Zdzislaw Polkowski

Sandeep Kautish

Deepmala Singh

Alka Mayura

Mary Jeyanthi

Knowledge Management makes the management of information and resources within a commercial organization more effective. The contributions of this book investigate the applications of Knowledge Management in the upcoming era of Semantic Web, or Web 3.0, and the opportunities for reshaping and redesigning business strategies for more effective outcomes.

Next Generation Business Models

Knowledge Management and Web 3.0

Ahmed A. Elngar

Om Prakash Jena

Alok Ranjan Tripathy

COMPUTATIONAL INTELLIGENCE and HEALTHCARE INFORMATICS The book provides the state-of-the-art innovation, research, design, and implements methodological and algorithmic solutions to data processing problems, designing and analysing evolving trends in health informatics, intelligent disease prediction, and computer-aided diagnosis. Computational intelligence (CI) refers to the ability of computers to accomplish tasks that are normally completed by intelligent beings such as humans and animals. With the rapid advance of technology, artificial intelligence (AI) techniques are being effectively used in the fields of health to improve the efficiency of treatments, avoid the risk of false diagnoses, make therapeutic decisions, and predict the outcome in many clinical scenarios. Modern health treatments are faced with the challenge of acquiring, analyzing and applying the large amount of knowledge necessary to solve complex problems. Computational intelligence in healthcare mainly uses computer techniques to perform clinical diagnoses and suggest treatments. In the present scenario of computing, CI tools present adaptive mechanisms that permit the understanding of data in difficult and changing environments. The desired results of CI technologies profit medical fields by assembling patients with the same types of diseases or fitness problems so that healthcare facilities can provide effectual treatments. This book starts with the fundamentals of computer intelligence and the techniques and procedures associated with it. Contained in this book are state-of-the-art methods of computational intelligence and other allied techniques used in the healthcare system, as well as advances in different CI methods that will confront the problem of effective data analysis and storage faced by healthcare institutions. The objective of this book is to provide researchers with a platform encompassing state-of-the-art innovations; research and design; implementation of methodological and algorithmic solutions to data processing problems; and the design and analysis of evolving trends in health informatics, intelligent disease prediction and computer-aided diagnosis. Audience The book is of interest to artificial intelligence and biomedical scientists, researchers, engineers and students in various settings such as pharmaceutical & biotechnology companies, virtual assistants developing companies, medical imaging & diagnostics centers, wearable device designers, healthcare assistance robot manufacturers, precision medicine testers, hospital management, and researchers working in healthcare system.

Computational Intelligence and Healthcare Informatics

Siddhartha Bhattacharyya

Oscar Castillo

Ashish Khanna

Deepak Gupta

This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2021), held at Jan Wyzykowski University, Poland, during June 2021. 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.

ICDAM 2021, Volume 2

Proceedings of Data Analytics and Management

Sambit Kumar Mishra

Julian Vasilev

This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

Applications, New Developments, and Future Trends

Data Science in Engineering and Management

Escalating urbanization and energy consumption have increased the demand for green engineering solutions and intelligent systems to mitigate environmental hazards and offer a more sustainable future. Green engineering technologies help to create sustainable, eco-friendly designs and solutions with the aid of updated tools, methods, designs, and innovations. These technologies play a significant role in optimizing sustainability in various areas of energy, agriculture, waste management, and bioremediation and include green computing and artificial intelligence (AI) applications. Green Engineering and Technology: Innovations, Design, and Architectural Implementation examines the most recent advancements in green technology, across multiple industries, and outlines the opportunities of emerging and future innovations, as well as practical real-world implementation. Features: Provides different models capable of fulfilling the criteria of energy efficiency, health and safety, renewable resources, and more Examines recycling, waste management, and bioremediation techniques as well as waste-to-energy technologies Presents business cases for adopting green technologies including electronics, manufacturing, and infrastructure projects Reviews green technologies for applications such as energy production, building construction, transportation, and industrialization Green Engineering and Technology: Innovations, Design, and Architectural Implementation serves as a useful and practical guide for practicing engineers, researchers, and students alike.

Innovations, Design, and Architectural Implementation

Green Engineering and Technology

Samarjeet Borah

Ritesh Dash

This book focuses on environmental sustainability by employing elements of engineering and green computing through modern educational concepts and solutions. It visualizes the potential of artificial intelligence, enhanced by business activities and strategies for rapid implementation, in manufacturing and green technology. This book covers utilization of renewable resources and implementation of the latest energy-generation technologies. It discusses how to save natural resources from depletion and illustrates facilitation of green technology in industry through usage of advanced materials. The book also covers environmental sustainability and current trends in manufacturing. The book provides the basic concepts of green technology, along with the technology aspects, for researchers, faculty, and students.

Methods and Applications

AI in Manufacturing and Green Technology

Prasant Kumar Pattnaik

Sasmita Rani Samanta

Pradeep Kumar Mallick

Jnyana Ranjan Mohanty

This book presents applications of cognitive management and cognitive computing in the fields of risk management, cognitive fraud detection, and in business decision making. The book provides insights on how cognitive management and cognitive computing enable businesses to quickly augment human intelligence and help humans perform tasks better. For example, the authors describe how by analyzing patterns in big data, small data, and "dark data," cognitive technologies can detect human behavior and suggest options for personalizing of products and services. The book studies companies in industries such as automotive, airline, health care, retail, wealth management, and litigation who have adopted these approaches. Presents applications of cognitive computing and cognitive management used in augmenting and empowering business decisions; Shows how to employ the Internet of Things in businesses using a cognitive management framework; Discusses technical aspects and alternatives to traditional tools, algorithms, and methodologies in cognitive computing.

Cognitive Computing for Risk Management

Sudeep Tanwar

Pradeep Kumar Singh

Sunil Kumar Pandey

Gheorghe Matei

Daniela Pirvu

This edited book is comprised of original research that focuses on technological advancements for effective teaching with an emphasis on learning outcomes, ICT trends in higher education, sustainable developments and digital ecosystem in education, management and industries. The contents of the book are classified as; (i) Emerging ICT Trends in Education, Management and Innovations (ii) Digital Technologies for advancements in education, management and IT (iii) Emerging Technologies for Industries and Education, and (iv) ICT Technologies for Intelligent Applications. The book represents a useful tool for academics, researchers, industry professionals and policymakers to share and learn about the latest teaching and learning practices supported by ICT. It also covers innovative concepts applied in education, management and industries using ICT tools.

Proceedings of International Conference on ICRIHE - 2020, Delhi, India : IICT-2020

Innovations in Information and Communication Technologies (IICT-2020)

Valentina Emilia Balas

This book includes high-quality papers presented at the International Conference on Data Science and Management (ICDSM 2019), organised by the Gandhi Institute for Education and Technology, Bhubaneswar, from 22 to 23 February 2019. It features research in which data science is used to facilitate the decision-making process in various application areas, and also covers a wide range of learning methods and their applications in a number of learning problems. The empirical studies, theoretical analyses and comparisons to psychological phenomena described contribute to the development of products to meet market demands.

Proceedings of ICDSM 2019

Advances in Data Science and Management

Zdzislaw Polkowski

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