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This book provides an in-depth insight into the Indian society and the varied social issues it is currently faced with. While serving as a foundation and ready-reference resource, the book covers all important topics such as the role of Women in Indian Society, Population, Poverty, Urbanization and related issues of Communalism and Social Empowerment. It aims to not only equip an aspirant with all the relevant information required for scoring high marks but also help the future policy-makers to have a better understanding of what Indian society needs.
Microprocessors and Interfacing is a textbook for undergraduate engineering students who study a course on various microprocessors, its interfacing, programming and applications.
The most apt deciphering of Indus valley civilization script with the help of 43 bilingual-like inscriptions -from Dholavira to the bulls and chimera of Harappan seals. Old Tamil language is here proved beyond doubts to be the lingua franca of the Indus civilization people.
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This multi-disciplinary book presents the most recent advances in exergy, energy, and environmental issues. Volume 2 focuses on fundamentals in the field and covers current problems, future needs, and prospects in the area of energy and environment from researchers worldwide. Based on some selected lectures from the Eleventh International Exergy, Energy and Environmental Symposium (IEEES-11) and complemented by further invited contributions, this comprehensive set of contributions promote the exchange of new ideas and techniques in energy conversion and conservation in order to exchange best practices in "energetic efficiency." Included are fundamental and historical coverage of the green transportation and sustainable mobility sectors, especially regarding the development of sustainable technologies for thermal comforts and green transportation vehicles. Furthermore, contributions on renewable and sustainable energy sources, strategies for energy production, and the carbon-free society constitute an important part of this book.
Digital classrooms have become a common addition to curriculums in higher education; however, such learning systems are only successful if students are properly motivated to learn. Optimizing Student Engagement in Online Learning Environments is a critical scholarly resource that examines the importance of motivation in digital classrooms and outlines methods to reengage learners. Featuring coverage on a broad range of topics such as motivational strategies, learning assessment, and student involvement, this book is geared toward academicians, researchers, and students seeking current research on the importance of maintaining ambition among learners in digital classrooms.
Processing information and analyzing data efficiently and effectively is crucial for any company that wishes to stay competitive in its respective market. Nonlinear data presents new challenges to organizations, however, due to its complexity and unpredictability. The only technology that can properly handle this form of data is artificial neural networks. These modeling systems present a high level of benefits in analyzing complex data in a proficient manner, yet considerable research on the specific applications of these intelligent components is significantly deficient. Applications of Artificial Neural Networks for Nonlinear Data is a collection of innovative research on the contemporary nature of artificial neural networks and their specific implementations within data analysis. While highlighting topics including propagation functions, optimization techniques, and learning methodologies, this book is ideally designed for researchers, statisticians, academicians, developers, scientists, practitioners, students, and educators seeking current research on the use of artificial neural networks in diagnosing and solving nonparametric problems.
This book provides an overview of recycled polyesters, which are an important sustainable raw material in textile production. It discusses the manufacturing methods and the unique properties of recycled polyesters manufactured using the different methods. It also highlights the various test methods and identification mechanisms for recycled polyesters, which are very essential for ensuring the traceability and conformity of usage of recycled polyester in the final product.
Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing. There is a need for research that seeks to understand the development and efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a collection of innovative research that combines theory and practice on adopting the latest deep learning advancements for machines capable of visual processing. Highlighting a wide range of topics such as video segmentation, object recognition, and 3D modelling, this publication is ideally designed for computer scientists, medical professionals, computer engineers, information technology practitioners, industry experts, scholars, researchers, and students seeking current research on the utilization of evolving computer vision techniques.