Current Problems of Applied Mathematics and Computer Systems
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This book based on the best papers accepted for presentation during the International Conference on Current Problems of Applied Mathematics and Computer Systems (CPAMCS-2024), Russia. This book includes research focused on contemporary mathematical challenges and their resolutions within scientific computing, data analysis and modular computing. This book presents original studies on numerical methods in scientific computing, optimization problem-solving, function approximation techniques, among other topics. Furthermore, it encompasses research contributions in data analysis and modular…mehr

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Produktbeschreibung
This book based on the best papers accepted for presentation during the International Conference on Current Problems of Applied Mathematics and Computer Systems (CPAMCS-2024), Russia. This book includes research focused on contemporary mathematical challenges and their resolutions within scientific computing, data analysis and modular computing. This book presents original studies on numerical methods in scientific computing, optimization problem-solving, function approximation techniques, among other topics. Furthermore, it encompasses research contributions in data analysis and modular computing, highlighting advancements in deep learning, neural networks, mathematical statistics, machine learning techniques, residue number systems and artificial intelligence. Additionally, this book addresses critical issues in mathematical education. This book intends for professionals engaged in scientific computing, parallel computing, computer technology, machine learning, information security, and mathematics education.
Autorenporträt
Anatoly Alikhanov has obtained his Ph.D. in Physical and Mathematical Sciences and currently holds the position of Professor, Vice-Rector for Scientific and Research Work and the Head of the Regional Scientific and Educational Mathematical Center “North Caucasian Center for Mathematical Research” at North-Caucasus Federal University, Stavropol, Russia. Alikhanov has an extensive publication record, with publications in high-ranked journals. His academic excellence has been recognized in “The Single Recent Year Data Ranking of World’s Top 2% Scientists,” compiled by Stanford University, for the years 2019 through 2023. He previously served as a Visiting Member of the Dissertation Council at the Department of Mathematics, Southeast University, Nanjing, China. In 2016 and 2023, he was invited to undertake internships at Nanjing University, focusing on numerical methods for solving fractional differential equations. Dmitrii Kaplun is Ph.D. (2009), Associate Professor (2015), Lead Researcher at Saint Petersburg Electrotechnical University “LETI” (Saint Petersburg, Russia), Full Professor (2023) at China University of Mining and Technology (Xuzhou, China). In 2009 he defended his PhD thesis in computer science at Saint Petersburg Electrotechnical University “LETI.” The current research and academic work are related to digital signal and image processing, embedded and reconfigurable systems, computer vision and machine learning. Author of more than 150 papers in journals and conference proceedings. Kaplun has been an Editorial Board Member for Scientific Reports since 2022 and Associate Editor for Industrial Artificial Intelligence journal since 2023. Pavel Lyakhov received the degree in mathematics from Stavropol State University, in 2009, and the Ph.D. degree in physical and mathematical sciences, in 2012. Currently, he is the Head of the Department of Mathematical Modeling, North-Caucasus Federal University. He is the author of more than 170 scientific articles and the holder of 28 copyright certificates and patents. His research interests include high-performance computing, residual class system arithmetic, machine learning, artificial intelligence, and medical imaging. Aslan Apekov has obtained his Ph.D. in Physical and Mathematical Sciences. He is the Deputy Director for Research at the North-Caucasus Center for Mathematical Research and the Head of the Computational Methods Department at the North-Caucasus Federal University. He received a PhD in Condensed Matter Physics. He supervised applied research on the topic of Development and Study of Image Reconstruction Methods for a Multifunctional X-ray Diagnostic Complex with Digital Tomosynthesis Function. His research interests include the physics of interphase phenomena, mathematical modeling of physical processes, and computational physics.  Irina Samoylenko is Ph.D., Associate Professor at Informational Systems Department, Stavropol State Agrarian University, Russia. She received M.S. degree in Applied Mathematics and Informatics, Ph.D. in System Analysis, Control and Processing of Information in North-Caucasus Federal University. She is a member of Association of Scientific Editors and Publishers, Russia. She participated in international conferences and internships in Italy, Turkey, Romania, Serbia and Czech Republic. Her research interests include wireless sensor networks, optimization tasks, IoT in agriculture. Irina has been an Editor of various international conferences from publishing houses including Springer, Institute of Physics, American Institute of Physics etc. She has publications in reputed international journals, such as Ad-Hoc, Computers and Electronics in Agriculture, Computer Communications.