This book explores how advances in graphic processing units (GPUs), programmable logic devices (TPUs), and field-programmable gate arrays have altered the serverless computing landscape (FPGAs). Distributed system architectures and implementations have undergone significant changes due to the popularity of serverless computing. Making and releasing product applications, doing market research, and maintaining customer interactions might all benefit from the reduced infrastructure expenses made possible by serverless computing. This book is a great resource for teachers and students interested in learning more about serverless computing. Some of the main questions surrounding serverless technology, such as scalability and performance distribution, are answered. Concepts and fundamentals of computing performance such as cost-free operation, good time and resource management, fairness, and interoperability are discussed. Serverless is at the forefront of this shift, which has made data-intensive, distributed applications, and open-source platforms essential for any modern computer to function. Data-centric queuing, real-time logging and monitoring, querying, and alarms are all examples of serverless services.

This book provide clear insight into the Internet of Drone for Academicians, Postdoc fellows, Research scholars, Graduate and Post-graduate students, Industry-fellows, and Software Engineers. This work will be useful to professionals who seek information about the Internet of Drones. Experts in Quantum Computing and Physics; Post-Quantum Cryptography; Data Scientists; and Data Analysts are among them. Quantum computing and security for Unmanned Aerial Vehicles (UAV) or Drones are widely useful for applications such as military, government, and non-government systems. Thus, this work explore these applications. The Internet of Drones offers vast prospects to improve everyday living for ordinary people. This work explores similar futuristic aspects.

This book offers a comprehensive analysis of the pre-Covid-19 and post-Covid-19 situation and public policy measures needed to revive the economy in the light of the recent initiatives by the state government, including a committee to suggest post-Covid-19 revival strategy. This collection of essays by specialized author/s in her/his/their area of research examines the impact of Covid-19 in the larger context of economic and developmental context of Punjab, ranging from basic developmental transformation analysis to the specific policy issues in each sector and policy domain, including the larger developmental crisis in the context of the regional economy and society of Punjab. The sectors analysed include: agriculture including dairy sector and agricultural markets, industry, services, education, health, besides fiscal, banking, diaspora, gender, governance, and sustainability challenges the state economy faces. It dwells on sector specific issues as well as ways forward for betterment of livelihoods of those engaged, especially farmers and industrial and service sector informal workers.

This book uses primary evidence to assess the value of agro-input and service delivery business models in terms of their inclusiveness, effectiveness and impact from a small farmer perspective, in the form of case studies in three Indian states: Punjab, Bihar and Uttar Pradesh. The services discussed include custom rental of farm machinery and equipment, franchising for backward and forward linkage for farmers and the supermarkets for delivery of farm inputs, and extension services. The book examines agro-input and service delivery business models as institutional innovations for inclusive and effective delivery of such services in the small farmer context, based on primary data from the agencies designing and implementing such models and the farmers who make use of these inputs and services. Further, it identifies major issues and challenges in the delivery of farm inputs and services across regions and types of farmers and examines possible policy and enabling provisions to promote cost-effective and high-quality agro-input delivery channels.

Autonomous and Connected Heavy Vehicle Technology presents the fundamentals, definitions, technologies, standards and future developments of autonomous and connected heavy vehicles. This book provides insights into various issues pertaining to heavy vehicle technology and helps users develop solutions towards autonomous, connected, cognitive solutions through the convergence of Big Data, IoT, cloud computing and cognition analysis. Various physical, cyber-physical and computational key points related to connected vehicles are covered, along with concepts such as edge computing, dynamic resource optimization, engineering process, methodology and future directions. The book also contains a wide range of case studies that help to identify research problems and an analysis of the issues and synthesis solutions. This essential resource for graduate-level students from different engineering disciplines such as automotive and mechanical engineering, computer science, data science and business analytics combines both basic concepts and advanced level content from technical experts.

Over the past few years, the demand for data traffic has experienced explosive growth thanks to the increasing need to stay online. New applications of communications, such as wearable devices, autonomous systems, drones, and the Internet of Things (IoT), continue to emerge and generate even more data traffic with vastly different performance requirements. With the COVID-19 pandemic, the need to stay online has become even more crucial, as most of the fields, would they be industrial, educational, economic, or service-oriented, had to go online as best as they can. As the data traffic is expected to continuously strain the capacity of future communication networks, these networks need to evolve consistently in order to keep up with the growth of data traffic. Thus, more intelligent processing, operation, and optimization will be needed for tomorrow’s communication networks. The Sixth Generation (6G) technology is latest approach for mobile systems or edge devices in terms of reduce traffic congestions, energy consumption blending with IoT devices applications.  The 6G network works beyond the 5G (B5G), where we can use various platforms as an application e.g. fog computing enabled IoT networks, Intelligent techniques for SDN network, 6G enabled healthcare industry, energy aware location management. Still this technology must resolve few challenges like security, IoT enabled trust network. This book will focus on the use of AI/ML-based techniques to solve issues related to 6G enabled networks, their layers, as well as their applications. It will be a collection of original contributions regarding state-of-the-art AI/ML-based solutions for signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction 6G enabled software-defined networking, congestion control, communication network optimization, security, and anomaly detection. The proposed edited book emphasis on the 6G network blended with Fog-IoT networks to introduce its applications and future perspectives that helps the researcher to apply this technique in their domain and it may also helpful to resolve the challenges and future opportunities with 6G networks.

Use of cutting fluids in metal cutting enhances machining performance. However, the use of cutting fluids results in problems such as high cost, pollution and hazards to operator's health. To overcome the problems related to the use of cutting fluids, researchers have made efforts to search for some alternatives to minimize or even avoid the use of cutting fluids in machining operations. MQL is one of the safe and environment friendly alternatives sought to reduce the use of coolant lubricant fluids in metal cutting.

Electrical discharge machining (EDM) is one of the most widely disseminated manufacturing technologies, in particular as regards the generation of accurate and complex geometrical shapes on hard metallic components. Nevertheless, current EDM has major limitations when dealing with fine surface finish and material removal rate. Recently EDM with powder mixed dielectric (PMEDM) has been a focus of intense research work in order to overcome these technological performance barriers. The present study is done with an objective to modify the machining characteristics like surface roughness, material removal rate, and hardness by adding different concentrations of TiO2 into the dielectric fluid of EDM. XRD and MAPING analysis has been carried out to find the migration of powder from the dielectric to the machined surface. SEM of the surface and the cross-section is also done to analyze the surface texture and recast layer. The results achieved show that minor amount of powder was migrated to machined surface, which resulted in surface improvement. The dielectric with added powder also shows significant improvement in material removal rate.