Jitendra Kumar – författare

Cloud computing offers subscription-based on-demand services, and it has emerged as the backbone of the computing industry. It has enabled us to share resources among multiple users through virtualization, which creates a virtual instance of a computer system running in an abstracted hardware layer. Unlike early distributed computing models, it offers virtually limitless computing resources through its large scale cloud data centers. It has gained wide popularity over the past few years, with an ever-increasing infrastructure, a number of users, and the amount of hosted data. The large and complex workloads hosted on these data centers introduce many challenges, including resource utilization, power consumption, scalability, and operational cost. Therefore, an effective resource management scheme is essential to achieve operational efficiency with improved elasticity. Machine learning enabled solutions are the best fit to address these issues as they can analyze and learn from the data. Moreover, it brings automation to the solutions, which is an essential factor in dealing with large distributed systems in the cloud paradigm.Machine Learning for Cloud Management explores cloud resource management through predictive modelling and virtual machine placement. The predictive approaches are developed using regression-based time series analysis and neural network models. The neural network-based models are primarily trained using evolutionary algorithms, and efficient virtual machine placement schemes are developed using multi-objective genetic algorithms.Key Features:The first book to set out a range of machine learning methods for efficient resource management in a large distributed network of clouds.Predictive analytics is an integral part of efficient cloud resource management, and this book gives a future research direction to researchers in this domain.It is written by leading international researchers.The book is ideal for researchers who are working in the domain of cloud computing.

Cloud computing offers subscription-based on-demand services, and it has emerged as the backbone of the computing industry. It has enabled us to share resources among multiple users through virtualization, which creates a virtual instance of a computer system running in an abstracted hardware layer. Unlike early distributed computing models, it offers virtually limitless computing resources through its large scale cloud data centers. It has gained wide popularity over the past few years, with an ever-increasing infrastructure, a number of users, and the amount of hosted data. The large and complex workloads hosted on these data centers introduce many challenges, including resource utilization, power consumption, scalability, and operational cost. Therefore, an effective resource management scheme is essential to achieve operational efficiency with improved elasticity. Machine learning enabled solutions are the best fit to address these issues as they can analyze and learn from the data. Moreover, it brings automation to the solutions, which is an essential factor in dealing with large distributed systems in the cloud paradigm.Machine Learning for Cloud Management explores cloud resource management through predictive modelling and virtual machine placement. The predictive approaches are developed using regression-based time series analysis and neural network models. The neural network-based models are primarily trained using evolutionary algorithms, and efficient virtual machine placement schemes are developed using multi-objective genetic algorithms.Key Features:The first book to set out a range of machine learning methods for efficient resource management in a large distributed network of clouds.Predictive analytics is an integral part of efficient cloud resource management, and this book gives a future research direction to researchers in this domain.It is written by leading international researchers.The book is ideal for researchers who are working in the domain of cloud computing.

This book focuses on the menace of metal pollution and its impact on plants, particularly food grains, pulse and vegetable plants covering morphological, anatomical, physiological and biochemical aspects. It includes comparative studies among metal hyper-accumulators (metallophytes) and non-accumulators including exogenous hormonal alleviation in them due to metal stress. Low dose stimulation effects are also reviewed. The most significant feature of the book is its extensive coverage of genomics, metabolomics, ionomics, proteomics and transcriptomics in metal non-hyper-accumulators and hyper-accumulators. Being an edited volume, the book incorporates a variety of research perspectives, enhancing the existing knowledge about metal pollution and points to newer avenues to be researched.

This book focuses on the menace of metal pollution and its impact on plants, particularly food grains, pulse and vegetable plants covering morphological, anatomical, physiological and biochemical aspects. It includes comparative studies among metal hyper-accumulators (metallophytes) and non-accumulators including exogenous hormonal alleviation in them due to metal stress. Low dose stimulation effects are also reviewed. The most significant feature of the book is its extensive coverage of genomics, metabolomics, ionomics, proteomics and transcriptomics in metal non-hyper-accumulators and hyper-accumulators. Being an edited volume, the book incorporates a variety of research perspectives, enhancing the existing knowledge about metal pollution and points to newer avenues to be researched.

The Lentil Genome: Genetics, Genomics and Breeding is a comprehensive volume on this important legume, from its economic importance to the latest in sequencing. The book includes botanical descriptions, discussion of lentil genetics, cytogenetics and breeding, molecular mapping genes and QTLs, as well as structural and functional genomics, genome sequencing, assembly, repetitive genome, gene annotation and synteny. Lentil [Lens culinaris ssp. culinaris Medikus] is among the earliest domesticates from the Near-East Fertile Crescent and plays a vital role in nutritional wellbeing and livelihood for the small-scale farmers in the dryland agricultural ecosystems of South Asia, Sub-Saharan Africa, West Asia, and North Africa. The classical plant breeding approach of selection-recombination-selection has been used successfully for genetic improvement in lentil. However further genetic improvement for developing the high yielding cultivars is required knowledge of gene network underlying the complex traits. Realizing the importance of genomics enabled improvement in crop plants, the scientific community has recently placed major emphasis on whole genome sequencing in many major crops including lentil. This compilation of the latest lentil genome research serves the immediate needs of students, scientists and is needed to strengthen conventional crop improvement strategies of lentil.

Focuses on the latest tools and strategies for genome sequencingIncludes discussions of public and private genome sequencing and how the information is leading to advancementsHighlights the impact on germplasm characterization gene discovery and generic improvement in post genome eraPresents insights from leading experts from around the globe

We live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyber security. We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements. However, they are undergoing rapid changes and need special attention. The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges. Therefore, there is a significant need to develop improved network management and cyber security solutions. To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges. More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.

We live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyber security. We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements. However, they are undergoing rapid changes and need special attention. The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges. Therefore, there is a significant need to develop improved network management and cyber security solutions. To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges. More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.

Cloud computing is the on-demand availability of computer system resources, especially data storage and computing power, without direct active management by the user. This book explores algorithms, protocols, and system design principles of key smart technologies including cloud computing and the internet of things.• Discusses the system design principles in cloud computing along with artificial intelligence, machine learning, and data analytics applications• Presents blockchain-based solutions, cyber-physical system applications, and deep learning approaches to solving practical problems• Highlights important concepts including the cloud of things architecture, cloud service management and virtualization, and resource management techniques• Covers advanced technologies including fog computing, edge computing, and distributed intelligence• Explores cloud-enabling technology, broadband networks and internet architecture, internet service providers (ISPs), and connectionless packet switching.The book is primarily written for graduate students, academic researchers, and professionals in the field of computer science and engineering, electrical engineering, and information technology.

This book is an introduction to fundamental techniques of image analysis with machine vision and their applicability in Industry 5.0. It provides basic and emerging techniques in the field of image analysis and machine vision in Industry 5.0. It also covers an extensive study of recent related work and research challenges in the field. Further, it discusses some effective solutions to address the challenges of digitally transforming industrial activities and improving their efficiency. Provides effective and robust machine vision-enabled methods across different industrial fields, emphasizing their applicability and reliability Covers the emerging concepts of image analysis and machine vision utilized in the digital transformation of manufacturing activities under Industry 5.0 Discusses conceptual methodologies of image analysis and machine vision tailored for various industrial applications, providing insights into their practical implementation Practical issues on implementing machine vision applications with image analysis techniques in Industry 5.0 are addressed, offering guidance on method implementation Includes case studies of various industrial processes, highlighting current challenges and presenting effective solutions, offering real-world insights into the application of machine visionIt is a reference book for research students, scientists, and professionals working in the fields of image processing, computer vision, and the Internet of Things.

This book covers essential molecular techniques for crop improvement, including genotyping methods, genetic mapping, and marker-assisted selection. The book examines statistical tools for marker analysis, allele mining strategies, and gene pyramiding approaches. It explores comparative genomics, proteomics applications, and biotechnology methods including recombinant DNA technology and also includes:Comprehensive coverage of molecular markers and genotyping techniques for crop improvementDetailed statistical tools and methodologies for marker analysis and genetic mappingPractical applications of marker-assisted selection and allele mining strategiesIntegration of genomics, proteomics, and biotechnology in plant breeding programsCurrent approaches to gene pyramiding and development of enhanced derived varietiesAdditional chapters address nanotechnology applications, male sterility systems, intellectual property rights, and bioinformatics tools. Designed for students and researchers in plant breeding, genetics, and biotechnology programs.This title has been co-published with Elite Publishing House. T&F does not sell or distribute the print versions in India.

Genetic engineering and biotechnology along with conventional breeding have played an important  role in developing superior cultivars by transferring economically important traits from distant, wild and even unrelated  species to the cultivated varieties which otherwise could not have been possible with conventional breeding. There is a vast amount of literature pertaining to the genetic improvement of crops over last few decades. However, the wonderful results achieved by crop scientists in food legumes’ research and development over the years are scattered in different journals of the World. The two volumes in the series ‘Alien Gene Transfer in Crop Plants’ address this issue and offer a comprehensive reference on the developments made in major food crops of the world. These volumes aim at bringing the contributions from globally renowned scientists at one platform in a reader-friendly manner. The 1st volume entitled, ‘Alien Gene Transfer in Crop Plants: Innovations, Methods and Risk Assessment” will deal exclusively with the process and methodology. The contents of this volume have been designed to appraise the readers with all the theoretical and practical aspects of wide hybridization and gene transfer like processes and methods of gene transfer, role of biotechnology with special reference to embryo rescue, genetic transformation, protoplast fusion and molecular marker technology, problems such as cross incompatibility and barriers to distant hybridization and solutions to overcome them. Since wild and weedy relatives of crop plants may have negative traits associated with them, there are always possibilities of linkage drag while transferring alien alleles. Therefore, problems and limitations of alien gene transfer from these species will also be discussed in this series. Further, the associated risks with this and assessment of risks will also be given due weightage.

Genetic engineering and biotechnology along with conventional breeding have played an important  role in developing superior cultivars by transferring economically important traits from distant, wild and even unrelated  species to the cultivated varieties which otherwise could not have been possible with conventional breeding. There is a vast amount of literature pertaining to the genetic improvement of crops over last few decades. However, the wonderful results achieved by crop scientists in food legumes’ research and development over the years are scattered in different journals of the World. The two volumes in the series ‘Alien Gene Transfer in Crop Plants’ address this issue and offer a comprehensive reference on the developments made in major food crops of the world. These volumes aim at bringing the contributions from globally renowned scientists at one platform in a reader-friendly manner. The second volume entitled, “Alien Gene Transfer in Crop Plants: Achievements and Impact” will deal more with the practical aspects. This volume will cover achievements of alien gene transfer in major food crops of the world and their impact on development of newer genetic variability and additional avenues for selection; development of superior cultivars for increased yield, resistance to biotic and abiotic stresses, improved nutritional and industrial quality; innovation of new techniques and positive as well as negative environmental implications. This volume has been divided into four groups with an aim to cover all major cereals, pulses, oilseeds and other crops (vegetable and horticultural crops) which are of economic importance.

Genetic engineering and biotechnology along with conventional breeding have played an important  role in developing superior cultivars by transferring economically important traits from distant, wild and even unrelated  species to the cultivated varieties which otherwise could not have been possible with conventional breeding. There is a vast amount of literature pertaining to the genetic improvement of crops over last few decades. However, the wonderful results achieved by crop scientists in food legumes’ research and development over the years are scattered in different journals of the World. The two volumes in the series ‘Alien Gene Transfer in Crop Plants’ address this issue and offer a comprehensive reference on the developments made in major food crops of the world. These volumes aim at bringing the contributions from globally renowned scientists at one platform in a reader-friendly manner. The 1st volume entitled, ‘Alien Gene Transfer in Crop Plants: Innovations, Methods and Risk Assessment” will deal exclusively with the process and methodology. The contents of this volume have been designed to appraise the readers with all the theoretical and practical aspects of wide hybridization and gene transfer like processes and methods of gene transfer, role of biotechnology with special reference to embryo rescue, genetic transformation, protoplast fusion and molecular marker technology, problems such as cross incompatibility and barriers to distant hybridization and solutions to overcome them. Since wild and weedy relatives of crop plants may have negative traits associated with them, there are always possibilities of linkage drag while transferring alien alleles. Therefore, problems and limitations of alien gene transfer from these species will also be discussed in this series. Further, the associated risks with this and assessment of risks will also be given due weightage.

Genetic engineering and biotechnology along with conventional breeding have played an important  role in developing superior cultivars by transferring economically important traits from distant, wild and even unrelated  species to the cultivated varieties which otherwise could not have been possible with conventional breeding. There is a vast amount of literature pertaining to the genetic improvement of crops over last few decades. However, the wonderful results achieved by crop scientists in food legumes’ research and development over the years are scattered in different journals of the World. The two volumes in the series ‘Alien Gene Transfer in Crop Plants’ address this issue and offer a comprehensive reference on the developments made in major food crops of the world. These volumes aim at bringing the contributions from globally renowned scientists at one platform in a reader-friendly manner. The second volume entitled, “Alien Gene Transfer in Crop Plants: Achievements and Impact” will deal more with the practical aspects. This volume will cover achievements of alien gene transfer in major food crops of the world and their impact on development of newer genetic variability and additional avenues for selection; development of superior cultivars for increased yield, resistance to biotic and abiotic stresses, improved nutritional and industrial quality; innovation of new techniques and positive as well as negative environmental implications. This volume has been divided into four groups with an aim to cover all major cereals, pulses, oilseeds and other crops (vegetable and horticultural crops) which are of economic importance.

Food legumes are important constituents of human and animal nutrition, supplying high quality proteins crucial for a balanced diet. These crops also play an important role in low-input agricultural production systems by fixing atmospheric nitrogen. Despite systematic and continuous breeding efforts by legume researchers all over the world, substantial genetic gains have not been achieved. These issues require immediate attention, and overall, a paradigm shift is needed in breeding strategies to strengthen our traditional crop improvement programs. To this end, Biology and Breeding of Food Legumes provides extensive information on their history, origin, evolution and botany, as well as breeding objectives and procedures, nutritional improvement, industrial uses, post-harvest technology and recent developments made through biotechnological intervention.

More than 20 million childhood deaths occur every year due to the micronutrient deficiency and diet-related non-communicable diseases (cardiovascular diseases, cancers, chronic respiratory diseases and diabetes).

More than 20 million childhood deaths occur every year due to the micronutrient deficiency and diet-related non-communicable diseases (cardiovascular diseases, cancers, chronic respiratory diseases and diabetes).

Identification of desirable genotypes with traits of interest is discernible for making genetic improvement of crop plants. In this direction, screening of a large number of germplasm for desirable traits and transfer of identified traits into agronomic backgrounds through recombination breeding is the common breeding approach.

Identification of desirable genotypes with traits of interest is discernible for making genetic improvement of crop plants. In this direction, screening of a large number of germplasm for desirable traits and transfer of identified traits into agronomic backgrounds through recombination breeding is the common breeding approach. Although visual screening is easier for qualitative traits, its use is not much effective for quantitative traits and also for those, which are difficult to score visually. Therefore, it is imperative to phenotype the germplasm accessions and breeding materials precisely using high throughput phenomics tools for challenging and complex traits under natural, controlled and harsh environmental conditions. Realizing the importance of phenotyping data towards identification and utilization of a germplasm as donors, global scientific community has exerted increased focus on advancing phenomics in crop plants leading to development of a number of techniques and methodologies for screening of agronomic, physiological, and biochemical traits. These technologies have now become much advanced and entered the era of digital science. This book provides exhaustive information on various aspects related to phenotyping of crop plants and offers a most comprehensive reference on the developments made in traditional and high throughput phenotyping of agricultural crops.

This book features original research papers presented at the International Conference on Computational and Applied Mathematics, held at the Indian Institute of Technology Kharagpur, India during November 23–25, 2018.

This book features original research papers presented at the International Conference on Computational and Applied Mathematics, held at the Indian Institute of Technology Kharagpur, India during November 23–25, 2018.

This book presents select proceedings of the Electric Power and Renewable Energy Conference 2020 (EPREC-2020). It provides rigorous discussions, case studies, and recent developments in the emerging areas of power electronics, especially, power inverter and converter, electrical drives, regulated power supplies, operation of FACTS & HVDC, etc.

This book presents select proceedings of the Electric Power and Renewable Energy Conference 2020 (EPREC-2020). It provides rigorous discussions, case studies, and recent developments in the emerging areas of power electronics, especially, power inverter and converter, electrical drives, regulated power supplies, operation of FACTS & HVDC, etc.

The book includes original research and case studies that present recent developments in the control system, especially load frequency control, wide-area monitoring, control & instrumentation, optimization, intelligent control, energy management system, SCADA systems, etc.

The volume contains peer-reviewed proceedings of EPREC 2021 with a focus on control applications in the modern power system. The book includes original research and case studies that present recent developments in the control system, especially load frequency control, wide-area monitoring, control & instrumentation, optimization, intelligent control, energy management system, SCADA systems, etc. The book will be a valuable reference guide for beginners, researchers, and professionals interested in advancements in the control system.

The book includes peer-reviewed papers on renewable energy economics and policy, renewable energy resource assessment, operations management and sustainability, energy audit, global warming, waste and resource management, green energy deployment, green buildings, integration of green energy, energy efficiency, etc.