Bøker av Nilanjan Dey

This book presents advanced research on smart health technologies, focusing upon the innovative transformations in diagnosis and treatment planning using medical imaging and data analysed by data science techniques. It shows how smart health technologies leverage artificial intelligence (AI) and big data analytics to provide more accurate and efficient diagnosis and treatment planning. In search for innovative and novel methods and techniques for health technologies and medical data processing, the book discusses applications of Artificial Intelligence, Data Science, Machine Learning, Deep Learning, the Internet of Things, Big Data, Cloud Computing.- Includes use of Electronic Patient records in healthcare, analysis of big data in medical diagnosis, reliability, and challenges of EPR and EHR in smart healthcare- Explores evolving techniques for smart healthcare, it's application in medical imaging and prediction in the fields of treatment planning- Provides recent studies in AI-driven healthcare technologies, and medical imaging to outline insight into smart healthcare technologies- Discusses the role of big data in smart healthcare, computing techniques for healthcare for medical diagnosis and treatment planning- Encompasses the ethical and legal challenges of using smart healthcare and medical dataThis book serves as a valuable reference for researchers working on smart health technologies. Researchers of medical imaging, artificial intelligence, data science along with healthcare domain will find it a great resource as well.

The book explains basic ideas behind several kinds of applied multi-objective optimization and shows how it will be applied in practical contexts in the domain of healthcare, engineering design, and manufacturing. The book discusses how meta-heuristic algorithms are successful in resolving challenging, multi-objective optimization issues in various disciplines, including engineering, economics, medical and environmental management. The topic is useful for graduates, researchers and lecturers in optimization, engineering, management science and computer science.

This book explains the basic ideas behind several variants of ant colony optimization (ACO) and shows how they may be used in real-world settings like manufacturing, engineering design, and health care. Marco Dorigo proposed ACO for the first time, and it has been used to solve a variety of optimization problems. This book presents the latest developments of ACO.

Dieses Buch betont die grundlegenden Konzepte des CS-Algorithmus und seiner Varianten sowie deren Anwendung zur Lösung unterschiedlicher Optimierungsprobleme in medizinischen und ingenieurwissenschaftlichen Anwendungen. Evolutionäre metaheuristische Ansätze werden zunehmend zur Lösung komplexer Optimierungsprobleme in verschiedenen realen Anwendungen eingesetzt. Einer der erfolgreichsten Optimierungsalgorithmen ist die Cuckoo-Suche (CS), die zu einem aktiven Forschungsbereich geworden ist, um N-dimensionale und lineare/nichtlineare Optimierungsprobleme mithilfe einfacher mathematischer Prozesse zu lösen. CS hat die Aufmerksamkeit verschiedener Forscher auf sich gezogen, was zur Entstehung zahlreicher Varianten des grundlegenden CS mit verbesserten Leistungsmerkmalen seit 2019 geführt hat.

This book provides a detailed vogue picture of workforce management. Nowadays, the methodology of people management has been more advanced and dynamic; it becomes highly competitive. Keeping in mind the significance of economic and social development of the country, the author has tried to draw attention on innovative and creative practices of workforce retention in business. The book provides an idea on the way of merchandising with people, cultural dynamics with impacted leadership, investment in people for organizational transformation and the future of people management with artificial intelligence.

This book is focused on AI-empowered knowledge management to improve processes, implementation of technology for providing easy access to knowledge and the impact of knowledge management to promote the platform for generation of new knowledge through continuous learning. The book discusses process of knowledge management which includes entirety of the creation, distribution, and maintenance of knowledge to achieve organizational objectives. It also covers knowledge management tools which enable and enhance knowledge creation, codification, and transfer within business firms thereby reducing the burden of work and allowing application of resources and effective usage towards practical tasks. An immense growth of artificial intelligence in business organizations has occurred and AI-empowered knowledge management practice is leading towards growth and development of the organization.

The book presents current research advances, both academic and industrial, in machine learning, artificial intelligence, and data analytics for biomedical and healthcare applications. The book deals with key challenges associated with biomedical data analysis including higher dimensions, class imbalances, smaller database sizes, etc. It also highlights development of novel pattern recognition and machine learning methods specific to medical and genomic data, which is extremely necessary but highly challenging. The book will be useful for healthcare professionals who have access to interesting data sources but lack the expertise to use data mining effectively.

This book extends the work from introduction of ubiquitous computing, to the Internet of things to security and to privacy aspects of ubiquitous computing. The uniqueness of this book is the combination of important fields like the Internet of things and ubiquitous computing. It assumes that the readers' goal is to achieve a complete understanding of IoT, smart computing, security issues, challenges and possible solutions. It is not oriented towards any specific use cases and security issues; privacy threats in ubiquitous computing problems are discussed across various domains. This book is motivating to address privacy threats in new inventions for a wide range of stakeholders like layman to educated users, villages to metros and national to global levels. This book contains numerous examples, case studies, technical descriptions, scenarios, procedures, algorithms and protocols. The main endeavour of this book is threat analysis and activity modelling of attacks in order to give an actual view of the ubiquitous computing applications. The unique approach will help readers for a better understanding.

This book presents essential concepts of traditional Flower Pollination Algorithm (FPA) and its recent variants and also its application to find optimal solution for a variety of real-world engineering and medical problems. Swarm intelligence-based meta-heuristic algorithms are extensively implemented to solve a variety of real-world optimization problems due to its adaptability and robustness. FPA is one of the most successful swarm intelligence procedures developed in 2012 and extensively used in various optimization tasks for more than a decade. The mathematical model of FPA is quite straightforward and easy to understand and enhance, compared to other swarm approaches. Hence, FPA has attracted attention of researchers, who are working to find the optimal solutions in variety of domains, such as N-dimensional numerical optimization, constrained/unconstrained optimization, and linear/nonlinear optimization problems. Along with the traditional bat algorithm, the enhanced versions of FPA are also considered to solve a variety of optimization problems in science, engineering, and medical applications.

The book aims to provide advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques, including examples from different medical conditions. 3D imaging in biomedical applications and pathological medical imaging is also reviewed.