Sustainable Utilization Of Nanoparticles And Nanofluids In Engineering Applications
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Sustainable Utilization of Nanoparticles and Nanofluids in Engineering Applications
In the present state of manufacturing industries, industrial and commercial components have been prepared for low energy consumption and high performance. Recent and emerging nanoparticles and nanofluid technologies must be incorporated into advanced manufacturing processes to improve the performance of sustainable materials and manufacturing processes. It is essential to assess the activities involved in nanoparticle and nanofluid applications, identify the potential impacts, and discuss various utilization methods for nanoparticles and nanofluids, the economy, the environment, and engineering applications. Sustainable Utilization of Nanoparticles and Nanofluids in Engineering Applications provides the latest research and significant potential to apply nanomaterials and nanofluids in various engineering applications. It is a reference guide to provide real-life problems with feasible potential systems, models, and examples related to the application, synthesis, innovations, and properties of advanced nanomaterials and nanofluids. Covering key topics including sustainable development, utilization, and innovation of nanoparticles and nanofluids, this reference work is ideal for industry professionals, material scientists, manufacturing industry professionals, material selectors, design engineers, machine instructors, administrators, researchers, academicians, postgraduates, scholars, and instructors.
Multidisciplinary Applications of AI Robotics and Autonomous Systems
As society transitions into the digital age, the demand for advanced robotics and autonomous systems has remained unchanged. However, the field faces significant challenges bridging the gap between current capabilities and the potential for brilliant, autonomous machines. While exact and efficient, current robotic systems need more sophistication and adaptability of human intelligence. This limitation restricts their application in complex and dynamic environments, hindering their ability to realize their potential fully. Multidisciplinary Applications of AI Robotics and Autonomous Systems addresses these challenges by presenting cutting-edge research and innovative robotics and autonomous systems solutions. By exploring topics such as digital transformation, IoT, AI, and cloud-native computing paradigms, readers will understand the latest advancements in the field. The book delves into theoretical frameworks, computational models, and experimental approaches, offering insights to help researchers and practitioners develop more intelligent and autonomous machines.
Handbook of Research on AI and ML for Intelligent Machines and Systems
The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.