Kanak Kalita – författare

Nanostructured Thin Film Deposition by Sputtering: From Fundamentals to Applications provides an exhaustive overview of the significant influence of sputtering in the production of nanostructured thin films. It begins with a review of the historical evolution and fundamental principles inherent to sputtering before delving into a thorough examination of thin films, covering their distinctive properties, the impact of sputtering, and the role of target materials. Building upon this base, the book unveils advanced sputtering methodologies, augmented with applicable case studies. The book provides an in-depth study of nanostructured thin films, addressing their diverse forms, and the elaborate procedures for nanostructure characterization. Finally, it embarks on an extensive analysis of the broad range of applications of sputtered nanostructured thin films, with a focus on sectors such as electronics, optics, biomedicine, and environmental science, as well as promising domains like automotive, oil and gas, food, and energy sectors. This approach offers a sweeping view of sputtering, bridging basic concepts and sophisticated aspects, thereby crafting an invaluable compendium for both researchers and learners in the field.Covers the latest advances and applications of sputtering for depositing nanostructured thin filmsEmphasizes the importance of plasma diagnostics, materials characterization, and surface engineering in the field of thin film technologyIncludes practical examples and case studies that illustrate the potential of sputtered nanostructured thin films for a wide range of industries and applications

METAHEURISTICS for MACHINE LEARNING The book unlocks the power of nature-inspired optimization in machine learning and presents a comprehensive guide to cutting-edge algorithms, interdisciplinary insights, and real-world applications. The field of metaheuristic optimization algorithms is experiencing rapid growth, both in academic research and industrial applications. These nature-inspired algorithms, which draw on phenomena like evolution, swarm behavior, and neural systems, have shown remarkable efficiency in solving complex optimization problems. With advancements in machine learning and artificial intelligence, the application of metaheuristic optimization techniques has expanded, demonstrating significant potential in optimizing machine learning models, hyperparameter tuning, and feature selection, among other use-cases. In the industrial landscape, these techniques are becoming indispensable for solving real-world problems in sectors ranging from healthcare to cybersecurity and sustainability. Businesses are incorporating metaheuristic optimization into machine learning workflows to improve decision-making, automate processes, and enhance system performance. As the boundaries of what is computationally possible continue to expand, the integration of metaheuristic optimization and machine learning represents a pioneering frontier in computational intelligence, making this book a timely resource for anyone involved in this interdisciplinary field. Metaheuristics for Machine Learning: Algorithms and Applications serves as a comprehensive guide to the intersection of nature-inspired optimization and machine learning. Authored by leading experts, this book seamlessly integrates insights from computer science, biology, and mathematics to offer a panoramic view of the latest advancements in metaheuristic algorithms. You’ll find detailed yet accessible discussions of algorithmic theory alongside real-world case studies that demonstrate their practical applications in machine learning optimization. Perfect for researchers, practitioners, and students, this book provides cutting-edge content with a focus on applicability and interdisciplinary knowledge. Whether you aim to optimize complex systems, delve into neural networks, or enhance predictive modeling, this book arms you with the tools and understanding you need to tackle challenges efficiently. Equip yourself with this essential resource and navigate the ever-evolving landscape of machine learning and optimization with confidence. Audience The book is aimed at a broad audience encompassing researchers, practitioners, and students in the fields of computer science, data science, engineering, and mathematics. The detailed but accessible content makes it a must-have for both academia and industry professionals interested in the optimization aspects of machine learning algorithms.

This book is an essential guide for anyone looking to drive sustainable technological innovation, providing a comprehensive toolkit of decision-making methods and real-world applications to effectively manage technology in the era of Industry 5.0. Sustainable technological innovation is critical for building a more sustainable future. As the world faces increasing environmental challenges, there is a pressing need for new and innovative technologies that can reduce resource consumption, mitigate environmental impacts, and promote sustainable development. This book focuses on the vital role of decision-making processes in achieving sustainability through technological innovation in the context of Industry 5.0. By delving into various decision-making methods and approaches employed to facilitate sustainable technological innovation across essential industries such as manufacturing, agriculture, and energy, the book will present both theoretical and applied research on managing technology, including decision-making connected to Industry 4.0 and 5.0, artificial intelligence, and other revolutionary techniques. The book covers a wide range of topics, including multiple attribute decision theory, multiple objective decision-making, patent mining, big data analytics, and other decision-making methods and techniques, and features case studies and reviews that highlight real-world applications of sustainable technological innovation in different industries. The exploration of various decision-making methods and approaches for sustainable technological innovation makes this book an essential guide for those looking toward a sustainable Industry 5.0. Readers will find the book: Emphasizes the role of decision-making processes in enabling sustainable technological innovation, providing a unique perspective on the subject;Covers a wide range of topics related to decision-making for sustainable technological innovation, including decision theory, multiple attribute and objective decision-making, patent mining, big data analytics, and case studies;Provides real-world examples and case studies that demonstrate the effectiveness of decision-making processes in promoting sustainable technological innovation across various industries;Features the latest research and developments in the field, ensuring that readers are up-to-date on the most current thinking on decision-making for sustainable technological innovation.Audience Researchers, practitioners, and students in the fields of computer science, data science, engineering, and mathematics, specifically interested in decision analytics and machine learning algorithms.

Master the complexity of modern networks with this essential guide, which provides the state-of-the-art AI and machine learning techniques needed to execute seamless sensor data fusion and energy-efficient aggregation across Industrial IoT and smart city environments. The use of artificial intelligence and machine learning techniques for data aggregation and fusion is becoming increasingly important, as these technologies can help extract important features and knowledge from data. Sensor data aggregation and fusion are essential components of IoT and Industrial IoT systems, as they enable the combination of data from multiple sources to provide a more comprehensive view of the system being monitored. This book is a comprehensive guide to the state-of-the-art techniques and methods used for sensor data aggregation and fusion in IoT and Industrial IoT environments, covering the fundamental principles of data aggregation and fusion, as well as the latest advancements and applications in the field. The book takes a practical approach to the subject matter, providing a deeper understanding of the challenges and opportunities associated with sensor data aggregation and fusion in IoT and Industrial IoT environments. It covers topics such as machine learning-based data aggregation, intelligent multi-sensor fusion, data aggregation and fusion in smart cities, and energy-efficient data aggregation and fusion. Written by leading experts in the field, the book will provide a comprehensive overview of the latest advancements in sensor data aggregation and fusion in IoT and Industrial IoT environments.

The book is essential for anyone exploring the forefront of healthcare innovation, as it offers a thorough exploration of transformative data-driven methodologies that can significantly enhance patient outcomes and clinical efficiency in today’s evolving medical landscape. In today’s rapidly advancing healthcare landscape, the integration of medical analytics has become essential for improving patient outcomes, clinical efficiency, and decision-making. Medical Analytics for Clinical and Healthcare Applications provides a comprehensive examination of how data-driven methodologies are revolutionizing the medical field. This book offers a deep dive into innovative techniques, real-world applications, and emerging trends in medical analytics, showcasing how these advancements are transforming disease detection, diagnosis, treatment planning, and healthcare management. Spanning sixteen chapters across five subsections, this edited volume covers a wide array of topics—from foundational principles of medical data analysis to cutting-edge applications in predictive healthcare and medical data security. Readers will encounter state-of-the-art methodologies, including machine learning models, predictive analytics, and deep learning techniques applied to various healthcare challenges such as mental health disorders, cancer detection, and hospital mortality predictions. Medical Analytics for Clinical and Healthcare Applications equips readers with the knowledge to harness the power of medical analytics and its potential to shape the future of healthcare. Through its interdisciplinary approach and expert insights, this volume is poised to serve as a valuable resource for advancing healthcare technologies and improving the overall quality of care. Readers will find the volume: Explores the latest medical analytics techniques applied across clinical settings, from diagnosis to treatment optimization;Features real-world case studies and tools for implementing data-driven solutions in healthcare;Bridges the gap between healthcare professionals, data scientists, and engineers for collaborative innovation in medical technologies;Provides foresight into emerging trends and technologies shaping the future of healthcare analytics.Audience Healthcare professionals, clinical researchers, medical data scientists, biomedical engineers, IT professionals, academics, and policymakers focused on the intersection of medicine and data analytics.

Cultivate a more profitable and sustainable future for your agricultural operations with this essential book, which provides expert insights and real-world examples of how blockchain technology can revolutionize food safety, supply chain transparency, and market access for farmers globally. As global populations grow and environmental concerns rise, agriculture faces the dual challenges of increasing productivity and sustainability. Blockchain technology offers innovative solutions to these challenges by enhancing traceability, efficiency, and transparency in agricultural processes. This book delves into how blockchain can revolutionize various aspects of agriculture, from supply chain management to farm operations and market access. It addresses critical topics such as improving food safety through real-time traceability of produce from farm to fork, reducing fraud by securely recording transactions, and facilitating fair trade practices by providing transparent access to information across the value chain. The book also examines the economic implications of blockchain in agriculture, highlighting how this technology can help reduce costs, increase profitability, and provide small-scale farmers with better access to global markets. Additionally, it discusses the role of smart contracts in automating agricultural agreements and payments, reducing the need for intermediaries and enhancing the efficiency of operations. By focusing on practical applications and forward-looking innovations, this book aims to inform and inspire stakeholders in the agricultural sector to embrace blockchain technologies. Through a blend of expert insights and real-world examples, it paints a vivid picture of how blockchain can cultivate a more efficient, transparent, and sustainable future for agriculture.

Manufacturing, as an industry, has been undergoing huge transformation in recent times due to technological development, putting manufacturing at the intersection of traditional techniques and advanced computational intelligence. This new volume offers an understanding of the nuances of this transformation. It provides an exploration of high-strength steel sections and discusses the selection of a CNC lathe using the TOPSIS method. Bibliometric insights into multi-objective optimization and metaheuristic algorithms are also discussed as is the development of high entropy alloys. The book delves into practical applications of computational intelligence, including optimizing investment casting process parameters, enhancing mobile robot navigation performance, and more. The intricate processes behind fabrication are also explored along with a study of wear and thermal behaviors of advanced composite coatings.

This book covers a wide array of methods ranging from classical to metaheuristic to AI-enhanced approaches.The chapters are meticulously selected and organized in three sections—metaheuristics, machine learning and engineering applications.

This book unravels the intriguing interplay between macroscopic manufacturing processes and microscopic fabrication techniques. It dives into the sophisticated world of precision manufacturing, where high accuracy, controlled processes enable the production of complex components and products. It covers micro and nano fabrication, which revolutionizes conventional manufacturing by creating minuscule yet highly functional parts, some even smaller than the width of a human hair. This book explores various topics, from precise machining techniques to nanoimprint technology, reflecting the vast breadth and depth of this field. The aim is to provide readers with a comprehensive understanding of how these micro and macro scales intertwine, opening new frontiers in manufacturing. By showcasing the latest research findings and their practical applications, this book elucidates the enormous potential and implications of this burgeoning field. The contents are laid out in a user-friendly manner to communicate complex ideas in an accessible, engaging way, making it a valuable resource for anyone curious about the next big leap in manufacturing technology.

This book comprises select proceedings of the international conference ETAEERE 2020, and covers latest research in the areas of electronics, communication and computing. The book includes different approaches and techniques for specific applications using particle swarm optimization, Otsu’s function and harmony search optimization algorithm, DNA-NAND gate, triple gate SOI MOSFET, micro-Raman and FTIR analysis, high-k dielectric gate oxide, spectrum sensing in cognitive radio, microstrip antenna, GPR with conducting surfaces, energy efficient packet routing, iBGP route reflectors, circularly polarized antenna, double fork shaped patch radiator, implementation of Doppler radar at 24 GHz, iris image classification using SVM, digital image forgery detection, secure communication, spoken dialog system, and DFT-DCT spreading strategies. Given the range of topics covered, this book can be useful for both students and researchers working in electronics and communication.

This book comprises select proceedings of the international conference ETAEERE 2020, and covers latest research in the areas of electronics, communication and computing. The book includes different approaches and techniques for specific applications using particle swarm optimization, Otsu’s function and harmony search optimization algorithm, DNA-NAND gate, triple gate SOI MOSFET, micro-Raman and FTIR analysis, high-k dielectric gate oxide, spectrum sensing in cognitive radio, microstrip antenna, GPR with conducting surfaces, energy efficient packet routing, iBGP route reflectors, circularly polarized antenna, double fork shaped patch radiator, implementation of Doppler radar at 24 GHz, iris image classification using SVM, digital image forgery detection, secure communication, spoken dialog system, and DFT-DCT spreading strategies. Given the range of topics covered, this book can be useful for both students and researchers working in electronics and communication.