Samarjeet Borah – författare

Social Network Analytics: Computational Research Methods and Techniques focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, it includes a variety of applications from several domains, such as scientific research, and the business and industrial sectors. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, the big data analytics of social networks, multidimensional scaling, and more.

As analyzing social network data is rapidly gaining interest in the scientific research community because of the importance of the information and insights that can be culled from the wealth of data inherent in the various aspects of the network, this book provides insights on measuring the relationships and flows between people, groups, organizations, computers, URLs, and more.

Examines a variety of data analytic techniques that can be applied to social networks Discusses various methods of visualizing, modeling and tracking network patterns, organization, growth and change Covers the most recent research on social network analysis and includes applications to a number of domains

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.

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.

This book discusses the newest approach to online learning systems in higher education. As e-Learning platforms change their mechanisms for data processing and storage, there is a need to move these systems toward being more efficient and smarter. This book covers online learning systems and their application to large-scale data along with the technological aspects of these processes and problem-solving methods.Online Learning Systems: Methods and Applications with Large-Scale Data discusses the efficiency measurement and environmental impact of online education. The book offers a parametric evaluation and categorization of online learning systems and provides an exploration of big data ecosystems in cloud computing. Descriptive analytical methods that assist in finding solutions for big data challenges are also covered within the book.The book is written for academicians, which includes teachers, students, and higher education policymakers who believe in transforming the education industry, as well as research scholars and those working in education technology and artificial intelligence. Industry professionals involved in education management and those working in e-Learning companies will also find this book useful.

This book discusses the newest approach to online learning systems in higher education. As e-Learning platforms change their mechanisms for data processing and storage, there is a need to move these systems toward being more efficient and smarter. This book covers online learning systems and their application to large-scale data along with the technological aspects of these processes and problem-solving methods.Online Learning Systems: Methods and Applications with Large-Scale Data discusses the efficiency measurement and environmental impact of online education. The book offers a parametric evaluation and categorization of online learning systems and provides an exploration of big data ecosystems in cloud computing. Descriptive analytical methods that assist in finding solutions for big data challenges are also covered within the book.The book is written for academicians, which includes teachers, students, and higher education policymakers who believe in transforming the education industry, as well as research scholars and those working in education technology and artificial intelligence. Industry professionals involved in education management and those working in e-Learning companies will also find this book useful.

This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications.Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence.This book will be helpful to a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications.

Experts in research, industry, and academia cover recent trends and state-of-the art solutions in computer and communications engineering, focusing specifically on real-time applications of electronics, communications, computing, and information technology. The volume provides sound theoretical and application-oriented knowledge with a special focus on the development of safety-critical networks and integrated electrical and electronics systems. The volume also features numerous new algorithms that assist in solving computer and communication engineering problems.

Experts in research, industry, and academia cover recent trends and state-of-the art solutions in computer and communications engineering, focusing specifically on real-time applications of electronics, communications, computing, and information technology. The volume provides sound theoretical and application-oriented knowledge with a special focus on the development of safety-critical networks and integrated electrical and electronics systems. The volume also features numerous new algorithms that assist in solving computer and communication engineering problems.

This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications.Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence.This book will be helpful to a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications.

Soft computing techniques have the ability to handle complex, uncertain, and imprecise information to create usable solutions to convoluted problems, or those just too time-consuming to solve with current hardware. This new book details the use and applications of soft computing technology in several fields, exploring the use of these techniques in biomedical applications, communication technologies, data analytics and applications, image processing and natural language processing.The chapters in the section on biomedical applications explore soft computing techniques for cancer data analysis, depression and mental health analysis, heart disease detection, etc. The editors go on to discuss soft computing in communication systems, looking at graphs, design processes, and mapping techniques, as well as the integration of IoT devices, drone technology, etc. The volume also details how soft computing methodologies can assist in tackling the obstacles associated with signal processing, network optimization, quality of service and beyond.Several chapters discuss the use of soft computing techniques in data compression, handling of large-scaled heterogenous databases, visualization techniques, etc. Applications of soft computing in image processing are also discussed and cover human face recognition, casualty detection, traffic sign recognition, and predicting soil features using satellite imagery. Soft computing techniques in natural language processing consider text-to-speech signal conversion, NLP and speech recognition, speech emotion recognition and more.This volume will help to facilitate the amalgamation of theoretical principles and practical applications, bringing forth possible solutions to complex problems in various domains. The book is a welcome resource for researchers, students, professionals, and even for individuals looking for knowledge on soft computing.Applied Soft Computing Techniques: Theoretical Principles and Practical Applications will help to facilitate the amalgamation of theoretical principles and practical applications, bringing forth possible solutions to complex problems in various domains. The book is a welcome resource for researchers, students, professionals, and even for individuals looking for knowledge on soft computing.

This volume explores a wide range of advanced applications of intelligent technologies in image processing across diverse domains. It examines biological and biomedical imaging, highlighting the use of machine learning and deep learning techniques for the diagnosis and detection of conditions such as brain tumors, diabetes, pneumonia, and heart disease. Beyond healthcare, the book presents applications of intelligent computing in areas including plant identification and leaf disease detection, fruit classification and counting, forensic analysis, facial detection and emotion recognition, and sketch-tophoto synthesis. It also provides insights into key deep learning approaches, such as convolutional neural networks (CNNs) and the Inception V3 architecture, along with image enhancement techniques like contrast limited adaptive histogram equalization (CLAHE).

Cyber-physical systems (CPS) are intelligent robotics systems that cleverly merge computing algorithms with physical operations, enabling state-of-the-art response systems by integrating the virtual and physical dimensions and enhancing efficiency, automation, and interconnectedness in many sectors. With examples of real-world implementation, this new book explores many facets of CPS in robotics and engineering and presents a host of cutting-edge technologies and approaches in industrial applications as well as in other sectors, such transportation, gaming, medicine and healthcare, civil engineering and infrastructure, communications and internet security, library science, election integrity, music, etc., providing inspiration for new ideas for CPS applications.

This book is an outcome of the second national conference on Communication, Cloud and Big Data (CCB) held during November 10-11, 2016 at Sikkim Manipal Institute of Technology. The nineteen chapters of the book are some of the accepted papers of CCB 2016. These chapters have undergone review process and then subsequent series of improvements. The book contains chapters on various aspects of communication, computation, cloud and big data. Routing in wireless sensor networks, modulation techniques, spectrum hole sensing in cognitive radio networks, antenna design, network security, Quality of Service issues in routing, medium access control protocol for Internet of Things, and TCP performance over different routing protocols used in mobile ad-hoc networks are some of the topics discussed in different chapters of this book which fall under the domain of communication.Moreover, there are chapters in this book discussing topics like applications of geographic informationsystems, use of radar for road safety, image segmentation and digital media processing, web content management system, human computer interaction, and natural language processing in the context of Bodo language. These chapters may fall under broader domain of computation. Issues like robot navigation exploring cloud technology, and application of big data analytics in higher education are also discussed in two different chapters.  These chapters fall under the domains of cloud and big data, respectively.

This book presents high-quality papers from an international forum for research on computational approaches to learning. It includes current research and findings from various research labs, universities and institutions that may lead to development of marketable products. It also provides solid support for these findings in the form of empirical studies, theoretical analysis, or comparison to psychological phenomena. Further, it features work that shows how to apply learning methods to solve important application problems as well as how machine learning research is conducted. The book is divided into two main parts: Machine Learning Techniques, which covers machine learning-related research and findings; and, Data Analytics, which introduces recent developments in this domain. Additionally, the book includes work on data analytics using machine learning techniques.

This book is an outcome of the second national conference on Communication, Cloud and Big Data (CCB) held during November 10-11, 2016 at Sikkim Manipal Institute of Technology. The nineteen chapters of the book are some of the accepted papers of CCB 2016. These chapters have undergone review process and then subsequent series of improvements. The book contains chapters on various aspects of communication, computation, cloud and big data. Routing in wireless sensor networks, modulation techniques, spectrum hole sensing in cognitive radio networks, antenna design, network security, Quality of Service issues in routing, medium access control protocol for Internet of Things, and TCP performance over different routing protocols used in mobile ad-hoc networks are some of the topics discussed in different chapters of this book which fall under the domain of communication.Moreover, there are chapters in this book discussing topics like applications of geographic informationsystems, use of radar for road safety, image segmentation and digital media processing, web content management system, human computer interaction, and natural language processing in the context of Bodo language. These chapters may fall under broader domain of computation. Issues like robot navigation exploring cloud technology, and application of big data analytics in higher education are also discussed in two different chapters.  These chapters fall under the domains of cloud and big data, respectively.

This book presents the latest research on computational approaches to learning. It includes high-quality peer-reviewed papers from the “Intelligent and Interactive Computing Conference (IIC 2018)” organized by the Universiti Teknikal Malaysia, Melaka. It uses empirical studies, theoretical analysis, and comparisons with psychological phenomena to show how learning methods can be employed to solve important application problems. The book also describes ongoing research in various research labs, universities and institutions, which may lead to the development of marketable products.

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.

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.

This book presents the outcomes of the Third National Conference on Communication, Cloud and Big Data (CCB) held on November 2–3, 2018, at Sikkim Manipal Institute of Technology, Majitar, Sikkim. Featuring a number of papers from the conference, it explores various aspects of communication, computation, cloud, and big data, including routing in cognitive radio wireless sensor networks, big data security issues, routing in ad hoc networks, routing protocol for Internet of things (IoT), and algorithm for imaging quality enhancement.

This book presents the outcomes of the Third National Conference on Communication, Cloud and Big Data (CCB) held on November 2–3, 2018, at Sikkim Manipal Institute of Technology, Majitar, Sikkim. Featuring a number of papers from the conference, it explores various aspects of communication, computation, cloud, and big data, including routing in cognitive radio wireless sensor networks, big data security issues, routing in ad hoc networks, routing protocol for Internet of things (IoT), and algorithm for imaging quality enhancement.

Focusing on soft computing techniques and application in various engineering research domains, this book presents the state-of-the-art outcomes from ongoing research works being conducted in various research laboratories and educational institutions.

This book includes high-quality papers presented at the Second International Conference on Data Science and Management (ICDSM 2021), organized by the Gandhi Institute for Education and Technology, Bhubaneswar, from 19 to 20 February 2021.

This book includes high-quality papers presented at the Second International Conference on Data Science and Management (ICDSM 2021), organized by the Gandhi Institute for Education and Technology, Bhubaneswar, from 19 to 20 February 2021.

This book includes high-quality papers presented at the Third International Conference on Data Science and Management (ICDSM 2024), organized by the Gandhi Institute for Education and Technology, Bhubaneswar, from December 13–14, 2024.