The thesis contains several pioneering results at the intersection of state-of-the-art materials characterization techniques and machine learning. The use of machine learning empowers the information extraction capability of neutron and photon spectroscopies. In particular, new knowledge and new physics insights to aid spectroscopic analysis may hold great promise for next-generation quantum technology. As a prominent example, the so-called proximity effect at topological material interfaces promises to enable spintronics without energy dissipation and quantum computing with fault tolerance, yet the characteristic spectral features to identify the proximity effect have long been elusive. The work presented within permits a fine resolution of its spectroscopic features and a determination of the proximity effect which could aid further experiments with improved interpretability. A few novel machine learning architectures are proposed in this thesis work which leverage the case when the data is scarce and utilize the internal symmetry of the system to improve the training quality. The work sheds light on future pathways to apply machine learning to augment experiments.

TECHNOLOGY INNOVATION FOR THE CIRCULAR ECONOMY The book comprises 56 peer-reviewed chapters comprehensively covering in-depth areas of circular economy design, planning, business models, and enabling technologies. Some of the greatest opportunities for innovation in the circular economy are in remanufacturing, refurbishment, reuse, and recycling. Critical to its growth, however, are developments in product design approaches and the manufacturing business model that are often met with challenges in the current, largely linear economies of today’s global manufacturing chains. The conference hosted by the REMADE Institute in Rochester, NY, brought together U.S. and international researchers, industry engineers, technologists, and policymakers, to discuss the myriad intertwining issues relating to the circular economy. This book consists of 56 chapters in 10 distinct parts covering broad areas of research and applications in the circular economy area. The first four parts explore the system level work related to circular economy approaches, models and advancements including the use of artificial intelligence (AI) and machine learning to guide implementation, as well as design for circularity approaches. Mechanical and chemical recycling technologies follow, highlighting some of the most advanced research in those areas. Next, innovation in remanufacturing is addressed with descriptions of some of the most advanced work in this field. This is followed by tire remanufacturing and recycling, highlighting innovative technologies in addressing the volume of end-of-use tires. Pathways to net-zero emissions in manufacturing of materials concludes the book, with a focus on industrial decarbonization. Audience This book has a wide audience in academic institutes, business professionals and engineers in a variety of manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals.

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This book captures the path of digital transformation that the cement enterprises are adopting progressively to elevate themselves to ‘Industry 4.0’ level. Digital innovations-based Internet of Things (IoT) and Artificial Intelligence (AI) are pertinent technologies for the cement enterprises as the manufacturing processes operate at very large scales with multiple inputs, outputs, and variables, resulting in the essentiality of big data management. Featuring contributions from cement industries worldwide, it covers various aspects of cement manufacturing from IoT, machine learning and data analytics perspective. It further discusses implementation of digital solutions in cement process and plants through case studies. Features: Present an up-to-date, consolidated view on modern cement manufacturing technology, applying new systems. Provides narration of complexity and variables in modern cement plants and processes. Discusses evolution of automation and computerization for the manufacturing processes. Covers application of ERP techniques to cement enterprises. Includes data-driven approaches for energy, environment, and quality management. This book aims at researchers and industry professionals involved in cement manufacturing, cement machinery and system suppliers, chemical engineering, process engineering, industrial engineering, and chemistry.

The text presents the latest research and development, technical challenges, and future directions in the field of hybrid metal additive manufacturing. It further discusses the modeling of hybrid additive manufacturing processes for metals, hybrid additive manufacturing of composite materials, and low-carbon hybrid additive manufacturing processes. THIS BOOK •Presents cutting-edge advancements and limitations in hybrid additive manufacturing technologies. • Discusses fabrication methods and rapid tooling techniques focusing on metals, composites, and alloys. •Highlights the importance of low-carbon additive manufacturing technologies toward achieving sustainability. •Emphasizes the challenges and solutions for integrating additive manufacturing and Industry 4.0 to enable rapid manufacturing of customized and tailored products. • Covers hybrid additive manufacturing of composite materials and additive manufacturing for fabricating high-hardness components. The text discusses the recent advancements in additive manufacturing of high-hardness components and covers important engineering materials such as metals, alloys, and composites. It further highlights defects and post-processing of hybrid additive manufacturing components, sustainability solutions for hybrid additive manufacturing processes, and recycling of machining waste into metal powder feedstock. It will serve as an ideal reference text for senior undergraduate and graduate students, and researchers in fields including mechanical engineering, aerospace engineering, manufacturing engineering, and production engineering.

This book is as an extension of previous book “Computer Vision and Machine Learning in Agriculture” for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies.

Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com

Nature-Inspired Sensors presents and discusses the basic principles and latest developments in nature-inspired sensing and biosensing materials as well as the design and mechanisms for analyzing their potential in multifunctional sensing applications. The book starts with a comprehensive review of certain fundamental mechanisms in different living creatures, including humans, animals, and plants. It presents and discusses ways for imitating various nature-inspired structural features and their functional properties, such as hierarchical, interlocked, porous, and bristle-like structures and hetero-layered brick-and-mortar structures. It also highlights the utility of these structures and their properties for sensing functions, which include static coloration, self-cleaning, adhesive, underwater navigation and object detection, electric charge generation, and sensitive olfactory functions for detecting various substances. This is followed by an appraisal of accumulating knowledge and its translation from the laboratory to the point-of-care phase, using selective sensors as well as desktop and wearable artificial sensing devices, for example, electronic noses and electronic skins, in conjunction with AI-assisted data processing and decision-making in the targeted field of application. In addition, the book offers an insight into the challenges of continuing the development of nature-inspired smart sensing and biosensing technology and their wider availability, which can be substantially improved. It is a valuable reference for graduates, undergraduates, researchers, and working professionals in the fields of chemistry, materials science, and biomedical and environmental science. - Discusses the current strategies for fabricating nature-derived bio/chemical sensors - Presents ways to apply nature-derived bio/chemical sensors in real life - Describes the future of nature-derived bio/chemical sensors