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Deep Learning for Internet of Things Infrastructure
USA.Mamoun Alazab is an Associate Professor in the College of Engineering, IT and Environment at Charles Darwin University, Australia.Ali Kashif Bashir is a Senior Lecturer/Associate Professor and Program Leader of BSc (H) Computer Forensics and Security at the Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom.Al-Sakib Khan Pathan is an Adjunct Professor of Computer Science and Engineering at the Independent University, Bangladesh.
Deep Learning for Internet of Things Infrastructure
This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT systems and services across various application domains. The book investigates the challenges posed by the implementation of deep learning on IoT networking models and services. It provides fundamental theory, model, and methodology in interpreting, aggregating, processing, and analyzing data for intelligent DL-enabled IoT. The book also explores new functions and techno...
Implementing Data Analytics and Architectures for Next Generation Wireless Communications
Wireless communication is continuously evolving to improve and be a part of our daily communication. This leads to improved quality of services and applications supported by networking technologies. We are now able to use LTE, LTE-Advanced, and other emerging technologies due to the enormous efforts that are made to improve the quality of service in cellular networks. As the future of networking is uncertain, the use of deep learning and big data analytics is a point of focus as it can work in many capacities at a variety of levels for wireless communications. Implementing Data Analytics and Architectures for Next Generation Wireless Communications addresses the existing and emerging theoret...
Applications of Machine intelligence in Engineering
The Global Conference on Artificial Intelligence and Applications (GCAIA 2021) provides a prominent venue for researchers, engineers, entrepreneurs, and scholar students to share their research ideas in the area of AI. Academic researchers would reveal the results and conclusions of laboratory based investigations via the GCAIA 21 platform, which bridges the gap between academia, industry, and government ethics. The GCAIA 21 platform will also bring together regional and worldwide issues to explore current advancements in contemporary Computation Intelligence. This Conference Proceedings volume contains the written versions of most of the contributions presented during the conference of GCAIA 2021. The conference has provided an excellent chance for researchers from diverse locations to present and debate their work in the field of artificial intelligence and its applications. It includes a selection of 62 papers. All accepted papers were subjected to strict peer-review by 2–4 expert referees. The papers have been selected for this volume because of their quality and their relevance to the theme of the conference.
Proceedings of Data Analytics and Management
This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.
Modeling and Optimization of Signals Using Machine Learning Techniques
Modeling and Optimization of Signals using Machine Learning Techniques is designed for researchers from academia, industries, and R&D organizations worldwide who are passionate about advancing machine learning methods, signal processing theory, data mining, artificial intelligence, and optimization. This book addresses the role of machine learning in transforming vast signal databases from sensor networks, internet services, and communication systems into actionable decision systems. It explores the development of computational solutions and novel models to handle complex real-world signals such as speech, music, biomedical data, and multimedia. Through comprehensive coverage of cutting-edge techniques, this book equips readers with the tools to automate signal processing and analysis, ultimately enhancing the retrieval of valuable information from extensive data storage systems. By providing both theoretical insights and practical guidance, the book serves as a comprehensive resource for researchers, engineers, and practitioners aiming to harness the power of machine learning in signal processing.
Innovative Smart Materials Used in Wireless Communication Technology
In recent years, wireless communication has become an integral part of daily life, allowing people across the world to communicate with each other easily, regardless of their geographical location. As these technologies develop, innovations are made in the ways in which they are constructed. Emerging trends in smart material usage in wireless technology requires further investigation for the optimization of next-generation communication technology. Innovative Smart Materials Used in Wireless Communication Technology focuses on the advancements of smart material usage in wireless communication technologies. It analyzes the design, usage, and construction of these smart materials for wireless applications. Covering topics such as millimeter wave antennas, semiconductor materials, and wearable applications, this premier reference source is an essential resource for material engineers and scientists, communications scientists, manufacturers, students and educators of higher education, librarians, researchers, and academicians.
A Research Agenda for Financial Law and Regulation
This is an open access title available under the terms of a CC BY-NC-ND 4.0 License. It is free to read, download and share on Elgaronline, thanks to generous funding support from the University of Zurich. This prescient Research Agenda explores the transformative impact of technological advancements on legal and regulatory frameworks in the financial sector. Balancing theory, practice and empirical findings, it provides a comprehensive analysis of the opportunities and challenges presented by the shift towards decentralisation and disintermediation.
