Mathematical Modeling, Applied Analysis and Computational Methods : ICAIM-2023, Greater Noida, India, March 24-26
Idioma: inglés
Editorial: Springer, 2025
Serie: Libro 403 de 464 - Springer Proceedings in Mathematics & Statistics
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Druck auf Anfrage Neuware - Printed after ordering - This volume presents a curated selection of papers presentedat the International Conference on Applied and Industrial Mathematics (ICAIM 2023), hosted by Sharda University in Greater Noida, Uttar Pradesh, India, from 24-26March 2023. It delves into diverse realms of mathematical modelling, applied analyses, computational methods and industrial mathematics. Each chapter within this collection offers intriguing insights into tackling real-world challenges through the lens of mathematical modelling and computational approaches. The book traverses an array of compelling subjects from safeguarding secrets through specialized codes to optimizing solar energy utilization. It illuminates how mathematics is potent in unravelling intricate problems, such as understanding disease propagation or enhancing machine learning algorithms. Through lucid explanations and engaging examples, this volume is tailored for curious minds eager to delve into the marvels of mathematics from fresh perspectives.…
N° de ref. del artículo 9789819634590
- Título
- Mathematical Modeling, Applied Analysis and Computational Methods : ICAIM-2023, Greater Noida, India, March 24-26
- Autor
- Yeliz Karaca
- Editorial
- Springer
- Año de publicación
- 2025
- Estado
- Neu
- Encuadernación
- Buch
- Idioma
- inglés
- ISBN 10
- 9819634598
- ISBN 13
- 9789819634590
- Peso del artículo
- 670 gramos
- Dimensiones
- 241x160x21 mm
- Serie
- Libro 403 de 464: Springer Proceedings in Mathematics & Statistics
This volume presents a curated selection of papers presented at the International Conference on Applied and Industrial Mathematics (ICAIM 2023), hosted by Sharda University in Greater Noida, Uttar Pradesh, India, from 24-26 March 2023. It delves into diverse realms of mathematical modelling, applied analyses, computational methods and industrial mathematics. Each chapter within this collection offers intriguing insights into tackling real-world challenges through the lens of mathematical modelling and computational approaches. The book traverses an array of compelling subjects from safeguarding secrets through specialized codes to optimizing solar energy utilization. It illuminates how mathematics is potent in unravelling intricate problems, such as understanding disease propagation or enhancing machine learning algorithms. Through lucid explanations and engaging examples, this volume is tailored for curious minds eager to delve into the marvels of mathematics from fresh perspectives.
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Acerca del autor
Ayub Khan is Professor and Head of the Department of Mathematics, Jamia Millia Islamia, New Delhi, India. Earlier, he held the position of Pro Vice-Chancellor and Vice-Chancellor (in-charge) of Maulana Azad National Urdu University, Hyderabad, Telangana, India. He was the first aluminus of the University of Delhi to hold a Ph.D. degree in nonlinear dynamical system. He completed his Ph.D. degree from the University of Delhi in 1995 on the topic “Chaos in Nonlinear Planar Oscillations of a Satellite in Elliptic Orbits”. His research work was online to NEP 2020 even in 1995. With more than 165 research papers published in several journals of repute, he has supervised 23 Ph.D. and 12 M.Tech. students. A member of different academic bodies in the country, he has delivered a number of lectures at different forum and conferences.
R. C. Singh is Professor of Physics, Director National and International Ranking, Advisor of the Learning Resource Centre (Central Library), and Director of Online Education at Sharda University, Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, India. He earned his Ph.D. degree in theoretical condensed matter physics, B.Sc. (Hons.) and M.Sc. degrees in physics from Banaras Hindu University, Varanasi, Uttar Pradesh, India. With more than 70 research papers and several book chapters published in peer-reviewed international journals and conference proceedings, he has an impressive publication record. He has also authored one book and co-edited three books, in addition to eleven conference proceedings. Under his guidance, five research students have successfully obtained their doctorate degrees, while five more research fellows are currently carrying out their research work under his mentorship. A reviewer for several international journals and actively participates in national and international conferences, seminars, workshops and short-term courses, he successfully completed three research projects that were sponsored by the Department of Science and Technology (the Government of India), New Delhi, with 3 patents granted and 6 patents published in collaboration with his colleagues.
Khursheed Alam is Professor and Head of the Department of Mathematics, Sharda University, Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, India. He also is Coordinator of The A.H. Siddiqi Centre for Advance Research in Applied Mathematics and Physics (CARAMP), School of Basic Sciences & Research at Sharda University. He obtained his M.Sc. and Ph.D. degree in mathematics in the year 1999 and 2005, respectively, from Jamia Millia Islamia, New Delhi. He is associated with the Sharda Group of Institutions (SGI), since July 2006. With more than 17 years of teaching experience and research, his research area is fractals using wavelet, image processing, nonlinear dynamical systems and chaos theory.
With more than 43 research papers in many Scopus- and SCI-indexed journals, he is the recipient of the Academic Excellence Awards 2021 for the Best Performer in Learning and Development, received at the International Conference and the Academic Excellence Award on Recent Innovation and Interdisciplinary Research and Global Academic Excellence Awards 2021 for the Best Young Scientist, received in National Conference & Academic Excellence Award on Recent Innovation and Interdisciplinary Research. He has published 6 books and many book chapters.
Yeliz Karaca is an Associate Professor of Mathematics, and a Researcher Professor at the University of Massachusetts (UMass) Chan Medical School, Worcester, USA. She received her Ph.D. degree in Mathematics in 2012. Along with the other awards she has been conferred, she was granted the Cooperation in Neurological Sciences and Support Award by Turkish Neurology Association as the first mathematician in Türkiye. She also holds a medical card as the only mathematician entitled for it. Furthermore, she received the Outstanding Young Scientist Award in 2012 and Best Paper Awards in her specialized discipline, among the other national and international awards in different categories as well as grants. Another award of hers is Outstanding Reviewer Award (Mathematics Journal, MDPI) in 2021.
Editor-in-Chief of the book series Systems Science & Nonlinear Intelligence Dynamics, Dr. Karaca has been acting as the Lead Editor, Editor and Associate Editor in many SCI-indexed journals. She has been the leading Guest Editor of several special issues, including “Fractals-Fractional AI-Based Analyses and Applications to Complex Systems (Parts IV, III, II, I)” in Fractals Journal. She also has active involvement with diverse projects, some of which are the Institute of Electrical and Electronics Engineers (IEEE, as senior member), the Organization for Women in Science for the Developing World (OWSD); Complex Human Adaptive Organizations and Systems (CHAOS), University of Perugia, Italy; International Engineering and Technology Institute (IETI, as the member of Board of Director). Her research interests include complex systems sciences with applications in various terrains, applied mathematics, advanced computational methods, AI applications, computational complexity, fractional calculus, fractional quantum calculus, fractals and multifractals, stochastic processes, different kinds of differential and difference equations, discrete mathematics, algebraic complexity, complexity science, wavelet and entropy, solutions of advanced mathematical challenges, mathematical neuroscience and biology as well as advanced data analysis in medicine and other related theoretical, computational and applied domains.
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