publication -21.07.2023. 3. Computer program: Program for adaptive smoothing of navigation system data. Certificate of Inclusion of Information in the State Register of Rights to Copyrighted Objects No. 11096 dated June 23, 2020. Structure of the work. The work consists of the content, definitions and abbreviations, introduction, four chapters including seventeen subsections, conclusion, list of sources used, appendices. The work is printed on 122 pages, with the use of computer capabilities of emphasis in the form of illustrations, diagrams and tables. The list of references consists of 91 titles. The author expresses his deep gratitude to his supervisor, Professor of the Department of "Computer and Software Engineering", Dr. Atanov Sabyrzhan Kubeysinovich and foreign consultant, Professor, PhD University of Texas at San Antonio (USA) Jamshidi Mohamad for invaluable work and advice during the study.
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