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This book is based on the 18 tutorials presented during the 29th workshop on Advances in Analog Circuit Design. Expert designers present readers with information about a variety of topics at the frontier of analog circuit design, with specific contributions focusing on analog circuits for machine learning, current/voltage/temperature sensors, and high-speed communication via wireless, wireline, or optical links. This book serves as a valuable reference to the state-of-the-art, for anyone involved in analog circuit research and development.
This book is based on the 18 tutorials presented during the 30th workshop on Advances in Analog Circuit Design. Expert designers present readers with information about a variety of topics at the frontier of analog circuit design, with specific contributions focusing on analog circuits for machine learning, current/voltage/temperature sensors, and high-speed communication via wireless, wireline, or optical links. This book serves as a valuable reference to the state-of-the-art, for anyone involved in analog circuit research and development.
This book presents a comprehensive discussion of the recent advances in Industry 4.0, manufacturing processes, and intelligent techniques. It will serve as an ideal reference text for graduate students and academic researchers in the fields of manufacturing engineering, industrial engineering, mechanical engineering, and production engineering. This text introduces Industry 4.0, its evolution, and essential pillars of Industry 4.0 including calibration, metrology, quality control, robotics, artificial intelligence, and the Internet of Things. It comprehensively covers important topics including the cold spray technique for additive manufacturing, tool condition monitoring, robotic manipulators, metrology, quality control, and the Internet of Things in Industry 4.0. The book: Discusses additive manufacturing and applications of lasers in advanced manufacturing Covers sensors, actuators, and calibration techniques for next-generation industries Emphasizes the recycling of materials for sustainable manufacturing Explores latest advances in the Internet of Things, robotics, artificial intelligence, and machine learning in view of Industry 4.0 Provides a conceptual framework of Industry 4.0 with the help of applications and case studies The text is primarily written for graduate students and academic researchers in the fields of manufacturing engineering, industrial engineering, mechanical engineering, and production engineering.
This book provides the state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research. The fifth 2020 Future Technologies Conference was organized virtually and received a total of 590 submissions from academic pioneering researchers, scientists, industrial engineers, and students from all over the world. The submitted papers covered a wide range of important topics including but not limited to computing, electronics, artificial intelligence, robotics, security and communications and their applications to the real world. After a double-blind peer review process, 210 submissions (including 6 poster papers) have been selected to be included in these proceedings. One of the meaningful and valuable dimensions of this conference is the way it brings together a large group of technology geniuses in one venue to not only present breakthrough research in future technologies, but also to promote discussions and debate of relevant issues, challenges, opportunities and research findings. The authors hope that readers find the book interesting, exciting and inspiring.
This book explores and motivates the need for building homogeneous and heterogeneous multi-core systems for machine learning to enable flexibility and energy-efficiency. Coverage focuses on a key aspect of the challenges of (extreme-)edge-computing, i.e., design of energy-efficient and flexible hardware architectures, and hardware-software co-optimization strategies to enable early design space exploration of hardware architectures. The authors investigate possible design solutions for building single-core specialized hardware accelerators for machine learning and motivates the need for building homogeneous and heterogeneous multi-core systems to enable flexibility and energy-efficiency. The advantages of scaling to heterogeneous multi-core systems are shown through the implementation of multiple test chips and architectural optimizations.
This book provides readers a good overview of some of most recent advances in the field of hybrid pixelated detectors for X-ray imaging. Coverage includes both technology and applications, with an in-depth review of the research topics conducted at leading research institutions in the world. The conversion of the X-ray signal into an analogue/digital value is discussed, as well as a review of CMOS chips used for X-ray image sensors. Applications of hybrid pixel detectors are discussed, such as medical imaging, high energy physics, space, non-destructive testing and security. Provides coverage of a broad range of topics, from international experts in academia and industry; Includes in-depth analysis of how to optimize X-ray detection and electronics for X-ray detection; Covers both technology and applications in a number of different domains.
Recently, Tiny Machine Learning (TinyML) has gained incredible importance due to its capabilities of creating lightweight machine learning (ML) frameworks aiming at low latency, lower energy consumption, lower bandwidth requirement, improved data security and privacy, and other performance necessities. As billions of battery-operated embedded IoT and low power wide area networks (LPWAN) nodes with very low on-board memory and computational capabilities are getting connected to the Internet each year, there is a critical need to have a special computational framework like TinyML. TinyML for Edge Intelligence in IoT and LPWAN Networks presents the evolution, developments, and advances in TinyML as applied to IoT and LPWANs. It starts by providing the foundations of IoT/LPWANs, low power embedded systems and hardware, the role of artificial intelligence and machine learning in communication networks in general and cloud/edge intelligence. It then presents the concepts, methods, algorithms and tools of TinyML. Practical applications of the use of TinyML are given from health and industrial fields which provide practical guidance on the design of applications and the selection of appropriate technologies. TinyML for Edge Intelligence in IoT and LPWAN Networks is highly suitable for academic researchers and professional system engineers, architects, designers, testers, deployment engineers seeking to design ultra-lower power and time-critical applications. It would also help in designing the networks for emerging and future applications for resource-constrained nodes. - This book provides one-stop solutions for emerging TinyML for IoT and LPWAN applications. - The principles and methods of TinyML are explained, with a focus on how it can be used for IoT, LPWANs, and 5G applications. - Applications from the healthcare and industrial sectors are presented. - Guidance on the design of applications and the selection of appropriate technologies is provided.
New Materials and Devices for 5G Applications and Beyond focuses on the materials, device architectures and enabling integration schemes for 5G applications and emerging technologies. It gives a comprehensive overview of the trade-offs, challenges and unique properties of novel upcoming technologies. Starting from the application side and its requirements, the book examines different technologies under consideration for the different functions, both more conventional to exploratory, and within this context the book provides guidance to the reader on how to possibly optimize the system for a particular application. This book aims at guiding the reader through the technologies required to enable 5G applications, with the main focus on mm-wave frequencies, up to THz. New Materials and Devises for 5G Applications and Beyond is suitable for industrial researchers and development engineers, and researchers in materials science, device engineering and circuit design. - Reviews challenges and emerging opportunities for materials, devices, and integration to enable 5G technologies - Includes discussion of technologies such as RF-MEMs, RF FINFETs, and transistors based on current and emerging materials (InP, GaN, etc.) - Focuses on mm-wave frequencies up to the terahertz regime