Nazmul Siddique - Böcker

Opportunistic networking, by definition, allows devices to communicate whenever a window of opportunity is available. Many emerging technologies employ opportunistic exchanges of information. This book addresses this trend in communications engineering, taking into account three specific areas—vehicular, device-to-device (D2D), and cognitive radio—while describing the opportunistic communication methods of each. From smart homes to smart cities, smart agriculture to never-die-networks and beyond, the text explores the state of the art of opportunistic networking, providing the latest research, developments, and practices in one concise source.

Applied Informatics for Industry 4.0 combines the technologies of computer science and information science to assist in the management and processing of data to provide different types of services. Due to the adaptation of 4.0 IR-related technologies, applied informatics is playing a vital role in different sectors such as healthcare, complex system design and privacy-related issues. This book focuses on cutting edge research from the fields of informatics and complex industrial systems, and will cover topics including health informatics, bioinformatics, brain informatics, genomics and proteomics, data and network security and more. The text will appeal to beginners and advanced researchers in the fields of computer science, information sciences, electrical and electronic engineering and robotics.

We are all aware that artificial intelligence (AI) has brought a change in our lives, driven by a new form of interaction between man and machine. We are in the era of the fourth Industrial Revolution (IR) where AI plays vital roles in human development by enabling extraordinary technological advances making fundamental changes to the way we live, work and relate to one another. It is an opportunity to help everyone, including leaders, policymakers and people from all income groups and nations, to harness converging technologies in order to create an inclusive, human-centered future. We need to prepare our graduates as well as researchers to conduct their research with 4.0 IR-related technologies. We need to develop policies and implement those policies to focus on the components of 4.0 IR for sustainable developments. Applied Intelligence for Industry 4.0 will cover cutting edge topics in the fields of AI and industry 4.0. The text will appeal to beginners and advanced researchers in computer science, information sciences, engineering and robotics.Features Discusses advance data mining, feature extraction and classification algorithms for disease detection, cyber security detection and prevention, soil quality assessment and other industrial applications Includes the parameter optimization and explanation of intelligent approaches for business applications Presents context-aware smart insights and energy efficient and smart computing for the next-generation of smart industry

Computer vision and image analysis are indispensable components of every automated environment. Modern machine vision and image analysis techniques play key roles in automation and quality assurance. Working environments can be improved significantly if we integrate computer vision and image analysis techniques. The more advancement in innovation and research in computer vision and image processing, the greater the efficiency of machines as well as humans. Computer Vision and Image Analysis for Industry 4.0 focuses on the roles of computer vision and image analysis for 4.0 IR-related technologies. The text proposes a variety of techniques for disease detection and prediction, text recognition and signature verification, image captioning, flood level assessment, crops classifications and fabrication of smart eye-controlled wheelchairs.

Applied Informatics for Industry 4.0 combines the technologies of computer science and information science to assist in the management and processing of data to provide different types of services. Due to the adaptation of 4.0 IR-related technologies, applied informatics is playing a vital role in different sectors such as healthcare, complex system design and privacy-related issues. This book focuses on cutting edge research from the fields of informatics and complex industrial systems, and will cover topics including health informatics, bioinformatics, brain informatics, genomics and proteomics, data and network security and more. The text will appeal to beginners and advanced researchers in the fields of computer science, information sciences, electrical and electronic engineering and robotics.

We are all aware that artificial intelligence (AI) has brought a change in our lives, driven by a new form of interaction between man and machine. We are in the era of the fourth Industrial Revolution (IR) where AI plays vital roles in human development by enabling extraordinary technological advances making fundamental changes to the way we live, work and relate to one another. It is an opportunity to help everyone, including leaders, policymakers and people from all income groups and nations, to harness converging technologies in order to create an inclusive, human-centered future. We need to prepare our graduates as well as researchers to conduct their research with 4.0 IR-related technologies. We need to develop policies and implement those policies to focus on the components of 4.0 IR for sustainable developments. Applied Intelligence for Industry 4.0 will cover cutting edge topics in the fields of AI and industry 4.0. The text will appeal to beginners and advanced researchers in computer science, information sciences, engineering and robotics.Features Discusses advance data mining, feature extraction and classification algorithms for disease detection, cyber security detection and prevention, soil quality assessment and other industrial applications Includes the parameter optimization and explanation of intelligent approaches for business applications Presents context-aware smart insights and energy efficient and smart computing for the next-generation of smart industry

Computer vision and image analysis are indispensable components of every automated environment. Modern machine vision and image analysis techniques play key roles in automation and quality assurance. Working environments can be improved significantly if we integrate computer vision and image analysis techniques. The more advancement in innovation and research in computer vision and image processing, the greater the efficiency of machines as well as humans. Computer Vision and Image Analysis for Industry 4.0 focuses on the roles of computer vision and image analysis for 4.0 IR-related technologies. The text proposes a variety of techniques for disease detection and prediction, text recognition and signature verification, image captioning, flood level assessment, crops classifications and fabrication of smart eye-controlled wheelchairs.

In today’s fast-evolving tech landscape, Intelligent Networks and Systems: Advanced Technologies and Applications explores cutting-edge innovations in intelligent systems and their real-world impact. From smart grids and IoT applications to machine learning-driven network optimization and cybersecurity, this book covers the key technologies shaping modern infrastructure.Balancing technical depth with clear, engaging writing, this book is designed for researchers, industry professionals, and tech enthusiasts alike. It not only unpacks the latest advancements but also examines ethical and regulatory challenges as intelligent networks become more integrated into everyday life.As these technologies continue to transform industries, this book serves as a vital resource for staying ahead. Whether you're looking to deepen your expertise or apply these concepts in practice, this book will guide and inspire your journey into the future of intelligent technology.

This book explores how advanced machine learning techniques are transforming healthcare, highlighting innovative applications in disease diagnosis, treatment, and healthcare management. It shows that adaptation of machine learning can bring significant benefits for the sustainability of healthcare informatics in the era of 4.0 IR.With contributions from researchers and field experts, the book covers key topics such as predictive analytics, medical image processing, and personalized healthcare. Each chapter provides detailed methodologies, datasets, and experimental results, with practical insights into AI-driven diagnostics, patient monitoring, and decision-support systems.Designed for those seeking to apply machine learning in healthcare and to advance healthcare informatics, this book is a valuable resource for researchers, professionals, and students.

The increasing reliance on automation and data-driven decision-making is transforming industries. As technology advances, the need for more intelligent and efficient systems is growing. This book explores how data-driven approaches are being applied in various fields to solve real-world challenges.With contributions from researchers and professionals, the chapters discuss practical applications of modern computational techniques. Topics range from optimizing industrial processes to improving predictive systems in different sectors. The book also emphasizes the importance of responsible and interpretable technology to ensure fairness and transparency.This book is a valuable resource for students, researchers, and professionals looking to understand the evolving role of data in industry. It provides insights into emerging trends and encourages further exploration in the field of intelligent systems and automation.

AI is revolutionizing healthcare, transforming diagnostics, treatment, and patient care. Applied Intelligence for Healthcare Informatics: Techniques and Applications explores cutting-edge AI solutions for disease prediction, medical imaging, mental health analysis, and healthcare decision-making. Covering topics like heart disease prediction, COVID-19 detection, breast cancer classification, and ethical AI challenges, this book bridges theory with real-world applications. A must-read for researchers, practitioners, and innovators, it offers insights into the future of AI-driven healthcare.

Data-Driven Applications for Emerging Technologies explores the practical use of data science in AI, healthcare, sustainability, and security. It covers key topics like predictive modelling, deep learning, and natural language processing, offering a mix of theory and hands-on applications. The book highlights how data-driven techniques can improve decision-making, optimize processes, and solve real-world problems.Each chapter includes research contributions from academics and industry professionals, making the content both relevant and accessible. Readers will find practical insights into applying machine learning frameworks, data preprocessing techniques, and emerging technologies across different domains.Designed for researchers, professionals, and students, this book provides a solid foundation in data-driven methods without being overly technical. Whether you’re looking to enhance your understanding of AI and machine learning or apply data science in real-world scenarios, this book serves as a useful and practical resource.

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples.Key features: Covers all the aspects of fuzzy, neural and evolutionary approaches with worked out examples, MATLAB® exercises and applications in each chapterPresents the synergies of technologies of computational intelligence such as evolutionary fuzzy neural fuzzy and evolutionary neural systemsConsiders real world problems in the domain of systems modelling, control and optimizationContains a foreword written by Lotfi ZadehComputational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing is an ideal text for final year undergraduate, postgraduate and research students in electrical, control, computer, industrial and manufacturing engineering.

Focusing on the nuts and bolts of wireless network access for computers on board vehicles, this volume shows how in-car computerization now does much more than merely act as a glorified map-reader.

Opportunistic networking, by definition, allows devices to communicate whenever a window of opportunity is available. Many emerging technologies employ opportunistic exchanges of information. This book addresses this trend in communications engineering, taking into account three specific areas—vehicular, device-to-device (D2D), and cognitive radio—while describing the opportunistic communication methods of each. From smart homes to smart cities, smart agriculture to never-die-networks and beyond, the text explores the state of the art of opportunistic networking, providing the latest research, developments, and practices in one concise source.

Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller. The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined.The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area.Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control.

Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller. The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined.The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area.Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control.

This new edition continues to focus on the nuts and bolts of wireless network access for devices on board vehicles. It has been updated to reflect on the most recent trends in the broad domain of Intelligent Transport Systems. It covers 802.11ac – a recent standard that is very useful in context where a large amount of information is to be sent in a limited time window. The new edition includes a thorough revision of the 'Vehicular Communication: Issues and Standards' chapter, with new citations and a new subsection on security. The new edition also cites numerous fresh research works to give readers an updated overview of the field. An update on the time delay incurred by applications that always run in the background (Skype, etc) is also covered. The 'Future Directions and Research Ideas' chapter is also largely re-written. An entirely new chapter on D2D communication keeping in view the vehicular context has been added in this edition. This volume will be a useful addition to the libraries for both the students of wireless communication and those studying applied probability.

This new edition continues to focus on the nuts and bolts of wireless network access for devices on board vehicles. The new edition includes a thorough revision of the 'Vehicular Communication: Issues and Standards' chapter, with new citations and a new subsection on security.

The book constitutes selected peer-reviewed proceedings of the International Conference on the 4th Industrial Revolution and Beyond (IC4IR 2021). The book serves as a reference book for practitioners and researchers working in the areas of AI, soft computing, IoT, and data analytics.