Though an individual can process a limitless amount of information, the human brain can only comprehend a small amount of data at a time. Using technology can improve the process and comprehension of information, but the technology must learn to behave more like a human brain to employ concepts like memory, learning, visualization ability, and decision making. Emerging Trends and Applications in Cognitive Computing is a fundamental scholarly source that provides empirical studies and theoretical analysis to show how learning methods can solve important application problems throughout various industries and explain how machine learning research is conducted. Including innovative research on topics such as deep neural networks, cyber-physical systems, and pattern recognition, this collection of research will benefit individuals such as IT professionals, academicians, students, researchers, and managers.

This book focuses on various advanced technologies which integrate with machine learning to assist one of the most leading industries, healthcare. It presents recent research works based on machine learning approaches supported by medical and information communication technologies with the use of data and image analysis. The book presents insight about techniques which broadly deals in delivery of quality, accurate and affordable healthcare solutions by predictive, proactive and preventative methods. The book also explores the possible use of machine learning in enterprises, such as enhanced medical imaging/diagnostics, understanding medical data, drug discovery and development, robotic surgery and automation, radiation treatments, creating electronic smart records and outbreak prediction.

The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies. It provides a unique opportunity to present the work on state-of-the-art of modern artificial intelligence tools and technologies to track and forecast COVID-19 cases. It indicates insights and viewpoints from scholars regarding risk and resilience analytics for policy making and operations of large-scale systems on this epidemic. A snapshot of the latest architectures, frameworks in machine learning and data science are also highlighted to gather and aggregate data records related to COVID-19 and to diagnose the virus. It delivers significant research outcomes and inspiring new real-world applications with respect to feasible AI based solutions in COVID-19 outbreak. In addition, it discusses strong preventive measures to control such pandemic.

This book features selected papers presented at the 3rd International Conference on Recent Innovations in Computing (ICRIC 2020), held on 20-21 March 2020 at the Central University of Jammu, India, and organized by the university's Department of Computer Science & Information Technology. It includes the latest research in the areas of software engineering, cloud computing, computer networks and Internet technologies, artificial intelligence, information security, database and distributed computing, and digital India.

This book provides a comprehensive and balanced description of learning and teaching by connecting it to secondary and higher education teachers' experiences and practices in day-to-day life. Woven around research conducted by educationists, psychologists, and practitioners around the globe, this book presents key concepts and addresses significant discussions and concerns with regard to learning and teaching in the present age. Seeking to help teachers understand learners' learning needs, preferences, and styles and manage their teaching plans, priorities, and practices accordingly, it details the main ideas and emerging practices related to learning and teaching in a very easy to 'read, understand, and practice' way. The first five chapters approach learning from different perspectives, while the next six explain in detail how to practice teaching to maximize learning outcomes. Combining the traditional textbook-style approach of content description with a self-learning approach based on various real-world situations and activities related to both learning and teaching, this textbook is particularly valuable for teachers in school education, higher education, and teacher education. This book is also an essential resource for fulfilling teachers' continuing professional development requirements. Although intended for teachers worldwide, the book especially helps teachers in South Asian countries to improve learning outcomes in their classrooms and, subsequently, the quality of their education systems.

This book comprises select proceedings of the international conference ETAEERE 2020. This volume covers latest research in advanced approaches in automation, control based devices, and adaptive learning mechanisms. The contents discuss the complex operations and behaviors of different systems or machines in different environments. Some of the areas covered include control of linear and nonlinear systems, intelligent systems, stochastic control, knowledge-based systems applications, fault diagnosis and tolerant control, and real-time control applications. The contents of this volume can be useful for researchers as well as professionals working in control and automation.

By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

This book provides an up-to-date review of fasciolosis, a disease caused by Fasciola hepatica and Fasciola gigantica, including its biology, transmission, epidemiology, host distribution, economic impact, and novel approaches for its diagnosis, treatment and prevention. It first offers a brief overview of the history of the disease, the genetic diversity of the parasite and its distribution, and the ecology of the vector snail, which belongs to the Lymnaeidae/Planorbidae family. It also examines the current strategies and novel approaches for controlling the parasite, diagnosing infections and vaccine development. Importantly, it highlights issues relating to the control of fasciolosis, including drug resistance, lack of effective diagnostics, and the parasite's long-term survival strategies based on regulation and modulation of the host immune system. Lastly, it discusses the novel control snail vectors using bait formulations, and synergetic and phototherapy treatment with chlorophyllin, which does not kill the vector.

This book presents high-quality, original contributions (both theoretical and experimental) on Information Security, Machine Learning, Data Mining and Internet of Things (IoT). It gathers papers presented at ICETIT 2019, the 1st International Conference on Emerging Trends in Information Technology, which was held in Delhi, India, in June 2019. This conference series represents a targeted response to the growing need for research that reports on and assesses the practical implications of IoT and network technologies, AI and machine learning, data analytics and cloud computing, security and privacy, and next generation computing technologies.

The current trend of learner centeredness in education has been challenging many of the current ways of working, especially in higher education institutions. This rapid change in educational institutions demands educators acquire new sets of skills via continuous reflective practices. Hence, educators in higher education institutions are actively involved in research-driven teaching and learning practices. This change of role from mere content delivery to learning facilitators could be better achieved through a strong research-driven community of practice. Preparing 21st Century Teachers for Teach Less, Learn More (TLLM) Pedagogies is a pivotal reference source that provides vital research on the application of practice-based learning techniques in higher education institutions. This publication establishes a platform for academics to share their best practices to promote teach less, learn more pedagogies and learn reciprocally from the community of practice. While highlighting topics such as interactive learning, experiential technology, and logical thinking skills, this book is ideally designed for teachers, instructional designers, higher education faculty, deans, researchers, professionals, universities, academicians, and students seeking current research on transformative learning and future teaching practices.

This book comprises select proceedings of the international conference ETAEERE 2020, and covers latest research in the areas of electronics, communication and computing. The book includes different approaches and techniques for specific applications using particle swarm optimization, Otsu's function and harmony search optimization algorithm, DNA-NAND gate, triple gate SOI MOSFET, micro-Raman and FTIR analysis, high-k dielectric gate oxide, spectrum sensing in cognitive radio, microstrip antenna, GPR with conducting surfaces, energy efficient packet routing, iBGP route reflectors, circularly polarized antenna, double fork shaped patch radiator, implementation of Doppler radar at 24 GHz, iris image classification using SVM, digital image forgery detection, secure communication, spoken dialog system, and DFT-DCT spreading strategies. Given the range of topics covered, this book can be useful for both students and researchers working in electronics and communication.

Constant improvements in technological applications have allowed for more opportunities to develop automated systems. This not only leads to higher success in smart data analysis, but also ensures that technological progression will continue. Ubiquitous Machine Learning and its Applications is a pivotal reference source for the latest research on the issues and challenges machines face in the new millennium. Featuring extensive coverage on relevant areas such as computational advertising, software engineering, and bioinformatics, this publication is an ideal resource for academicians, graduate students, engineering professionals, and researchers interested in discovering how they can apply these advancements to various disciplines.

This book describes the importance of sustainable livestock production from a food security perspective in the changing climate scenario. It covers the amelioration of climate change impacts and describes the various mitigation strategies to reduce enteric methane emissions. The book targets sustainable livestock production by covering diverse concepts of amelioration, mitigation, and policy up-gradation. Further, it examines various adverse impacts of climate change on growth, meat, milk, and reproduction in livestock. Most importantly, the book covers novel aspects of quantifying heat stress response of livestock based on non-invasive methodologies, including infrared thermal imaging, sensor-based applications, hair, urine, and fecal cortisol estimation. Particular emphasis was given to describing the skin-based novel approaches to establish climate resilience in indigenous breeds. The book provides detailed descriptions of alleviating climate change impacts on shelter management, nutritional interventions, and genetics-based strategies involving advanced genomic tools. Lastly, it highlights the livestock species which could be considered ideal climate-resilient animal models to withstand the adversities associated with climate change.

Sequential data from Web server logs, online transaction logs, and performance measurements is collected each day. This sequential data is a valuable source of information, as it allows individuals to search for a particular value or event and also facilitates analysis of the frequency of certain events or sets of related events. Finding patterns in sequences is of utmost importance in many areas of science, engineering, and business scenarios. Pattern Discovery Using Sequence Data Mining: Applications and Studies provides a comprehensive view of sequence mining techniques and presents current research and case studies in pattern discovery in sequential data by researchers and practitioners. This research identifies industry applications introduced by various sequence mining approaches.

The book, 'Laser Physics and Technology', addresses fundamentals of laser physics, representative laser systems and techniques, and some important applications of lasers. The present volume is a collection of articles based on some of the lectures delivered at the School on 'Laser Physics and Technology' organized at Raja Ramanna Centre for Advanced Technology during March, 12-30, 2012. The objective of the School was to provide an in-depth knowledge of the important aspects of laser physics and technology to doctoral students and young researchers and motivate them for further work in this area. In keeping with this objective, the fourteen chapters, written by leading Indian experts, based on the lectures delivered by them at the School, provide along with class room type coverage of the fundamentals of the field, a brief review of the current status of the field. The book will be useful for doctoral students and young scientists who are embarking on a research in this area as well as to professionals who would be interested in knowing the current state of the field particularly in Indian context.

The volume, complexity, and irregularity of computational data in modern algorithms and simulations necessitates an unorthodox approach to computing. Understanding the facets and possibilities of soft computing algorithms is necessary for the accurate and timely processing of complex data. Research Advances in the Integration of Big Data and Smart Computing builds on the available literature in the realm of Big Data while providing further research opportunities in this dynamic field. This publication provides the resources necessary for technology developers, scientists, and policymakers to adopt and implement new paradigms in computational methods across the globe. The chapters in this publication advance the body of knowledge on soft computing techniques through topics such as transmission control protocol for mobile ad hoc networks, feature extraction, comparative analysis of filtering techniques, big data in economic policy, and advanced dimensionality reduction methods.

In recent decades, significant advances in new methodologies like DNA sequencing and high-throughput sequencing have been used to identify microorganisms and monitor their interactions with different environments. Microbial genomics techniques are opening new approaches to microbiology by revealing how microorganisms affect human beings and the environment. This book covers four major areas: 1) Environmental microbial genomics, 2) Microbial genomics in human health, 3) Microbial genomics in crop improvement and plant health protection, and 4) Genome analysis of microbial pathogens. Within these areas, the topics addressed include: microbial genome diversity, evolution, and microbial genome sequencing; bioinformatics and microarray-based genomic technologies; functional genomics of bioremediation of soil and water from organic and inorganic pollutants and carbon management; functional genomics of microbial pathogens and relevant microorganisms; functional genomics of model microorganisms; and applied functional genomics. Given its scope, the book offers a comprehensive source of information on the latest applications of microorganisms and microbial genomics to enhance the sustainability of agriculture and the environment.

This book addresses the mapping of soil-landscape parameters in the geospatial domain. It begins by discussing the fundamental concepts, and then explains how machine learning and geomatics can be applied for more efficient mapping and to improve our understanding and management of 'soil'. The judicious utilization of a piece of land is one of the biggest and most important current challenges, especially in light of the rapid global urbanization, which requires continuous monitoring of resource consumption. The book provides a clear overview of how machine learning can be used to analyze remote sensing data to monitor the key parameters, below, at, and above the surface. It not only offers insights into the approaches, but also allows readers to learn about the challenges and issues associated with the digital mapping of these parameters and to gain a better understanding of the selection of data to represent soil-landscape relationships as well as the complex and interconnected links between soil-landscape parameters under a range of soil and climatic conditions. Lastly, the book sheds light on using the network of satellite-based Earth observations to provide solutions toward smart farming and smart land management.

This book analyzes the issues associated with climate change in the Himalayas. The purpose of choosing the Himalayas as a focus is because it is a particularly fragile mountain system, highly sensitive to climate change impacts, and it contains one of the largest human populations affected by climate change. The book provides extensive data and information regarding the climate history of the Himalayas, and the current effects of climate change on Himalayan weather systems, and on human and animal populations in the region. The book begins with an overview of global climate change with discussions of data trends and international initiatives, then segues into a history of climate changes and weather trends in the Himalayas. Weather systems of the Himalayas, both past and current, are analyzed and detailed through climate models, seasonal observations of weather fronts, and overviews of various climate scenarios. The book then discusses climate change impacts and signat ures specific to the Central Himalayan region, where the largest effects of impacts are observed. Readers will discover analysis presented on water resources, meteorological changes, biodiversity, agriculture and human health along with perspectives of management and policy. This book will appeal to researchers studying climate science, climatology, environmental scientists and policymakers.

This book presents selected articles from INDIA SMART GRID WEEK (ISGW 2017), which is the third edition of the Conference cum Exhibition on Smart Grids and Smart Cities, organized by India Smart Grid Forum from 07-10 March 2017 at Manekshaw Centre, Dhaula Kuan, New Delhi, India. ISGF is a public private partnership initiative of the Ministry of Power, Govt. of India with the mandate of accelerating smart grid deployments across the country. This book gives current scenario updates of Indian power sector business. It also highlights various disruptive technologies for power sector business.

In the event of a disastrous event leading to the loss of communication networks, ad-hoc networks are a potent wireless communication resource because of their unique features including being quickly deployable and having a distributed nature, large coverage area, reduced cost, and more. Flying ad-hoc networks (FANETS) and vehicular ad-hoc networks (VANETS) are the future technology and can solve many problems in e-commerce delivery through drones, agriculture, vaccine delivery, and more. The unique characteristics of these networks and special requirements have created new challenges for the research community in recent decades. Modelling and Simulation of Fast-Moving Ad-Hoc Networks (FANETs and VANETs) enhances the modelling and simulation aspects of FANETS and VANETS and understands the protocols in mac layer and network layers for fast-moving ad-hoc networks. It presents simulations run using various simulation tools and measures the performance metrics of ad-hoc networks. Covering topics such as emulation tools, secure communication, and modelling software, this premier reference source is an excellent resource for computer scientists, IT specialists, business leaders and managers, supply chain and logistics management, libraries, students, government officials, international organizations, law enforcement, engineers, agriculturalists, researchers, and academicians.

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. In many real-world problems, there are several different objectives that need to be taken into account. Solving these problems is a challenging task and requires careful consideration. In real applications, often simple and easy to understand methods are used; as a result, the solutions accepted by decision makers are not always optimal solutions. On the other hand, algorithms that would provide better outcomes are very time consuming. The greatest challenge facing researchers is how to create effective algorithms that will yield optimal solutions with low time complexity. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems. This book introduces readers to state-of-the-art developments in biologically inspired techniques and their applications, with a major emphasis on the MCDM process. To do so, it presents a wide range of contributions on e.g. BIAs, MCDM, nature-inspired algorithms, multi-criteria optimization, machine learning and soft computing.