Bøger af Brojo Kishore Mishra

In today's context of intricate global challenges, encompassing climate crises, resource scarcity, and social disparities, the imperative for sustainable development has never been more pressing. While academic scholars and researchers are instrumental in crafting solutions, they often grapple with the intricate balance between theoretical concepts and practical implementation. This gap impedes the transformation of innovative ideas into tangible societal progress, leaving a void where effective real-world strategies for cross-industry sustainability should flourish. "Fostering Cross-Industry Sustainability With Intelligent Technologies" seeks to bridge this divide. This book is more than just a collection of pages; it serves as a roadmap for those determined to make a tangible impact. It brings together a diverse group of esteemed experts from various disciplines, offering a comprehensive spectrum of actionable insights, all grounded in the ethical imperatives of inclusivity and environmental responsibility. Anchored in the United Nations Sustainable Development Goals (SDGs), this volume serves as a guiding star, channeling theoretical expertise into practical solutions. For academic scholars, scientists, innovators, and students alike, Fostering Cross-Industry Sustainability With Intelligent Technologies is the definitive guidepost. It fosters a profound understanding of the real-world implications of research, promoting interdisciplinary collaborations that transcend conventional boundaries. This comprehensive book presents a wealth of sustainable science and intelligent technology applications, all while emphasizing the importance of ethics and societal impact. With visionary insights woven throughout its pages, it calls upon humanity to envision a future where challenges transform into opportunities, and sustainable development becomes an attainable reality.

Data Science and Interdisciplinary Research: Recent Trends and Applications is a compelling edited volume that offers a comprehensive exploration of the latest advancements in data science and interdisciplinary research. Through a collection of 10 insightful chapters, this book showcases diverse models of machine learning, communications, signal processing, and data analysis, illustrating their relevance in various fields. Key Themes: -Advanced Rainfall Prediction: Presents a machine learning model designed to tackle the challenging task of predicting rainfall across multiple countries, showcasing its potential to enhance weather forecasting.-Efficient Cloud Data Clustering: Explains a novel computational approach for clustering large-scale cloud data, addressing the scalability of cloud computing and data analysis.-Secure In-Vehicle Communication: Explores the critical topic of secure communication in in-vehicle networks, emphasizing message authentication and data integrity.-Smart Irrigation 4.0: Details a decision model designed for smart irrigation, integrating agricultural sensor data reliability analysis to optimize water usage in precision agriculture.-Smart Electricity Monitoring: Highlights machine learning-based smart electricity monitoring and fault detection systems, contributing to the development of smart cities.-Enhanced Learning Environments: Investigates the effectiveness of mobile learning in higher education, shedding light on the role of technology in shaping modern learning environments.-Coastal Socio-Economy Study: Presents a case study on the socio-economic conditions of coastal fishing communities, offering insights into the livelihoods and challenges they face.-Signal Noise Removal: Shows filtering techniques for removing noise from ECG signals, enhancing the accuracy of medical data analysis and diagnosis.-Deep Learning in Biomedical Research: Explores deep learning techniques for biomedical research, particularly in the realm of gene identification using Next Generation Sequencing (NGS) data.-Medical Diagnosis through Machine Learning: Concludes with a chapter on breast cancer detection using machine learning concepts, demonstrating the potential of AI-driven diagnostics.

Engineering plays a major role in solving real-world problems, from small inconveniences to societal or global concerns around food scarcity, water shortages, environmental damage, problems in housing or infrastructure and more. In today's rapidly evolving world, the development of the latest generation of engineering and technology is crucial for maintaining productivity, innovation, and improving our overall quality of life. Intelligent Engineering Applications and Applied Sciences for Sustainability is an essential research book that serves as a compilation of cutting-edge research and advancements in engineering, science, and technology, and more importantly, how the application of these advancements will guide the path to a more sustainable future. This book focuses on intelligent engineering applications, which encompass the design and implementation of embedded technologies in various domains. It covers a wide range of fields and their influence on the Sustainable Development Goals (SDGs), fostering interdisciplinary approaches and innovative solutions, including additive manufacturing technologies, aerospace science and engineering, agricultural advancements, computer science for sustainable development, applied biosciences, applied mathematics, industrial engineering, robotics and automation, transportation, future mobility, and much more. As an academic, rigorous exploration of various disciplines, this book serves as an invaluable resource for researchers, scholars, and professionals seeking to advance the frontiers of intelligent engineering applications and applied sciences for a sustainable future.

The rapid growth and capability of artificial intelligence, digital twin, and the internet of things are unlocking incredible opportunities to overcome some of the greatest environmental and social impact challenges currently facing the global community, such as feeding a growing population, safety, affordable housing, and environmental sustainability. The Handbook of Research on Applications of AI, Digital Twin, and Internet of Things for Sustainable Development provides an interdisciplinary platform encompassing research on the potential opportunities and risks of reaching sustainable development using artificial intelligence, digital twin, and the internet of things. Covering key topics such as big data, environmental protection, and smart cities, this major reference work is ideal for computer scientists, industry professionals, researchers, scholars, academicians, librarians, policymakers, practitioners, educators, and students.

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. It features research in which data science is used to facilitate the decision-making process in various application areas, and also covers a wide range of learning methods and their applications in a number of learning problems. The empirical studies, theoretical analyses and comparisons to psychological phenomena described contribute to the development of products to meet market demands.

Natural Language Processing in Artificial Intelligence, focuses on natural language processing, artificial intelligence, and allied areas. The book delves into natural language processing, which enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world.

Presents the latest scholarly research on handling large data sets with conventional data mining and provides information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is designed for professionals, researchers, and students.