Vishal Jain

Sarika Jain

Ankur Choudhary

Ankita Bansal

Abha Jain

Computational Intelligence Techniques and Their Applications to Software Engineering Problems focuses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection and prioritization, and much more. The concepts of expert systems, case-based reasoning, fuzzy logic, genetic algorithms, swarm computing, and rough sets are introduced with their applications in software engineering. The field of knowledge discovery is explored using neural networks and data mining techniques by determining the underlying and hidden patterns in software data sets. Aimed at graduate students and researchers in computer science engineering, software engineering, information technology, this book: Covers various aspects of in-depth solutions of software engineering problems using computational intelligence techniques Discusses the latest evolutionary approaches to preliminary theory of different solve optimization problems under software engineering domain Covers heuristic as well as meta-heuristic algorithms designed to provide better and optimized solutions Illustrates applications including software requirement prioritization, software cost estimation, reliability assessment, software defect prediction, and more Highlights swarm intelligence-based optimization solutions for software testing and reliability problems

Computational Intelligence Techniques and Their Applications to Software Engineering Problems

Jyotir Moy Chatterjee

Ahmed A. Elngar

Sachi Nandan Mohanty

Priya Gupta

This book is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. It comprehensively covers the topic of recommender systems, which provide personalized recommendations of items or services to the new users based on their past behavior. Recommender system methods have been adapted to diverse applications including social networking, movie recommendation, query log mining, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. Recommendations in agricultural or healthcare domains and contexts, the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. This book illustrates how this technology can support the user in decision-making, planning and purchasing processes in agricultural & healthcare sectors.

Practical Tools and Applications in Medical, Agricultural and Other Industries

Recommender System with Machine Learning and Artificial Intelligence

San Murugesan

This book provides an overview of the emerging smart connected world, and discusses the roles and the usage of underlying semantic computing and Internet-of-Things (IoT) technologies. The book comprises ten chapters overall, grouped in two parts. Part I “Smart Connected World: Overview and Technologies” consists of seven chapters and provides a holistic overview of the smart connected world and its supporting tools and technologies. Part II “Applications and Case Studies” consists of three chapters that describe applications and case studies in manufacturing, smart cities, health, and more. Each chapter is self-contained and can be read independently; taken together, readers get a bigger picture of the technological and application landscape of the smart connected world. This book is of interest for researchers, lecturers, and practitioners in Semantic Web, IoT and related fields. It can serve as a reference for instructors and students taking courses in hybrid computing getting abreast of cutting edge and future directions of a connected ecosystem. It will also benefit industry professionals like software engineers or data scientists, by providing a synergy between Web technologies and applications. This book covers the most important topics on the emerging field of the smart connected world. The contributions from leading active researchers and practitioners in the field are thought provoking and can help in learning and further research. The book is a valuable resource that will benefit academics and industry. It will lead to further research and advancement of the field. Bharat K. Bhargava, Professor of Computer Science, Purdue University, United States

Technologies and Applications Shaping the Future

Smart Connected World

Le Gruenwald

Sven Groppe

Leveraging Artificial Intelligence in Global Epidemics provides readers with a detailed technical description of the role Artificial Intelligence plays in various stages of a disease outbreak, using COVID-19 as a case study. In the fight against epidemics, medical staff are on the front line; but behind the lines the battle is fought by researchers, and data scientists. Artificial Intelligence has been helping researchers with computer modeling and simulation for predictions about disease progression, the overall economic situation, tax incomes and population development. In the same manner, AI can prepare researchers for any emergency situation by backing the medical science. Artificial Intelligence plays a key and cutting-edge role in the preparedness for and dealing with the outbreak of global epidemics. It can help researchers analyze global data about known viruses to predict the patterns of the next pandemic and the impacts it will have. Not only prediction, AI plays an increasingly important role in assessing readiness, early detection, identification of patients, generating recommendations, situation awareness and more. It is up to the right input and the innovative ways by humans to leverage what AI can do. As COVID-19 has grabbed the world and its economy today, an analysis of the COVID-19 outbreak and the global responses and analytics will pay a long way in preparing humanity for such future situations. Provides readers with understanding of how Artificial Intelligence can be applied to the prediction, forecasting, detection, and testing of global epidemics, using COVID-19 and other recent epidemics such as Ebola, Corona viruses, Zika, influenza, Dengue, Chikungaya, and malaria as case studies Includes background material regarding readiness for coping with epidemics, including Machine Learning models for prediction of epidemic outbreaks based on existing data Includes technical coverage of key topics such as generating recommendations to combat outbreaks, genome sequencing, AI-assisted testing, AI-assisted contact tracing, situation awareness and combating disinformation, and the role of Artificial Intelligence and Machine Learning in drug discovery, vaccine development, and drug re-purposing

Leveraging Artificial Intelligence in Global Epidemics

Valentina Emilia Balas

Web Semantics strengthen the description of web resources to exploit them better and make them more meaningful for both humans and machines, thereby contributing to the development of a knowledgeintensive data web. The world is experiencing the movement of concept from data to knowledge and the movement of web from document model to data model. The underlying idea is making the data machine understandable and processable. In the light of these trends, conciliation of Semantic and the Web is of paramount importance for further progress in the area. Web Semantics: Cutting Edge and Future Directions in Healthcare describes the three major components of the study of Semantic Web, namely Representation, Reasoning, and Security with a special focus on the healthcare domain. This book summarizes the trends and current research advances in web semantics, emphasizing the existing tools and techniques, methodologies, and research solutions. It provides easily comprehensible information on Web Semantics including semantics for data and semantics for services. Presents a comprehensive examination of the emerging research in areas of the semantic web, including ontological engineering, semantic annotation, reasoning and intelligent processing, semantic search paradigms, semantic web mining, and semantic sentiment analysis Helps readers understand key concepts in semantic web applications for biomedical engineering and healthcare, including mapping disparate knowledge bases, security issues, multilingual semantic web, and integrating databases with knowledge bases Includes coverage of key application areas of the semantic web, including clinical decision-making, biodiversity science, interactive healthcare, intelligent agent systems, decision support systems, and clinical natural language processing

Cutting Edge and Future Directions in Healthcare

Web Semantics

Sarika Jain

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