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Showing 1 - 25 of 92 matches in All Departments
This book aims to provide information in the ever-growing field of low-power electronic devices and their applications in portable device, wireless communication, sensor, and circuit domains. . Negative Capacitance Field Effect Transistor: Physics, Design, Modeling and Applications, discusses low-power semiconductor technology and addresses state-of-art techniques such as negative-capacitance field-effect transistors and tunnel field-effect transistors. The book is broken up into four parts. Part one discusses foundations of low-power electronics including the challenges and demands and concepts like subthreshold swing. Part two discusses the basic operations of negative-capacitance field-effect transistor (NC-FET) and Tunnel Field-effect Transistor (TFET). Part three covers industrial applications including cryogenics and biosensors with NC-FET. This book is designed to be one-stop guidebook for students and academic researchers, to understand recent trends in the IT industry and semiconductor industry. It will also be of interest to researchers in the field of nanodevices like NC-FET, FinFET, Tunnel FET, and device-circuit codesign.
This new volume looks at the electrifying world of blockchain technology and how it has been revolutionizing the Internet of Things and cyber-physical systems. Aimed primarily at business users and developers who are considering blockchain-based projects, the volume provides a comprehensive introduction to the theoretical and practical aspects of blockchain technology. It presents a selection of chapters on topics that cover new information on blockchain and bitcoin security, IoT security threats and attacks, privacy issues, fault-tolerance mechanisms, and more. Some major software packages are discussed, and it also addresses the legal issues currently affecting the field. The information presented here is relevant to current and future problems relating to blockchain technology and will provide the tools to build efficient decentralized applications. Blockchain technology and the IoT can profoundly change how the world-and businesses-work, and this book provides a window into the current world of blockchain. No longer limited to just Bitcoin, blockchain technology has spread into many sectors and into a significant number of different technologies.
This book provides scientific and technological insights on novel techniques of design and manufacturing using laser technologies. It showcases applications of laser micromachining in the biomedical industry, laser-based manufacturing processes in aerospace engineering, and high-precision laser-cutting in the home appliance sector. Features: Each chapter discusses a specific engineering problem and showcases its numerical, and experimental solution Provides scientific and technological insights on novel routes of design and manufacturing using laser technologies Synergizes exploration related to the various properties and functionalities through extensive theoretical and numerical modeling Highlights current issues, developments, and constraints in additive manufacturing Discusses applications of laser cutting machines in the manufacturing industry and laser micromachining for the biomedical industry The text discusses optical, and laser-based green manufacturing technologies and their application in diverse engineering fields including mechanical, electrical, biomedical, and computer. It further covers sustainability issues in laser-based manufacturing technologies and the development of laser-based ultra-precision manufacturing techniques. The text also discusses the use of artificial intelligence and machine learning in laser-based manufacturing techniques. It will serve as an ideal reference text for senior undergraduate, graduate students, and researchers in fields including mechanical engineering, aerospace engineering, manufacturing engineering, and production engineering.
This book gives insight into the emerging semiconductor devices from their applications in electronic circuits. It discusses the challenges in the field of engineering and applications of advanced low-power devices. Emerging Low-Power Semiconductor Devices: Applications for Future Technology Nodes offers essential exposure to low-power devices, and applications in wireless, biosensing, and circuit domains. This book provides a detailed discussion on all aspects, including the current and future scenarios related to the low-power device. The book also presents basic knowledge about field-effect transistor (FET) devices and introduces emerging and novel FET devices. The chapters include a review of the usage of FET devices in various domains like biosensing, wireless, and cryogenics applications. The chapters also explore device-circuit co-design issues in the digital and analog domains. The content is presented in an easy-to-follow manner that makes it ideal for individuals new to the subject. This book is intended for scientists, researchers, and postgraduate students looking for an understanding of device physics, circuits, and systems.
Presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research Offers a compendium of current and emerging machine learning paradigms for healthcare informatics and reflects on the diversity and complexity through the use of case studies Provides a panoramic view of data and machine learning techniques and provides an opportunity for novel insights and discovers Explores the theory and practical applications of machine learning in healthcare Includes a guided tour of machine learning algorithms, architecture design, and applications and in interdisciplinary challenges
This new volume looks at the electrifying world of blockchain technology and how it has been revolutionizing the Internet of Things and cyber-physical systems. Aimed primarily at business users and developers who are considering blockchain-based projects, the volume provides a comprehensive introduction to the theoretical and practical aspects of blockchain technology. It presents a selection of chapters on topics that cover new information on blockchain and bitcoin security, IoT security threats and attacks, privacy issues, fault-tolerance mechanisms, and more. Some major software packages are discussed, and it also addresses the legal issues currently affecting the field. The information presented here is relevant to current and future problems relating to blockchain technology and will provide the tools to build efficient decentralized applications. Blockchain technology and the IoT can profoundly change how the world-and businesses-work, and this book provides a window into the current world of blockchain. No longer limited to just Bitcoin, blockchain technology has spread into many sectors and into a significant number of different technologies.
Machine Learning for Healthcare: Handling and Managing Data provides in-depth information about handling and managing healthcare data through machine learning methods. This book expresses the long-standing challenges in healthcare informatics and provides rational explanations of how to deal with them. Machine Learning for Healthcare: Handling and Managing Data provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of machine learning applications. These are illustrated in a case study which examines how chronic disease is being redefined through patient-led data learning and the Internet of Things. This text offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare. Readers will discover the ethical implications of machine learning in healthcare and the future of machine learning in population and patient health optimization. This book can also help assist in the creation of a machine learning model, performance evaluation, and the operationalization of its outcomes within organizations. It may appeal to computer science/information technology professionals and researchers working in the area of machine learning, and is especially applicable to the healthcare sector. The features of this book include: A unique and complete focus on applications of machine learning in the healthcare sector. An examination of how data analysis can be done using healthcare data and bioinformatics. An investigation of how healthcare companies can leverage the tapestry of big data to discover new business values. An exploration of the concepts of machine learning, along with recent research developments in healthcare sectors.
Magnetohydrodynamic Processes in Solar Plasmas provides comprehensive and up-to-date theory and practice surrounding the fundamentals of heliospheric research and the Sun’s basic plasma processes, covering the dynamics of the solar interior to its exterior in the framework of magnetohydrodynamics. The book covers novel aspects of solar and heliospheric physics, astrophysics, space science, and fundamentals of the fluids and plasmas. Topics covered include key phenomena in the solar interior such as magnetism, dynamo physics, and helioseismology, dynamics and plasma processes in its exterior, including fluid processes such as waves, shocks, instabilities, reconnection, dynamics in the partially ionized plasma, and much more. The book covers both the fundamentals of the topics included as well as current and future developments in the field, forming an essential, foundational reference for researchers, academics, and advanced students, in the field of solar physics and astrophysics, as well as neighboring disciplines.
MACHINE LEARNING TECHNIQUES FOR VLSI CHIP DESIGN This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, the efficient hardware of machine learning applications with FPGA or CMOS circuits, and many other aspects and applications of machine learning techniques for VLSI chip design. Artificial intelligence (AI) and machine learning (ML) have, or will have, an impact on almost every aspect of our lives and every device that we own. AI has benefitted every industry in terms of computational speeds, accurate decision prediction, efficient machine learning (ML), and deep learning (DL) algorithms. The VLSI industry uses the electronic design automation tool (EDA), and the integration with ML helps in reducing design time and cost of production. Finding defects, bugs, and hardware Trojans in the design with ML or DL can save losses during production. Constraints to ML-DL arise when having to deal with a large set of training datasets. This book covers the learning algorithm for floor planning, routing, mask fabrication, and implementation of the computational architecture for ML-DL. The future aspect of the ML-DL algorithm is to be available in the format of an integrated circuit (IC). A user can upgrade to the new algorithm by replacing an IC. This new book mainly deals with the adaption of computation blocks like hardware accelerators and novel nano-material for them based upon their application and to create a smart solution. This exciting new volume is an invaluable reference for beginners as well as engineers, scientists, researchers, and other professionals working in the area of VLSI architecture development.
This book highlights the molecular and cellular mechanisms involved in the initiation and progression of skin cancer. It also explains the role of the environment in skin cancer development and explores the potential of microbiome in the diagnosis, prevention and treatment of skin cancer. The book also presents potential biomarkers for early detection of skin cancer and discusses recent advances in skin cancer prevention and treatment using photodynamic therapy. Lastly, it summarizes the applications of biomedical engineering, non-coding and nanotechnology in the diagnosis and therapeutics in skin cancer. It is a valuable resource for investigators in the field of skin cancer, including pathologists, medical and surgical oncologists, and dermatologists.
This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniques and deploying novel technologies in intelligent healthcare services and applications. Describes the advances of computing methodologies for life and medical science data; Presents applications of artificial intelligence in healthcare along with case studies and datasets; Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.
This book summarizes various tools and techniques used to provide insights into the cellular and molecular pathophysiology of stroke. It also presents rodent animal models to help shed light on the pathophysiology of ischemic stroke. Presenting the latest information on the different types of stroke, including embolic, filament, photothrombotic, and bilateral common carotid artery, the book also describes techniques that are used for confirmation of stroke surgery, such as laser speckle imaging (LSI) and laser Doppler flowmetry (LDF), and discusses the non-human primates that are used in stroke surgery, cerebral venous sinuous thrombosis, and neurobehavioral assessment. Lastly, it analyzes various neuroprotective agents to treat and prevent ischemic stroke, and examines the challenges and advances in treating and preventing acute ischemic stroke.
This book highlights the molecular and cellular mechanisms involved in the initiation and progression of skin cancer. It also explains the role of the environment in skin cancer development and explores the potential of microbiome in the diagnosis, prevention and treatment of skin cancer. The book also presents potential biomarkers for early detection of skin cancer and discusses recent advances in skin cancer prevention and treatment using photodynamic therapy. Lastly, it summarizes the applications of biomedical engineering, non-coding and nanotechnology in the diagnosis and therapeutics in skin cancer. It is a valuable resource for investigators in the field of skin cancer, including pathologists, medical and surgical oncologists, and dermatologists.
This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniques and deploying novel technologies in intelligent healthcare services and applications. Describes the advances of computing methodologies for life and medical science data; Presents applications of artificial intelligence in healthcare along with case studies and datasets; Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.
This book combines the mainstream liberal arguments for religious tolerance with arguments from religious traditions in India to offer insights into appropriate attitudes toward religious 'others' from the perspective of the devout. The respective chapters address the relationship between religions from a comparative perspective, helping readers understand the meaning of religion and the opportunities for interreligious dialogue in the works of contemporary Indian philosophers such as Gandhi and Ramakrishna Paramhansa. It also examines various religious traditions from a philosophical viewpoint in order to reassess religious discussions on how to respond to differing and different religious others. Given its comprehensive coverage, the book is of interest to scholars working in the areas of anthropology, philosophy, cultural and religious diversity, and history of religion.
This book summarizes various tools and techniques used to provide insights into the cellular and molecular pathophysiology of stroke. It also presents rodent animal models to help shed light on the pathophysiology of ischemic stroke. Presenting the latest information on the different types of stroke, including embolic, filament, photothrombotic, and bilateral common carotid artery, the book also describes techniques that are used for confirmation of stroke surgery, such as laser speckle imaging (LSI) and laser Doppler flowmetry (LDF), and discusses the non-human primates that are used in stroke surgery, cerebral venous sinuous thrombosis, and neurobehavioral assessment. Lastly, it analyzes various neuroprotective agents to treat and prevent ischemic stroke, and examines the challenges and advances in treating and preventing acute ischemic stroke.
This book explores potentially disruptive and transformative healthcare-specific use cases made possible by the latest developments in Internet of Things (IoT) technology and Cyber-Physical Systems (CPS). Healthcare data can be subjected to a range of different investigations in order to extract highly useful and usable intelligence for the automation of traditionally manual tasks. In addition, next-generation healthcare applications can be enhanced by integrating the latest knowledge discovery and dissemination tools. These sophisticated, smart healthcare applications are possible thanks to a growing ecosystem of healthcare sensors and actuators, new ad hoc and application-specific sensor and actuator networks, and advances in data capture, processing, storage, and mining. Such applications also take advantage of state-of-the-art machine and deep learning algorithms, major strides in artificial and ambient intelligence, and rapid improvements in the stability and maturity of mobile, social, and edge computing models.
Discover the methods and techniques required for creating immersive design visualization for industry. This book proposes ways for industry-oriented design visualization from scratch. This includes fundamentals of creative and immersive technology; tools and techniques for architectural visualization; design visualization with Autodesk Maya; PBR integration; and texturing, material design, and integration into UE4 for immersive design visualization. You'll to dive into design and visualization, from planning to execution. You will start with the basics, such as an introduction to design visualization as well as to the software you will be using. You will next learn to create assets such as virtual worlds and texturing, and integrate them with Unreal Engine 4. Finally, there is a capstone project for you to make your own immersive visualization scene. By the end of the book you'll be able to create assets for use in industries such as game development, entertainment, architecture, design engineering, and digital education. What You Will Learn Gain the fundamentals of immersive design visualization Master design visualization with Autodesk Maya Study interactive visualization with UE4 Create your immersive design portfolio Who This Book Is For Beginning-intermediate learners from the fields of animation, visual art, and computer graphics as well as design visualization, game technology, and virtual reality integration.
Create assets for history-based games. This book covers the fundamental principles required to understand and create architectural visualizations of historical locations using digital tools. You will explore aspects of 3D design visualization and VR integration using industry-preferred software. Some of the most popular video games in recent years have historical settings (Age of Empires, Call of Duty, etc.). Creating these games requires creating historically accurate game assets. You will use Blender to create VR-ready assets by modeling and unwrapping them. And you will use Substance Painter to texture the assets that you create. You will also learn how to use the Quixel Megascans library to acquire and implement physically accurate materials in the scenes. Finally, you will import the assets into Unreal Engine 4 and recreate a VR integrated heritage that can be explored in real time. Using VR technology and game engines, you can digitally recreate historical settings for games. What You Will Learn Create high-quality, optimized models suitable for any 3D game engine Master the techniques of texturing assets using Substance Painter and Quixel Megascans Keep assets historically accurate Integrate assets with the game engine Create visualizations with Unreal Engine 4 Who Is This Book For Game developers with some experience who are eager to get into VR-based games
This book explores potentially disruptive and transformative healthcare-specific use cases made possible by the latest developments in Internet of Things (IoT) technology and Cyber-Physical Systems (CPS). Healthcare data can be subjected to a range of different investigations in order to extract highly useful and usable intelligence for the automation of traditionally manual tasks. In addition, next-generation healthcare applications can be enhanced by integrating the latest knowledge discovery and dissemination tools. These sophisticated, smart healthcare applications are possible thanks to a growing ecosystem of healthcare sensors and actuators, new ad hoc and application-specific sensor and actuator networks, and advances in data capture, processing, storage, and mining. Such applications also take advantage of state-of-the-art machine and deep learning algorithms, major strides in artificial and ambient intelligence, and rapid improvements in the stability and maturity of mobile, social, and edge computing models.
Urban Water Crisis and Management: Strategies for Sustainable Development, Sixth Edition presents solutions for the current challenges of urban water and management strategies. Through contributed chapters, a framework is laid out for a reduction of the use of groundwater (heavily overused as a solution) and the alternative options for the supply of water to cities, or for urban water. Sections discuss urban water, its problems and management approaches, address the root causes of the water crisis in urban areas, and cover the scientific and technical knowledge necessary to manage water resources. Significant gaps between developed and developing nations in the procedure of water management are also addressed, along with practical information regarding recycling and the reuse of wastewater which is useful as baseline data for the future.
Every year lives and properties are lost in road accidents. About one-fourth of these accidents are due to low vision in foggy weather. At present, there is no algorithm that is specifically designed for the removal of fog from videos. Application of a single-image fog removal algorithm over each video frame is a time-consuming and costly affair. It is demonstrated that with the intelligent use of temporal redundancy, fog removal algorithms designed for a single image can be extended to the real-time video application. Results confirm that the presented framework used for the extension of the fog removal algorithms for images to videos can reduce the complexity to a great extent with no loss of perceptual quality. This paves the way for the real-life application of the video fog removal algorithm. In order to remove fog, an efficient fog removal algorithm using anisotropic diffusion is developed. The presented fog removal algorithm uses new dark channel assumption and anisotropic diffusion for the initialization and refinement of the airlight map, respectively. Use of anisotropic diffusion helps to estimate the better airlight map estimation. The said fog removal algorithm requires a single image captured by uncalibrated camera system. The anisotropic diffusion-based fog removal algorithm can be applied in both RGB and HSI color space. This book shows that the use of HSI color space reduces the complexity further. The said fog removal algorithm requires pre- and post-processing steps for the better restoration of the foggy image. These pre- and post-processing steps have either data-driven or constant parameters that avoid the user intervention. Presented fog removal algorithm is independent of the intensity of the fog, thus even in the case of the heavy fog presented algorithm performs well. Qualitative and quantitative results confirm that the presented fog removal algorithm outperformed previous algorithms in terms of perceptual quality, color fidelity and execution time. The work presented in this book can find wide application in entertainment industries, transportation, tracking and consumer electronics.
Current vision systems are designed to perform in normal weather condition. However, no one can escape from severe weather conditions. Bad weather reduces scene contrast and visibility, which results in degradation in the performance of various computer vision algorithms such as object tracking, segmentation and recognition. Thus, current vision systems must include some mechanisms that enable them to perform up to the mark in bad weather conditions such as rain and fog. Rain causes the spatial and temporal intensity variations in images or video frames. These intensity changes are due to the random distribution and high velocities of the raindrops. Fog causes low contrast and whiteness in the image and leads to a shift in the color. This book has studied rain and fog from the perspective of vision. The book has two main goals: 1) removal of rain from videos captured by a moving and static camera, 2) removal of the fog from images and videos captured by a moving single uncalibrated camera system. The book begins with a literature survey. Pros and cons of the selected prior art algorithms are described, and a general framework for the development of an efficient rain removal algorithm is explored. Temporal and spatiotemporal properties of rain pixels are analyzed and using these properties, two rain removal algorithms for the videos captured by a static camera are developed. For the removal of rain, temporal and spatiotemporal algorithms require fewer numbers of consecutive frames which reduces buffer size and delay. These algorithms do not assume the shape, size and velocity of raindrops which make it robust to different rain conditions (i.e., heavy rain, light rain and moderate rain). In a practical situation, there is no ground truth available for rain video. Thus, no reference quality metric is very useful in measuring the efficacy of the rain removal algorithms. Temporal variance and spatiotemporal variance are presented in this book as no reference quality metrics. An efficient rain removal algorithm using meteorological properties of rain is developed. The relation among the orientation of the raindrops, wind velocity and terminal velocity is established. This relation is used in the estimation of shape-based features of the raindrop. Meteorological property-based features helped to discriminate the rain and non-rain pixels. Most of the prior art algorithms are designed for the videos captured by a static camera. The use of global motion compensation with all rain removal algorithms designed for videos captured by static camera results in better accuracy for videos captured by moving camera. Qualitative and quantitative results confirm that probabilistic temporal, spatiotemporal and meteorological algorithms outperformed other prior art algorithms in terms of the perceptual quality, buffer size, execution delay and system cost. The work presented in this book can find wide application in entertainment industries, transportation, tracking and consumer electronics. Table of Contents: Acknowledgments / Introduction / Analysis of Rain / Dataset and Performance Metrics / Important Rain Detection Algorithms / Probabilistic Approach for Detection and Removal of Rain / Impact of Camera Motion on Detection of Rain / Meteorological Approach for Detection and Removal of Rain from Videos / Conclusion and Scope of Future Work / Bibliography / Authors' Biographies
Visualization Techniques for Climate Change with Machine Learning and Artificial Intelligence covers computer-aided artificial intelligence and machine learning technologies as related to the impacts of climate change and its potential to prevent/remediate the effects. As such, different types of algorithms, mathematical relations and software models may help us to understand our current reality, predict future weather events and create new products and services to minimize human impact, chances of improving and saving lives and creating a healthier world. This book covers different types of tools for the prediction of climate change and alternative systems which can reduce the levels of threats observed by climate change scientists. Moreover, the book will help to achieve at least one of 17 sustainable development goals i.e., climate action. |
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