Interdisciplinary approaches using Machine Learning and Deep Learning techniques are smartly addressing real life challenges and have emerged as an inseparable element of disruption in current times. Applications of Disruptive Technology in Management practices are an ever interesting domain for researchers and professionals. This volume entitled Emerging Trends in Disruptive Technology Management for Sustainable Development has attempted to collate five different interesting research approaches that have innovatively reflected diverse potential of disruptive trends in the era of 4th. Industrial Revolution. The uniqueness of the volume is going to cater the entrepreneurs and professionals in the domain of artificial intelligence, machine learning, deep learning etc. with its unique propositions in each of the chapters. The volume is surely going to be a significant source of knowledge and inspiration to those aspiring minds endeavouring to shape their futures in the area of applied research in machine learning and computer vision. The expertise and experiences of the contributing authors to this volume is encompassing different fields of proficiencies. This has set an excellent prelude to discover the correlation among multidisciplinary approaches of innovation. Covering a broad range of topics initiating from IoT based sustainable development to crowd sourcing concepts with a blend of applied machine learning approaches has made this volume a must read to inquisitive wits. Features Assorted approaches to interdisciplinary research using disruptive trends Focus on application of disruptive technology in technology management Focus on role of disruptive technology on sustainable development Promoting green IT with disruptive technology The book is meant to benefit several categories of students and researchers. At the students' level, this book can serve as a treatise/reference book for the special papers at the masters level aimed at inspiring possibly future researchers. Newly inducted PhD aspirants would also find the contents of this book useful as far as their compulsory course-works are concerned. At the researchers' level, those interested in interdisciplinary research would also be benefited from the book. After all, the enriched interdisciplinary contents of the book would always be a subject of interest to the faculties, existing research communities and new research aspirants from diverse disciplines of the concerned departments of premier institutes across the globe. This is expected to bring different research backgrounds (due to its cross platform characteristics) close to one another to form effective research groups all over the world. Above all, availability of the book should be ensured to as much universities and research institutes as possible through whatever graceful means it may be. Hope this volume will cater as a ready reference to your quest for diving deep into the ocean of technology management for 4th. Industrial Revolution.

The rise of technology in human culture has changed almost every facet of society. Technology is especially useful regarding sustainable development. These technologies can cause significant greenhouse gas reductions and other benefits in terms of logistics and smart cities. New technology applied in this way can greatly help the human effort to restore the environment. Disruptive Technologies and Eco-Innovation for Sustainable Development provides an in-depth look into the new techniques, strategies, and technologies for achieving environmental sustainability through best business and technology practices. The book covers topics such as eco-innovation, green criteria, Agriculture 4.0, and topics related to logic, philosophy, and history of science and technology from the green/sustainable point of view. It is essential for managers, academicians, scientists, students, and researchers in various government, public, and private sectors.

The proliferation of entrepreneurship, technological and business innovations, emerging social trends and lifestyles, employment patterns, and other developments in the global context involve creative destruction that transcends geographic and political boundaries and economic sectors and industries. This creates a need for an interdisciplinary exploration of disruptive technologies, their impacts, and their implications for various stakeholders widely ranging from government agencies to major corporations to consumer groups and individuals. Disruptive Technology: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines innovation, imitation, and creative destruction as critical factors and agents of socio-economic growth and progress in the context of emerging challenges and opportunities for business development and strategic advantage. Highlighting a range of topics such as IT innovation, business strategy, and sustainability, this multi-volume book is ideally designed for entrepreneurs, business executives, business professionals, academicians, and researchers interested in strategic decision making using innovations and competitiveness.

Artificial intelligence (AI) is becoming a reality for pioneering organizations while they are facing complex and multifaceted aspects of business sustainability with ambiguous and changing ethical norms and vague or nonexistent legislation. The first quarter of the 21st century was identified as the beginning of the continuous, ongoing, and accelerating wave of simultaneous general purpose technologies revolutions causing accelerated shrinkage of the half-life of knowledge. Cases on Enhancing Business Sustainability Through Knowledge Management Systems presents teaching case studies exploring the formulation and implementation of knowledge management systems (KMS) in organizations. Covering topics such as automation, machine learning, and socio-ecological innovation, this case book is an essential resource for business leaders and managers, IT managers, entrepreneurs, government officials, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

Disruptive Trends in Computer Aided Diagnosis collates novel techniques and methodologies in the domain of content based image classification and deep learning/machine learning techniques to design efficient computer aided diagnosis architecture. It is aimed to highlight new challenges and probable solutions in the domain of computer aided diagnosis to leverage balancing of sustainable ecology. The volume focuses on designing efficient algorithms for proposing CAD systems to mitigate the challenges of critical illnesses at an early stage. State-of-the-art novel methods are explored for envisaging automated diagnosis systems thereby overriding the limitations due to lack of training data, sample annotation, region of interest identification, proper segmentation and so on. The assorted techniques addresses the challenges encountered in existing systems thereby facilitating accurate patient healthcare and diagnosis. Features: An integrated interdisciplinary approach to address complex computer aided diagnosis problems and limitations. Elucidates a rich summary of the state-of-the-art tools and techniques related to automated detection and diagnosis of life threatening diseases including pandemics. Machine learning and deep learning methodologies on evolving accurate and precise early detection and medical diagnosis systems. Information presented in an accessible way for students, researchers and medical practitioners. The volume would come to the benefit of both post-graduate students and aspiring researchers in the field of medical informatics, computer science and electronics and communication engineering. In addition, the volume is also intended to serve as a guiding factor for the medical practitioners and radiologists in accurate diagnosis of diseases.

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.

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.

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.

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.