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Federated Learning - A Systematic Review
Federated Learning (FL) represents a transformative leap in distributed machine learning by enabling multiple clients to collaboratively solve complex tasks without compromising data privacy. This innovative approach eliminates the need for centralized cloud storage, ensuring privacy-preserving data handling while offering smarter models, reduced latency, and enhanced power efficiency. This book serves as a comprehensive guide to the evolving field of Federated Learning, providing in-depth insights into its definition, architecture, and classification. It examines the distinctions between FL and traditional distributed learning paradigms through a comparative lens. The chapters explore key c...
The Encyclopedia of Neutrosophic Researchers, 5th Volume
Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy. In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, eco...
A Novel Neutrosophic Data Analytic Hierarchy Process for Multi-Criteria Decision Making Method: A Case Study in Kuala Lumpur Stock Exchange
This paper proposes a multi-criteria decision making method called the neutrosophic data analytical hierarchy process (NDAHP) for the single-valued neutrosophic set (SVNS). This method is an extension of the neutrosophic analytic hierarchy process (NAHP) but was designed to handle actual datasets which consists of crisp values. Our proposed NDAHP method uses an objective weighting mechanism whereas all other existing versions of the AHP, fuzzy AHP and other fuzzy based AHP method in literature such as the NAHP and picture fuzzy AHP uses a subjective weighting mechanism to arrive at the decision. This makes our proposed NDAHP method a very objective one as the weightage of the criteria which ...
Innovative Computing and Communications
This book includes high-quality research papers presented at the Eighth International Conference on Innovative Computing and Communication (ICICC 2025), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on 14–15 February 2025. Introducing the innovative works of scientists, professors, research scholars, students, and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.
Collected Papers. Volume VI
This sixth volume of Collected Papers includes 74 papers comprising 974 pages on (theoretic and applied) neutrosophics, written between 2015-2021 by the author alone or in collaboration with the following 121 co-authors from 19 countries: Mohamed Abdel-Basset, Abdel Nasser H. Zaied, Abduallah Gamal, Amir Abdullah, Firoz Ahmad, Nadeem Ahmad, Ahmad Yusuf Adhami, Ahmed Aboelfetouh, Ahmed Mostafa Khalil, Shariful Alam, W. Alharbi, Ali Hassan, Mumtaz Ali, Amira S. Ashour, Asmaa Atef, Assia Bakali, Ayoub Bahnasse, A. A. Azzam, Willem K.M. Brauers, Bui Cong Cuong, Fausto Cavallaro, Ahmet Çevik, Robby I. Chandra, Kalaivani Chandran, Victor Chang, Chang Su Kim, Jyotir Moy Chatterjee, Victor Christia...
Collected Papers. Volume VII
This seventh volume of Collected Papers includes 70 papers comprising 974 pages on (theoretic and applied) neutrosophics, written between 2013-2021 by the author alone or in collaboration with the following 122 co-authors from 22 countries: Mohamed Abdel-Basset, Abdel-Nasser Hussian, C. Alexander, Mumtaz Ali, Yaman Akbulut, Amir Abdullah, Amira S. Ashour, Assia Bakali, Kousik Bhattacharya, Kainat Bibi, R. N. Boyd, Ümit Budak, Lulu Cai, Cenap Özel, Chang Su Kim, Victor Christianto, Chunlai Du, Chunxin Bo, Rituparna Chutia, Cu Nguyen Giap, Dao The Son, Vinayak Devvrat, Arindam Dey, Partha Pratim Dey, Fahad Alsharari, Feng Yongfei, S. Ganesan, Shivam Ghildiyal, Bibhas C. Giri, Masooma Raza Ha...
Collected Papers. Volume VIII
This eighth volume of Collected Papers includes 75 papers comprising 973 pages on (theoretic and applied) neutrosophics, written between 2010-2022 by the author alone or in collaboration with the following 102 co-authors (alphabetically ordered) from 24 countries: Mohamed Abdel-Basset, Abduallah Gamal, Firoz Ahmad, Ahmad Yusuf Adhami, Ahmed B. Al-Nafee, Ali Hassan, Mumtaz Ali, Akbar Rezaei, Assia Bakali, Ayoub Bahnasse, Azeddine Elhassouny, Durga Banerjee, Romualdas Bausys, Mircea Boșcoianu, Traian Alexandru Buda, Bui Cong Cuong, Emilia Calefariu, Ahmet Çevik, Chang Su Kim, Victor Christianto, Dae Wan Kim, Daud Ahmad, Arindam Dey, Partha Pratim Dey, Mamouni Dhar, H. A. Elagamy, Ahmed K. Es...
Ai-Based Data Mobility and Intelligent Modeling for Smart Cities
The transformative potential of artificial intelligence (AI) is creating more efficient, connected, and sustainable urban environments in smart cities. By enabling seamless data mobility across diverse systems, AI facilitates real-time decision-making and predictive modeling that enhance city planning and governance. Intelligent data modeling empowers city leaders to anticipate challenges and improve citizens' quality of life through smarter infrastructure. This integration of AI and data-driven insights forms the backbone where technology and human-centered design converge to build resilient and adaptive urban ecosystems. AI-Based Data Mobility and Intelligent Modeling for Smart Cities explores how AI creates efficiency and improves smart cities. This book reviews the role of AI, machine learning, and deep reinforcement learning in the evolution of smart cities. Covering topics such as AI, intelligent modeling, and mobility, this book is an excellent resource for academic scientists, researchers, and research scholars.
Coding Dimensions and the Power of Finite Element, Volume, and Difference Methods
Engineers, researchers, and students attempting to effectively utilize numerical methods to solve complex engineering problems in today's fast-paced technological world are increasingly struggling to keep up without the necessary tools. While theoretical knowledge is vital, it can feel disconnected from practical application, leaving many ill-equipped to tackle real-world challenges. Coding Dimensions and the Power of Finite Element, Volume, and Difference Methods offers a comprehensive understanding and hands-on experience with numerical methods, empowering you to push the boundaries of innovation. By providing practical examples of coding and real-world applications, you will be equipped with the skills to tackle dynamic systems, partial and ordinary differential equations, and other mathematical simulations confidently.
