Advancements In The Processing Characterization And Application Of Lightweight Materials

"This book of contributed chapters will provide the resources necessary for processing, characterization and manufacturing using lightweight materials across the globe, offering recent advances in the field of light weight material usage and its recent developments"--

In the automotive industry, the need to reduce vehicle weight has given rise to extensive research efforts to develop aluminum and magnesium alloys for structural car body parts. In aerospace, the move toward composite airframe structures urged an increased use of formable titanium alloys. In steel research, there are ongoing efforts to design novel damage-controlled forming processes for a new generation of efficient and reliable lightweight steel components. All these materials, and more, constitute today’s research mission for lightweight structures. They provide a fertile materials science research field aiming to achieve a better understanding of the interplay between industrial processing, microstructure development, and the resulting material properties. The Handbook of Research on Advancements in the Processing, Characterization, and Application of Lightweight Materials provides the recent advancements in the lightweight mat materials processing, manufacturing, and characterization. This book identifies the need for modern tools and techniques for designing lightweight materials and addresses multidisciplinary approaches for applying their use. Covering topics such as numerical optimization, fatigue characterization, and process evaluation, this text is an essential resource for materials engineers, manufacturers, practitioners, engineers, academicians, chief research officers, researchers, students, and vice presidents of research in government, industry, and academia.

In the automotive and aerospace industries, the need for strong yet light materials has given rise to extensive research into aluminum and magnesium alloys and formable titanium alloys. All of these are categorized as light weight materials. The distinguishing feature of light weight materials is that they are low density, but they have a wide range of properties and, as a result, a wide range of applications. This book provides researchers and students with an overview of the recent advancements in light weight material processing, manufacturing and characterization. It contains chapters by eminent researchers on topics associated with light weight materials, including on the current buzzword “composite materials”. First, this book describes the current status of light weight materials. Then, it studies applications of these materials, given that, as the densities vary, so do the applications, ranging from automobiles and aviation to bio-mechatronics. This book will therefore serve as an excellent guide to this field.

This book covers the most important aspects of lightweight metal alloys including history, physical metallurgy, overview of production technologies, alloy development, compositing, post-processing (heat treatment, surface engineering, bulk-deformation), and joining methodologies. It discusses the microstructural evolution, fractography, morphology of corroded and worn surface to enable easy understanding of the mechanism. The topics covered in this book include lightweight metallic materials, instrumental characterization of light weight metal alloys and composites, severe plastic deformation processing of aluminum alloys, solid-state welding of aluminum alloys, aluminum metal matrix composite for automotive and aircraft applications, and heat treatment of aluminum metal matrix composites. The book is highly useful for students, researchers, academicians, scientists, and engineers working on lightweight materials.

In today's digital age, the rapid advancement of AI and digital technologies has led to the emergence of digital consciousness, blurring the lines between human and machine thinking. At the same time, these technologies offer unprecedented convenience and efficiency but pose significant challenges. Individuals are increasingly facing issues such as stress, anxiety, and technology addiction, impacting their overall well-being and decision-making processes. The dichotomy between digital consciousness and human consciousness raises critical questions about how we can navigate these challenges in a rapidly evolving technological landscape. To address these pressing concerns, Comparative Analysis of Digital Consciousness and Human Consciousness: Bridging the Divide in AI Discourse offers a comprehensive exploration of the impacts of digital consciousness on human well-being and decision-making. This book delves into the paradoxes and challenges posed by the coexistence of digital and human consciousness, providing insights from psychological perspectives, practitioner experiences, and academic research. By offering a nuanced understanding of these concepts, we aim to equip readers with the knowledge and tools needed to manage the implications of digital consciousness in their personal and professional lives.

In the present era, technological developments are increasing the efficiency and potential of each stakeholder in a business. Robotic process automation is one of the key areas that can be applied in business organizations and corporate sectors to enhance productivity and show a path to success. Application and Adoption of Robotic Process Automation for Smart Cities provides relevant theoretical frameworks and various developments in the area of robotic process automation. Covering topics such as banking and financial services, public engagement, and smart cities, this premier reference source is a valuable resource for business leaders, IT managers, government officials, engineers, students and educators of higher education, researchers, and academicians.

Meta-learning, or learning to learn, has been gaining popularity in recent years to adapt to new tasks systematically and efficiently in machine learning. In the book, Meta-Learning Frameworks for Imaging Applications, experts from the fields of machine learning and imaging come together to explore the current state of meta-learning and its application to medical imaging and health informatics. The book presents an overview of the meta-learning framework, including common versions such as model-agnostic learning, memory augmentation, prototype networks, and learning to optimize. It also discusses how meta-learning can be applied to address fundamental limitations of deep neural networks, such as high data demand, computationally expensive training, and limited ability for task transfer. One critical topic in imaging is image segmentation, and the book explores how a meta-learning-based framework can help identify the best image segmentation algorithm, which would be particularly beneficial in the healthcare domain. This book is relevant to healthcare institutes, e-commerce companies, and educational institutions, as well as professionals and practitioners in the intelligent system, computational data science, network applications, and biomedical applications fields. It is also useful for domain developers and project managers from diagnostic and pharmacy companies involved in the development of medical expert systems. Additionally, graduate and master students in intelligent systems, big data management, computational intelligent approaches, computer vision, and biomedical science can use this book for their final projects and specific courses.

In the swiftly evolving realm of technology, the challenge of classical computing's constraints in handling intricate problems has become pronounced. While classical computers excel in many areas, they struggle with complex issues in cryptography, optimization, and molecular simulation. Addressing these escalating challenges requires a disruptive solution to push the boundaries of computation and innovation. Principles and Applications of Quantum Computing Using Essential Math, authored by A. Daniel, M. Arvindhan, Kiranmai Bellam, and N. Krishnaraj. This guide pioneers the transformative potential of quantum computing by seamlessly blending rigorous mathematics with quantum theory. It equips scholars, researchers, and aspiring technologists with insights to grasp and harness quantum computing's capabilities. By delving into quantum gates, algorithms, and error correction techniques, the book demystifies quantum computing, inviting exploration of quantum machine learning, cryptography, and the dynamic interplay between classical and quantum computing. As the quantum landscape expands, this book acts as a vital companion, navigating readers through the converging realms of industry, academia, and innovation. Principles and Applications of Quantum Computing Using Essential Math arrives as a timely answer to the limitations of classical computing, providing scholars with an essential roadmap to navigate the quantum technology landscape. With its clear explanations, practical applications, and forward-looking perspectives, this book serves as an indispensable tool for unraveling quantum computing's mysteries and driving innovation into uncharted domains.