2020 24th International Symposium On Vlsi Design And Test Vdat

This book constitutes the proceedings of the 26th International Symposium on VLSI Design and Test, VDAT 2022, which took place in Jammu, India, in July 2022. The 32 regular papers and 16 short papers presented in this volume were carefully reviewed and selected from 220 submissions. They were organized in topical sections as follows: Devices and Technology; Sensors; Analog/Mixed Signal; Digital Design; Emerging Technologies and Memory; System Design.

The wide gap between the existing security solutions and the actual practical deployment in smart manufacturing, smart home, and remote environments (with respect to wireless robotics) is one of the major reasons why we require novel strategies, mechanisms, architectures, and frameworks. Furthermore, it is also important to access and understand the different level of vulnerabilities and attack vectors in Wireless Sensor Network (WSN) and Wireless Robotics. This book includes an in-depth explanation of a secure and dependable Wireless Robotics (WR) architecture, to ensure confidentiality, authenticity, and availability. Features Blockchain technology for securing data at end/server side Emerging technologies/networking, like Cloud, Edge, Fog, etc., for communicating and storing data (securely). Various open issues, challenges faced in this era towards wireless robotics, including several future research directions for the future. Several real world’s case studies are included Chapters on ethical concerns and privacy laws, i.e., laws for service providers Security and privacy challenges in wireless sensor networks and wireless robotics The book is especially useful for academic researchers, undergraduate students, postgraduate students, and industry researchers and professionals.

Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques. Features: Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

This book provides a comprehensive overview of security vulnerabilities and state-of-the-art countermeasures using explainable artificial intelligence (AI). Specifically, it describes how explainable AI can be effectively used for detection and mitigation of hardware vulnerabilities (e.g., hardware Trojans) as well as software attacks (e.g., malware and ransomware). It provides insights into the security threats towards machine learning models and presents effective countermeasures. It also explores hardware acceleration of explainable AI algorithms. The reader will be able to comprehend a complete picture of cybersecurity challenges and how to detect them using explainable AI. This book serves as a single source of reference for students, researchers, engineers, and practitioners for designing secure and trustworthy systems.

Advanced Field-Effect Transistors: Theory and Applications offers a fresh perspective on the design and analysis of advanced field-effect transistor (FET) devices and their applications. The text emphasizes both fundamental and new paradigms that are essential for upcoming advancement in the field of transistors beyond complementary metal–oxide–semiconductors (CMOS). This book uses lucid, intuitive language to gradually increase the comprehension of readers about the key concepts of FETs, including their theory and applications. In order to improve readers’ learning opportunities, Advanced Field-Effect Transistors: Theory and Applications presents a wide range of crucial topics: • Design and challenges in tunneling FETs • Various modeling approaches for FETs • Study of organic thin-film transistors • Biosensing applications of FETs • Implementation of memory and logic gates with FETs The advent of low-power semiconductor devices and related implications for upcoming technology nodes provide valuable insight into low-power devices and their applicability in wireless, biosensing, and circuit aspects. As a result, researchers are constantly looking for new semiconductor devices to meet consumer demand. This book gives more details about all aspects of the low-power technology, including ongoing and prospective circumstances with fundamentals of FET devices as well as sophisticated low-power applications.

This book features high-quality research papers presented at the 4th International Conference on Computational Intelligence in Pattern Recognition (CIPR 2022), held at Indian Institute of Engineering Science and Technology, Shibpur, Howrah, West Bengal, India, during 23 – 24 April 2022. It includes practical development experiences in various areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.