Mathematical Computing and Sustainability
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Herausgegeben von:
Shalli Rani
, Syed Hassan Shah und Ayush Dogra
Über dieses Buch
The book is likely intended to provide a thorough knowledge of the complex relationships between computational intelligence, mathematical computing, and sustainability. By taking an interdisciplinary approach, the author may strive to connect theoretical frameworks with practical applications, providing readers with a road map for navigating the intricacies of addressing long-term difficulties. The book could use case studies and examples to demonstrate how cutting-edge technologies and mathematical models can be used to analyse and solve real-world sustainability problems, ultimately encouraging a holistic approach that fosters innovative solutions based on computational and mathematical principles.
This book is planned to cover the comprehensive investigation into the synergies between Computational Intelligence (CI), Mathematical Computing, and Sustainability. An examination of the possible impact of intelligent systems on sustainability, new concepts and approaches for incorporating CI and mathematical computing into sustainable practices etc. There will be chapters explaining the Exploration of upcoming technologies (e.g., quantum computing, bio-inspired computing) and their potential role in promoting sustainability.
- The book employs principles of Computational intelligence and mathematical problems deployed in the trace
- It will help solve the problems of sustainable development and ensure that readers learn the same ideas in different ways
Information zu Autoren / Herausgebern
Dr. Shalli Rani (Director, Research & Senior Member of IEEE) completed her Post-doc from Manchester Metropolitan University, UK in June , 2023. She is Professor in Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India. She has 18+ years teaching experience. She received MCA degree from Maharishi Dyanand University, Rohtak in 2004 and the M.Tech. degree in Computer Science from Janardan Rai Nagar Vidyapeeth University, Udaipur in 2007 and Ph.D. degree in Computer Applications from Punjab Technical University, Jalandhar in 2017. Her main area of interest and research are Wireless Sensor Networks, Underwater Sensor networks, Machine Learning and Internet of Things. She has published/accepted/presented more than 100+ papers in international journals /conferences (SCI+Scopus) and edited/authored five books with international publishers. She is serving as the associate editor of IEEE Future Directions Letters. She served as a guest editor in IEEE Transaction on Industrial Informatics, Hindawi WCMC and Elsevier IoT Journals. She has also served as reviewer in many repudiated journals of IEEE, Springer, Elsevier, IET, Hindawi and Wiley. She has worked on Big Data, Underwater Acoustic Sensors and IoT to show the importance of WSN in IoT applications. She received a young scientist award in Feb. 2014 from Punjab Science Congress, Lifetime Achievement Award and Supervisor of the year award from Global Innovation and Excellence, 2021
Dr. Syed Hassan Shah (Senior Member of IEEE) is a Wi-Fi connectivity subject matter expert with the Qualcomm Inc. product management team, where he is involved in Consumer and Compute Wireless products with a focus on Mi-Fi, CPE, and UWB technologies. In addition to that, Dr. Shah is also an adjunct faculty member at California State University, Fullerton Campus, where he teaches computer science courses to graduate classes. Over the past decade, Dr. Shah held multiple industrial & academic roles such as a Product Specialist for Distributed Antenna Systems (DAS), CBRS, Private LTE, Digital Electricity, and open RAN product lines. Dr. Shah was an Assistant Professor in the Department of Computer Science at Georgia Southern University, USA followed by a Post-Doctoral Fellowship at the University of Central Florida, Orlando, USA. Before moving to the United States, he completed his BS with honors in CS from Kohat University of Science & Technology (KUST), Pakistan, and his Ph.D. Degree (combined with Masters) from the School of Computer Science and Engineering (SCSE), Kyungpook National University (KNU), Republic of Korea (South Korea).
Dr. Ayush Dogra ( Allied Member – European Society of Oncological Imaging ) is currently working as an Assistant Director –Research , CURIN , Chitkara University , Punjab , India. He is graduated in Bachelor of Engineering and Technology (ECE) from Guru Nanak Dev University, Amritsar in 2011. He has received his Master’s degree in Electronics & Communication Engineering from Punjabi University, Patiala in 2013 and Master’s degree in Business Management (MBA) from IGNOU, Delhi ( Central University) during 2015. He completed his Doctorate Degree from Department of Electronics and Communications engineering from Oct-2015 to Jan-2019 from Panjab University.His work area focuses on devising a novel and innovative, market-oriented mechanism for medical image fusion
He has also worked as CSIR-Nehru Post-Doctoral Researcher in Biomedical Applications Unit, CSIR-Central Scientific Instruments Organization, Chandigarh. In the past, he worked as the Junior and Senior Research Fellow in the Department of Electronics and Communication Engineering, UIET, Panjab University, Chandigarh. Also worked as Post-Doctoral fellow in the Department of Center of Biomedical Engineering, IIT Ropar .
Fachgebiete
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Frontmatter
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Preface
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Contents
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List of contributors
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1 Leveraging computational intelligence and mathematical modeling for sustainable future in agriculture: a unified paradigm for recognizing tomato leaf diseases
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2 Digital dawn: how immersive technologies are shaping a sustainable future
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3 Sustainable intelligence: ethical issues in the evolution of intelligent systems
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4 Energy sustainability and computational intelligence based routing protocols in WSN: an analytical survey
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5 Harnessing the metaverse for healthcare innovation: exploring predictive analytics and AI-driven personalization
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6 Toward a sustainable future: a computational intelligence fusion framework of color and darknet features for the classification of crop leaf diseases
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7 Sustainable computing approaches for complex medical image analysis: a neurodiagnostic perspective
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8 Sustainability with artificial intelligence: obstacles, opportunities, and research agenda
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9 Smart solutions to a sustainable future
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10 Ethical issues in intelligent systems for sustainability
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11 CPS: cyber-physical system security for the Industrial Internet of Things in smart grid
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12 Integrating mathematical computing and deep learning for efficient monkeypox skin lesion detection: A pathway to sustainable health solutions
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13 Leveraging heuristics based on CK Metrics Suite for quality enhancement in sustainable quantum software development
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14 Intelligent systems for fire management and sustainability
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15 Transparent and sustainable AI for brain tumor detection: from conventional to hybrid models in predictive healthcare
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Index
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Mathematical Methods in the Digital Age
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Herstellerinformationen:
Walter de Gruyter GmbH
Genthiner Straße 13
10785 Berlin
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