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Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis, and early detection of diseases arising from outbreaks of different epidemics with special reference to COVID-19. Starting with a formal introduction of the human immune systems, this book focuses on the epidemiological aspects with due cognizance to modeling, prevention, and diagnosis of epidemics. In addition, it also deals with evolving decisions on post-pandemic socio-economic structure. The book offers a comprehensive coverage of the most essential topics, including: A general overview of pandemics and their outbreak behavior A detailed overview of CI techniques Intelligent modeling, prediction, and diagnostic measures for pandemics Prognostic models Post-pandemic socio-economic structure The accompanying case studies are based on available real-world data sets. While other books may deal with this COVID-19 pandemic, none features topics covering the human immune system as well as influences on the environmental disorder due to the ongoing pandemic. The book is primarily intended to benefit medical professionals and healthcare workers as well as the virologists who are essentially the frontline fighters of this pandemic. In addition, it also serves as a vital resource for relevant researchers in this interdisciplinary field as well as for tutors and postgraduate and undergraduate students of information sciences.
Intelligent Modelling, Prediction, and Diagnosis from Epidemiological Data COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis and early detection of diseases arising out of outbreaks of different epidemics with special reference to COVID-19. Starting with a formal introduction of the human immune systems, this book focuses on the epidemiological aspects with due cognizance to modeling, prevention and diagnosis of epidemics. In addition, it also deals with evolving decisions on post-pandemic economic-social structure. The book offers comprehensive coverage of the most essential topics, including: A general overview of pandemics and their outbreak behavior. A detailed overview of CI techniques. Intelligent modeling, prediction and diagnostic measures for pandemics. Prognostic models. Post-pandemic socio-economic structure. The accompanying case studies are based on real-world data sets available till date. While other books may deal with this Covid-19 pandemic, none features the human immune systems as well as influences on the environmental disorder due to the ongoing pandemic. The book is primarily intended to come to the benefit of medical professionals and healthcare workers along with the virologists who are essentially the frontline fighters of Covid-19 pandemic. In addition, it would also serve as an essential resource for relevant researchers in this interdisciplinary field apart from tutors, post-graduate and under-graduate students of information sciences.
Machine learning, Internet of Things (IoT) and data analytics are new and fresh technologies that are being increasingly adopted in the field of medicine. This book positions itself at the forefront of this movement, exploring the beneficial applications of these new technologies and how they are gradually creating a smart healthcare system. This book details the various ways in which machine learning, data analytics and IoT solutions are instrumental in disease prediction in smart healthcare. For example, wearable sensors further help doctors and healthcare managers to monitor patients remotely and collect their health parameters in real-time, which can then be used to create datasets to develop machine learning models that can aid in the prediction and detection of any susceptible disease. In this way, smart healthcare can provide novel solutions to traditional medical issues. This book is a useful overview for scientists, researchers, practitioners and academics specialising in the field of intelligent healthcare, as well as containing additional appeal as a reference book for undergraduate and graduate students
Intelligent Cyber-Physical Systems Security for Industry 4.0: Applications, Challenges and Management presents new cyber-physical security findings for Industry 4.0 using emerging technologies like artificial intelligence (with machine/deep learning), data mining, applied mathematics. All these are the essential components for processing data, recognizing patterns, modeling new techniques, and improving the advantages of data science. Features • Presents an integrated approach with Cyber-Physical Systems, CPS security, and Industry 4.0 in one place • Exposes the necessity of security initiatives, standards, security policies, and procedures in the context of industry 4.0 • Suggests solutions for enhancing the protection of 5G and the Internet of Things (IoT) security • Promotes how optimization or intelligent techniques envisage the role of artificial intelligence-machine/deep learning (AI-ML/DL) in cyberphysical systems security for industry 4.0 This book is primarily aimed at graduates, researchers and professionals working in the field of security. Executives concerned with security management, knowledge dissemination, information, and policy development for data and network security in different educational, government, and non-government organizations will also find this book useful.
Hybrid Intelligent Systems for Information Retrieval covers three areas along with the introduction to Intelligent IR, i.e., Optimal Information Retrieval Using Evolutionary Approaches, Semantic Search for Web Information Retrieval, and Natural Language Processing for Information Retrieval. • Talks about the design, implementation, and performance issues of the hybrid intelligent information retrieval system in one book • Gives a clear insight into challenges and issues in designing a hybrid information retrieval system • Includes case studies on structured and unstructured data for hybrid intelligent information retrieval • Provides research directions for the design and development of intelligent search engines This book is aimed primarily at graduates and researchers in the information retrieval domain.
Computational Intelligence in Image and Video Processing presents introduction, state-of-the-art and adaptations of computational intelligence techniques and their usefulness in image and video enhancement, classification, retrieval, forensics and captioning. It covers an amalgamation of such techniques in diverse applications of image and video processing. Features: A systematic overview of state-of-the-art technology in computational intelligence techniques for image and video processing Advanced evolutionary and nature-inspired approaches to solve optimization problems in the image and video processing domain Outcomes of recent research and some pointers to future advancements in image and video processing and intelligent solutions using computational intelligence techniques Code snippets of the computational intelligence algorithm/techniques used in image and video processing This book is primarily aimed at advanced undergraduates, graduates and researchers in computer science and information technology. Engineers and industry professionals will also find this book useful.
Blockchain for IoT provides the basic concepts of Blockchain technology and its applications to varied domains catering to socio-technical fields. It also introduces intelligent Blockchain platforms by way of infusing elements of computational intelligence into Blockchain technology. With the help of an interdisciplinary approach, it includes insights into real-life IoT applications to enable the readers to assimilate the concepts with ease. This book provides a balanced approach between theoretical understanding and practical applications. Features: A self-contained approach to integrating the principles of Blockchain with elements of computational intelligence A rich and novel foundation of Blockchain technology with reference to the internet of things conjoined with the tenets of artificial intelligence in yielding intelligent Blockchain platforms Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Information presented in an accessible way for research students of computer science and information technology, as well as software professionals who can inherit the much-needed developmental ideas to boost up their computing knowledge on distributed platforms This book is aimed primarily at undergraduates, postgraduates, and researchers studying Blockchain.
The theme of this book is sustainable e-waste management through effective amalgamation of information and communication technologies (ICT) and green recycling technologies to ensure development of intelligent, smart, and sustainable systems. It encompasses multidisciplinary interventions, including recent case studies from OEMs and IT industries as well as e-waste recyclers, and explores interdisciplinary research and industry–academia collaborations towards the development of smart and sustainable systems for e-waste management. Features: Covers the application of smart and intelligent systems for e-waste management. Explores recent advancements from the technological aspect – both recycling and ICT. Reviews supply chain criticalities for e-waste. Aims at cleaner production and intelligent systems for a green digital economy. Includes real-life case studies reflecting industry standards and the current paradigm. This book is aimed at graduate students and researchers in environmental engineering, waste management, urban mining, circular economy, waste processing, electronics and telecommunication engineering, electrical and electronics engineering, and chemical engineering.
Supply chain management, often known as SCM, refers to the extensive variety of operations that are required to plan, monitor, and coordinate the movement of a product from its raw materials to its finished state in the most time- and money-efficient manner possible. How the supply chain is managed has an impact not only on the quality of the product and the service but also on the distribution, costs, and overall customer experience. Supply chain management is a massive undertaking that needs firms to reevaluate the method in which they operate their supply chains. Blockchain, IoT, and AI Technologies for Supply Chain Management discusses the problems and difficulties that the facilitators of the supply chain confront, in addition to the possible solutions to such problems and difficulties. This book will be the only one of its kind to address the impact of COVID-19 on supply chain systems involving different stakeholders such as producers, dealers, and manufacturers and will provide a foundation for future research opportunities that will allow for the unrestricted expansion and prosperity of business. It will serve as a foundation for academics, scientists, and educationists interested in the use of modern technologies in the field of supply chain management, such as the Internet of Things (IoT), Artificial Intelligence (AI), and Blockchain. In addition to those engaged in research, undergraduate and postgraduate students in higher education can also use this publication as a reference book. This book also presents a multifaceted perspective for the general public, including topics such as computer science, the food business, hotel management, fashion, medical, inventory management, and agricultural spheres.
This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.