This volume captures the success of India's Look East Policy (LEP) in promoting economic engagement with neighbouring countries in Asia and simultaneously its limitations in propelling growth in the bordering North Eastern Region - India's bridge head to South East Asia. It analyses the instrumental role of LEP in bringing a tectonic shift in India's foreign trade by redirecting the focus from the West to the East, thus leading to a fundamental change in the nature of India's economic interdependence. Besides discussing foreign trade, it expounds as to how LEP made India play an important role in the emerging Asian security architecture and liberated Indian foreign policy from being centred on South Asia. The essays also enumerate the reasons for LEP's failure in the North Eastern Region and chart out actionable programmes for course correction that might be factored into its latest edition - the Act East Policy. This book will interest scholars and researchers of international relations, international trade and economics, politics, and particularly those concerned with Northeast India.

This volume captures the success of India's Look East Policy (LEP) in promoting economic engagement with neighbouring countries in Asia and simultaneously its limitations in propelling growth in the bordering North Eastern Region - India's bridge head to South East Asia. It analyses the instrumental role of LEP in bringing a tectonic shift in India's foreign trade by redirecting the focus from the West to the East, thus leading to a fundamental change in the nature of India's economic interdependence. Besides discussing foreign trade, it expounds as to how LEP made India play an important role in the emerging Asian security architecture and liberated Indian foreign policy from being centred on South Asia. The essays also enumerate the reasons for LEP's failure in the North Eastern Region and chart out actionable programmes for course correction that might be factored into its latest edition - the Act East Policy. This book will interest scholars and researchers of international relations, international trade and economics, politics, and particularly those concerned with Northeast India.

This book examines the strategic and economic logic behind the Bangladesh-China-India-Myanmar (BCIM) Regional Cooperation. According to estimates, BCIM covers approximately 9 percent of the world's mass and 40 percent of the world's population spanning across four countries, constituting the confluence of East, Southeast and South Asia. It contributes about 13 percent to world trade but ironically only 5 percent to inter-regional trade. This volume compares the various approaches to cooperation - trade-led vs project-led, geo-political vs geo-strategic, Sino-centric vs India-led. The chapters explore the complex interplay of geo-economics and geo-politics associated with BCIM sub-regional cooperation in general, and the BCIM Economic Corridor (BCIM-EC) in particular. It points to the current challenges that impede globalisation and economic growth, and critically reviews implications for the stakeholders, institutional frameworks and the spatial impact of the Corridor, especially on the underdeveloped regions. The book discusses the geo-political, geo-economic and geo-strategic advantages that will accrue to the member countries once the sub-regional cooperation becomes fully functional. It advocates the adoption of best practices from similar sub-regional groupings across the globe. This book will be of great interest to scholars and researchers of politics and international relations, geo-politics, strategic studies, sub-regional cooperation, South Asian studies, India-China relations, foreign trade and economics, besides those dealing with foreign policy and development cooperation. It will especially benefit policymakers, development agencies and strategic think tanks.

This book examines the strategic and economic logic behind the Bangladesh-China-India-Myanmar (BCIM) Regional Cooperation. According to estimates, BCIM covers approximately 9 percent of the world's mass and 40 percent of the world's population spanning across four countries, constituting the confluence of East, Southeast and South Asia. It contributes about 13 percent to world trade but ironically only 5 percent to inter-regional trade. This volume compares the various approaches to cooperation - trade-led vs project-led, geo-political vs geo-strategic, Sino-centric vs India-led. The chapters explore the complex interplay of geo-economics and geo-politics associated with BCIM sub-regional cooperation in general, and the BCIM Economic Corridor (BCIM-EC) in particular. It points to the current challenges that impede globalisation and economic growth, and critically reviews implications for the stakeholders, institutional frameworks and the spatial impact of the Corridor, especially on the underdeveloped regions. The book discusses the geo-political, geo-economic and geo-strategic advantages that will accrue to the member countries once the sub-regional cooperation becomes fully functional. It advocates the adoption of best practices from similar sub-regional groupings across the globe. This book will be of great interest to scholars and researchers of politics and international relations, geo-politics, strategic studies, sub-regional cooperation, South Asian studies, India-China relations, foreign trade and economics, besides those dealing with foreign policy and development cooperation. It will especially benefit policymakers, development agencies and strategic think tanks.

The immense increase on the size and type of real time data generated across various edge computing platform results in unstructured databases and data silos. This edited book gathers together an international set of researchers to investigate the possibilities offered by data-fabric solutions; the volume focuses in particular on data architectures and on semantic changes in future data landscapes.

Advances of Artificial Intelligence in a Green Energy Environment reviews the new technologies in intelligent computing and AI that are reducing the dimension of data coverage worldwide. This handbook describes intelligent optimization algorithms that can be applied in various branches of energy engineering where uncertainty is a major concern. Including AI methodologies and applying advanced evolutionary algorithms to real-world application problems for everyday life applications, this book considers distributed energy systems, hybrid renewable energy systems using AI methods, and new opportunities in blockchain technology in smart energy. Covering state-of-the-art developments in a fast-moving technology, this reference is useful for engineering students and researchers interested and working in the AI industry.

Scalable and Distributed Machine Learning and Deep Learning Patterns is a practical guide that provides insights into how distributed machine learning can speed up the training and serving of machine learning models, reduce time and costs, and address bottlenecks in the system during concurrent model training and inference. The book covers various topics related to distributed machine learning such as data parallelism, model parallelism, and hybrid parallelism. Readers will learn about cutting-edge parallel techniques for serving and training models such as parameter server and all-reduce, pipeline input, intra-layer model parallelism, and a hybrid of data and model parallelism. The book is suitable for machine learning professionals, researchers, and students who want to learn about distributed machine learning techniques and apply them to their work. This book is an essential resource for advancing knowledge and skills in artificial intelligence, deep learning, and high-performance computing. The book is suitable for computer, electronics, and electrical engineering courses focusing on artificial intelligence, parallel computing, high-performance computing, machine learning, and its applications. Whether you're a professional, researcher, or student working on machine and deep learning applications, this book provides a comprehensive guide for creating distributed machine learning, including multi-node machine learning systems, using Python development experience. By the end of the book, readers will have the knowledge and abilities necessary to construct and implement a distributed data processing pipeline for machine learning model inference and training, all while saving time and costs.

The North London town of Edgware has a parish dating back to the Middle Ages and links further back to the ancient Watling Street. It gives its name to the Edgware Road and the former village served as the first/last stopping point to travellers riding out of and into London. With the arrival of the Underground extension in 1924, the traditional village was rapidly transformed into a suburban town. Today, still growing, Edgware is visibly steeped in history with reminders of the old-world village it once was, and the suburban town it has grown into. In spite of the many changes that have occurred in Edgware the town has retained its identity and much of its historical buildings. This fascinating selection of old and new images of Edgware will be essential reading for all those who know the town and the area.

Towards Social Justice brings together papers from various perspectives in the humanities and social sciences on different issues related to the impact of positive discrimination on marginalised communities with special reference to Scheduled Caste-groups in India. This book contains some of the articles presented at a national seminar organised by the ICSSR, North Eastern Regional Centre and tries to address the question of how the well-being of the Scheduled Caste population can be promoted, with emphasis on the North-Eastern region to enable them to live a dignified life. Has the policy of positive discrimination worked? Do the states implement the reservation policy for the SCs in letter and spirit? How effective is the SC and ST Commission in removing the social, economic and political deprivation of the Scheduled Castes? This book will be of great help to the government, both at the Centre and the States, while making policies for the marginalized groups to empower them.

The application of contemporary and emerging operational research optimization methods in renewable energy is vital to creating and maintaining sustainable environments across the planet. More research is needed to understand how modern and innovative technological solutions can enhance accessible global energy. Operational Research for Renewable Energy and Sustainable Environments is a critical scholarly resource that examines the efficient use of modern electrical technology and renewable energy sources that have a positive impact on sustainable development. Highlighting topics such as cogeneration thermal modules, photovoltaic (PV) solar, and renewable energy systems (RES) application practices, this publication is geared towards academics, advocates, government officials, policymakers, humanized managers, practitioners, professionals, and students interested in the latest research on renewable energy and clean technology for sustainable rural development.

Using digital and mobile technologies provides smart healthcare options for the inhabitants of urban centers. The IOT revolution that has exploded in the segment of energy, transportation, security and infrastructure will have sweeping healthcare implications. A centralized healthcare system, data collection and sharing, analysis and testing methods will usher in a new age to combat modern times. Emerging technologies like Artificial Intelligence, 5G, and smart cameras as well as innovative strategies and design are just a few of the ways smart cities can address healthcare problems. Smart cities rely heavily on sensors to perceive parameters such as temperature, humidity, allergens, pollution and power grid status. All these affect deeply the way cities function and the adaptation phase cities will pass in achieving a balanced 'out of danger' co-living with Covid-19. The scope of this publication encompasses empirical work and scientific documentation on the two meeting areas: resilience and the smart city in the case of the Covid-19 pandemic in cities. Moreover, interface concept development and urban technologies production systems that can be replicable in many cities, including AI, machine learning and ICT are discussed. Strategically responding to system data updates enables healthcare to be smarter. Building capacity programs on how a community might gain universal access to valuable information, partners, networks, new learning paradigms and/or to eventually familiarize itself with innovative tracking, mentoring and fighting technologies and address the challenges in solving today's healthcare challenges.

Society, Representations and Textuality: The Critical Interface brings together papers from various critical perspectives of Humanities and Social Sciences. The work (a) takes stock of the recent developments in critical theory and cultural studies; (b) studies the impact of these developments on the understanding of social reality and the human predicament in India; and (c) brings together scholars from North East India who are engaged in the project of understanding society and communities in their chosen intellectual practice. The book is the first-ever attempt to establish a dialogic encounter between critical practices in Humanities and Social sciences, hitherto considered to be autonomous in their own disciplinary boundaries. Further, the volume addresses issues of identity and autonomy of a multicultural India, particularly with reference to the interface between hegemonic cultures and politically and culturally persistent smaller communities. A significant feature of this book is its attempt to theorize and describe the myriad manifestations of the critical interface between society and literary or cultural productions.

The perception of smart cities encompasses a strategy that uses different types of technologies, artificial intelligence (AI), and machine learning and in which, through the internet of things (IoT) and sensor-based data collection, the strategy extrapolates information using insights gained from that data to manage or monitor or track assets, resources, and services efficiently in an urban area. Both these models deeply affect the localities where they are applied and can create together immense possibilities for urban recovery, better quality of life, physical and mental health protection, and economic and social redevelopment. Smart Cities and Machine Learning in Urban Health promotes interdisciplinary work that develops and illustrates the concept of resilience in relation to smart city and machine learning. The book examines the ability of an area and its communities to recover quickly from difficulties; the rigidness and resistance of an area and its communities to possible crisis; the ability of an area, its communities, infrastructure, and business to spring back into shape; and the responsiveness and mitigation towards the crisis with a special look at the impact of the COVID-19 pandemic. The research's theoretical foundation rests on a wide range of non-architectural sources, primarily AI, sociology, urban studies, and technological development, but it explores everything on cases taken from real cities, thus transforming them into pieces of architectural interest. Covering topics such as carbon emissions, digital healthcare systems, and urban transformation, this book is an essential resource for graduate and post-graduate students, policymakers, researchers, university faculty, engineers, public management, hospital administration, professors, and academicians.

Advances in machine learning techniques and ever-increasing computing power has helped create a new generation of hardware and software technologies with practical applications for nearly every industry. As the progress has, in turn, excited the interest of venture investors, technology firms, and a growing number of clients, implementing intelligent automation in both physical and information systems has become a must in business. Handbook of Research on Smart Technology Models for Business and Industry is an essential reference source that discusses relevant abstract frameworks and the latest experimental research findings in theory, mathematical models, software applications, and prototypes in the area of smart technologies. Featuring research on topics such as digital security, renewable energy, and intelligence management, this book is ideally designed for machine learning specialists, industrial experts, data scientists, researchers, academicians, students, and business professionals seeking coverage on current smart technology models.

Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.