Neuware -The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics. 384 pp. Englisch.

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T�tulo: Advancing Software Engineering Through AI, Federated Learning, and Large Language Models
Editor: IGI Global Mai 2024
Fecha de publicaci�n: 2024
Idioma: Ingl�s
ISBN 13: 9798369335024
Encuadernaci�n: Buch
Estado: Neu
Dimensiones: 286�mil�metros de ancho por 221 de alto por 25 de largo
Peso: 1224 gramos

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Sinopsis

The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics.

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Avinash Kumar Sharma currently working as Associate Professor, Department of Computer Science & Engineering, Sharda School of Engineering & Technology (SSET), Sharda University, Greater Noida. Dr. Avinash Kumar Sharma have completed Ph.D from Uttarakhand Technical University, Dehradun (A State Govt. University) in Cloud Computing. His research areas are Cloud Computing, Machine Learning, Smart Agriculture, Artificial Intelligence. He has more than 18 years of teaching experience. He has published about 40 research articles in national / international conferences, journals, and book chapters. Dr. Avinash Kumar Sharma edited 04 books with IGI Global, 01 book with Wiley and 01 authored book with BPB Publication. He has also published 05 patents including 01 design patent.

Nitin Chanderwal is currently working as an Associate Professor Educator-Full Time in the Department of Electrical and Computer Engineering at University of Cincinnati. In the past I have worked as Associate Professor-Full Time of Information Systems and Analytics at IIM Shillong, Meghalaya, INDIA. During his tenure at IIM Shillong he also served as Chairperson for the Areas: {(Information Systems and Analytics) & (IT Services and Website Committee)}. During 2017-2018, He has worked as Professor Educator in the Department of EECS at University of Cincinnati, OH and during 2010-2011 as First Tier Bank Professor in the Peter Kiewit Institute at University of Nebraska at Omaha, NE, USA. In July 2001, he received B.Engg. in Computer Science & Engineering [Hons.] from Dr. B.R. Ambedkar University, Agra and M.Engg. in Software Engineering from Thapar University, erstwhile Thapar Institute of Engineering and Technology (Deemed University), Patiala, Punjab, INDIA in March 2003. In September 2008, he received Ph.D. in Computer Science & Engineering from Jaypee University of Information Technology, INDIA and University of Florida (UF), Gainesville, FL, USA under student exchange program, specifically he has completed 12 credits course work from UF. In May 2013, he received D.Sc. in Computer Science & Engineering from Uttarakhand Technical University, Dehradun, INDIA. I completed partial research work of D.Sc. at University of Nebraska at Omaha (UNO), NE, USA. He is a IBM certified engineer, a Life Member of IAENG, Senior Member of IEEE, ACM & IACSIT and Member of SIAM and ACIS and have published 200+ Research Papers in peer reviewed International Journals & Transactions, Book Chapters, Symposium, Conferences and Position. He has bagged more than 50 academic and research awards. My research interest includes Blockchain Technology, Cyber Physical Systems, Big Data Analytics, Social Networks especially Computer Mediated Communications & Flaming, Interconnection Networks & Architecture, Fault-tolerance & Reliability, NoCs, SoCs, and NiPs, Application of Stable Matching Problems, Stochastic Communication and Sensor Networks. He has received 2 Indian Patents and 1 Australian Patent during 2020-2021. he is also an Associate Editor of the International Journal of Parallel, Emergent and Distributed Systems, Taylor and Francis, UK and IEEE Access, IEEE, USA.

Amarjeet Prajapati is currently affiliated with the Jaypee Institute of Information Technology.

Pancham Singh is currently working as an Assistant Professor in the Department of Information Technology at AKGEC, Ghaziabad since 2007. Mr. Singh has over 18 years of teaching and one year of industry experiences. Mr. Singh received a B.Tech. Degree in Computer Science & Engineering from Dr. A.P.J. Abdul Kalam Technical University (formerly, UPTU), Lucknow, Uttar Pradesh, India in 2005; a Master Degree in Information Technology from RTU, Kota, Rajasthan, India in 2013 and a Pursuing PhD from Netaji Subhas University of Technology (NSUT), New Delhi, India since january 2023. In addition he has authored 3 books in Computer Science. He has presented and published more than 40 papers in international journals and conferences. He has reviewed more 50 papers for the International Journals and Conferences. In addition he has published 20 National and International Patents and 3 Design Grants. He was the session chair for the International Conference ICDT 2024. In addition, He did work as a time table In-charge since 2010 to 2023 for more than 13 yrs also media In-charge since 2015 to 2023 for more than 8 yrs in AKGEC. He did Flying Squad Duty assigned by AKTU as a In-charge and team member 4 times. He has attended more than 30 FDPs and did work as a In-charge and member for NBA and NACC in AKGEC. His research interests are Machine Learning, Deep Learning, Blockchain, Internet of Things, and Software Engineering.

Mrignainy Kansal is currently pursuing her PhD in Computer Science and Engineering from Netaji Subhas University of Technology (NSUT), New Delhi. Alongside her studies, she holds the position of an Assistant Professor at Ajay Kumar Garg Engineering College, Ghaziabad. She completed her BTech Degree in Information Technology from AKTU and further pursued her MTech in Information Technology from Guru Gobind Singh Indraprastha University, Delhi. She has a good record of publications at various International Conferences. Additionally, she has qualified GATE-2016 and GATE-2023. Her expertise lies in diverse areas such as Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, and Software Engineering.

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