- Table View
- List View
Handbook of 3D Machine Vision: Optical Metrology and Imaging (Series in Optics and Optoelectronics)
by Song ZhangChoosing from the numerous 3D vision methods available can be frustrating for scientists and engineers, especially without a comprehensive resource to consult. Filling this gap, this handbook gives an in-depth look at the most popular 3D imaging techniques. Written by key players in the field and inventors of important imaging technologies, it helps you understand the core of 3D imaging technology and choose the proper 3D imaging technique for your needs. For each technique, the book provides its mathematical foundations, summarizes its successful applications, and discusses its limitations.
The Handbook of Ad Hoc Wireless Networks (Electrical Engineering Handbook)
by Mohammad IlyasA relative newcomer to the field of wireless communications, ad hoc networking is growing quickly, both in its importance and its applications. With rapid advances in hardware, software, and protocols, ad hoc networks are now coming of age, and the time has come to bring together into one reference their principles, technologies, and techniques.The Handbook of Ad Hoc Wireless Networks does exactly that. Experts from around the world have joined forces to create the definitive reference for the field. From the basic concepts, techniques, systems, and protocols of wireless communication to the particulars of ad hoc network routing methods, power, connections, traffic management, and security, this handbook covers virtually every aspect of ad hoc wireless networking. It includes a section that explores several routing methods and protocols directly related to implementing ad hoc networks in a variety of applications.The benefits of ad hoc wireless networks are many, but several challenges remain. Organized for easy reference, The Handbook of Ad Hoc Wireless Networks is your opportunity to gain quick familiarity with the state of the art, have at your disposal the only complete reference on the subject available, and prepare to meet the technological and implementation challenges you'll encounter in practice.
Handbook of AI and Data Sciences for Sleep Disorders (Springer Optimization and Its Applications #216)
by Richard B. Berry Panos M. Pardalos Xiaochen XianThe rise of lifestyle changes resulting from constant connectivity, irregular work schedules, heightened stress, and disruptive sleep patterns, have contributed to increasing insomnia rates. Exacerbated by the COVID-19 pandemic, sleep disorders are more prevalent than ever. This handbook offers a comprehensive exploration of the fusion of Artificial Intelligence (AI) and data science within the realm of sleep disorders, presenting innovative approaches to diagnosis, treatment, and personalized care. The interdisciplinary nature of this handbook fosters collaboration between experts from diverse fields, including computer science, engineering, neuroscience, medicine, public health, AI, data science, and sleep medicine. Each chapter delves into specific aspects of sleep disorder analysis, innovative methodologies, novel insights, and real-world applications that showcase the transformative potential of AI and data science in sleep medicine, from analyzing sleep patterns and predicting disorder risk factors to utilizing big data analytics for large-scale epidemiological studies. This handbook hopes to offer a comprehensive resource for researchers, clinicians, and policymakers striving to address the challenges in sleep medicine.
Handbook of AI-based Metaheuristics (Advances in Metaheuristics)
by Anand J. KulkarniAt the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms. This will be a valuable reference for researchers in industry and academia, as well as for all Master’s and PhD students working in the metaheuristics and applications domains.
Handbook of Algorithms for Physical Design Automation
by Sachin S. Sapatnekar Dinesh P. Mehta Charles J. AlpertThe physical design flow of any project depends upon the size of the design, the technology, the number of designers, the clock frequency, and the time to do the design. As technology advances and design-styles change, physical design flows are constantly reinvented as traditional phases are removed and new ones are added to accommodate changes in
Handbook of Algorithms for Wireless Networking and Mobile Computing (Chapman & Hall/CRC Computer and Information Science Series)
by Azzedine BoukercheThe Handbook of Algorithms for Wireless Networking and Mobile Computing focuses on several aspects of mobile computing, particularly algorithmic methods and distributed computing with mobile communications capability. It provides the topics that are crucial for building the foundation for the design and construction of future generations of mobile and wireless networks, including cellular, wireless ad hoc, sensor, and ubiquitous networks. Following an analysis of fundamental algorithms and protocols, the book offers a basic overview of wireless technologies and networks. Other topics include issues related to mobility, aspects of QoS provisioning in wireless networks, future applications, and much more.
Handbook of Applied Cryptography (Discrete Mathematics and Its Applications)
by Alfred J. Menezes Paul C. van Oorschot Scott A. VanstoneCryptography, in particular public-key cryptography, has emerged in the last 20 years as an important discipline that is not only the subject of an enormous amount of research, but provides the foundation for information security in many applications. Standards are emerging to meet the demands for cryptographic protection in most areas of data communications. Public-key cryptographic techniques are now in widespread use, especially in the financial services industry, in the public sector, and by individuals for their personal privacy, such as in electronic mail. This Handbook will serve as a valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography. It is a necessary and timely guide for professionals who practice the art of cryptography. The Handbook of Applied Cryptography provides a treatment that is multifunctional:It serves as an introduction to the more practical aspects of both conventional and public-key cryptography It is a valuable source of the latest techniques and algorithms for the serious practitioner It provides an integrated treatment of the field, while still presenting each major topic as a self-contained unit It provides a mathematical treatment to accompany practical discussions It contains enough abstraction to be a valuable reference for theoreticians while containing enough detail to actually allow implementation of the algorithms discussedNow in its third printing, this is the definitive cryptography reference that the novice as well as experienced developers, designers, researchers, engineers, computer scientists, and mathematicians alike will use.
The Handbook of Applied Expert Systems
by Jay LiebowitzThe Handbook of Applied Expert Systems is a landmark work dedicated solely to this rapidly advancing area of study. Edited by Jay Liebowitz, a professor, author, and consultant known around the world for his work in the field, this authoritative source covers the latest expert system technologies, applications, methodologies, and practices. The book features contributions from more than 40 of the world's foremost expert systems authorities in industry, government, and academia.The Handbook is organized into two major sections. The first section explains expert systems technologies while the second section focuses on applied examples in a wide variety of industries. Key topics covered include fuzzy systems, genetic algorithm development, machine learning, knowledge representation, and much more.
Handbook of Approximation Algorithms and Metaheuristics: Contemporary and Emerging Applications, Volume 2 (Chapman & Hall/CRC Computer and Information Science Series)
by Teofilo F. GonzalezHandbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more. About the Editor Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.
Handbook of Approximation Algorithms and Metaheuristics: Methologies and Traditional Applications, Volume 1 (Chapman & Hall/CRC Computer and Information Science Series)
by Teofilo F. GonzalezHandbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more. About the Editor Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.
Handbook of Artificial Intelligence and Wearables: Applications and Case Studies
by Hemachandran K, Manjeet Rege, Zita Zoltay Paprika, K. V. Rajesh Kumar, and Shahid Mohammad GanieThe ever-changing world of wearable technologies makes it difficult for experts and practitioners to keep up with the most recent developments. This handbook provides a solid understanding of the significant role that AI plays in the design and development of wearable technologies along with applications and case studies. Handbook of Artificial Intelligence and Wearables: Applications and Case Studies presents a deep understanding of AI and its involvement in wearable technologies. The book discusses the key role that AI plays and goes on to discuss the challenges and possible solutions. It highlights the more recent advances along with real-world approaches for the design and development of the most popular AI-enabled wearable devices such as smart fitness trackers, AI-enabled glasses, sports wearables, disease diagnostic devices, and more, complete with case studies. This book will be a valuable source for researchers, academics, technologists, industrialists, practitioners, and all people who wish to explore the applications of AI and the part it plays in wearable technologies.
Handbook of Artificial Intelligence for Music: Foundations, Advanced Approaches, and Developments for Creativity
by Eduardo Reck MirandaThis book presents comprehensive coverage of the latest advances in research into enabling machines to listen to and compose new music. It includes chapters introducing what we know about human musical intelligence and on how this knowledge can be simulated with AI. The development of interactive musical robots and emerging new approaches to AI-based musical creativity are also introduced, including brain–computer music interfaces, bio-processors and quantum computing.Artificial Intelligence (AI) technology permeates the music industry, from management systems for recording studios to recommendation systems for online commercialization of music through the Internet. Yet whereas AI for online music distribution is well advanced, this book focuses on a largely unexplored application: AI for creating the actual musical content.
Handbook of Artificial Intelligence in Healthcare: Vol 2: Practicalities and Prospects (Intelligent Systems Reference Library #212)
by Lakhmi C. Jain Yen-Wei Chen Chee-Peng Lim Ashlesha Vaidya Charu MahorkarArtificial Intelligence (AI) has transformed many aspects of our daily activities. Health and well-being of humans stand as one of the key domains where AI has achieved significant progresses, saving time, costs, and potentially lives, as well as fostering economic resilience, particularly under the COVID-19 pandemic environments. This book is a sequel of the Handbook of Artificial Intelligence in Healthcare. The first volume of the Handbook is dedicated to present advances and applications of AI methodologies in several specific areas, i.e., signal, image, and video processing as well as information and data analytics. In this second volume of the Handbook, general practicality challenges and future prospects of AI methodologies pertaining to healthcare and related domains are presented in Part 1 and Part 2, respectively. It is envisaged that the selected studies will provide readers a general perspective on the issues, challenges, and opportunities in designing, developing, and implementing AI-based tools and solutions in the healthcare sector, bringing benefits to transform and advance health and well-being development of humans..
Handbook of Augmented Reality
by Borko FurhtAugmented Reality (AR) refers to the merging of a live view of the physical, real world with context-sensitive, computer-generated images to create a mixed reality. Through this augmented vision, a user can digitally interact with and adjust information about their surrounding environment on-the-fly. Handbook of Augmented Reality provides an extensive overview of the current and future trends in Augmented Reality, and chronicles the dramatic growth in this field. The book includes contributions from world expert s in the field of AR from academia, research laboratories and private industry. Case studies and examples throughout the handbook help introduce the basic concepts of AR, as well as outline the Computer Vision and Multimedia techniques most commonly used today. The book is intended for a wide variety of readers including academicians, designers, developers, educators, engineers, practitioners, researchers, and graduate students. This book can also be beneficial for business managers, entrepreneurs, and investors.
Handbook of Automated Essay Evaluation: Current Applications and New Directions
by Mark D. Shermis Jill BursteinThis comprehensive, interdisciplinary handbook reviews the latest methods and technologies used in automated essay evaluation (AEE) methods and technologies. Highlights include the latest in the evaluation of performance-based writing assessments and recent advances in the teaching of writing, language testing, cognitive psychology, and computational linguistics. This greatly expanded follow-up to Automated Essay Scoring reflects the numerous advances that have taken place in the field since 2003 including automated essay scoring and diagnostic feedback. Each chapter features a common structure including an introduction and a conclusion. Ideas for diagnostic and evaluative feedback are sprinkled throughout the book. Highlights of the book’s coverage include: The latest research on automated essay evaluation. Descriptions of the major scoring engines including the E-rater®, the Intelligent Essay Assessor, the Intellimetric™ Engine, c-rater™, and LightSIDE. Applications of the uses of the technology including a large scale system used in West Virginia. A systematic framework for evaluating research and technological results. Descriptions of AEE methods that can be replicated for languages other than English as seen in the example from China. Chapters from key researchers in the field. The book opens with an introduction to AEEs and a review of the "best practices" of teaching writing along with tips on the use of automated analysis in the classroom. Next the book highlights the capabilities and applications of several scoring engines including the E-rater®, the Intelligent Essay Assessor, the Intellimetric™ engine, c-rater™, and LightSIDE. Here readers will find an actual application of the use of an AEE in West Virginia, psychometric issues related to AEEs such as validity, reliability, and scaling, and the use of automated scoring to detect reader drift, grammatical errors, discourse coherence quality, and the impact of human rating on AEEs. A review of the cognitive foundations underlying methods used in AEE is also provided. The book concludes with a comparison of the various AEE systems and speculation about the future of the field in light of current educational policy. Ideal for educators, professionals, curriculum specialists, and administrators responsible for developing writing programs or distance learning curricula, those who teach using AEE technologies, policy makers, and researchers in education, writing, psychometrics, cognitive psychology, and computational linguistics, this book also serves as a reference for graduate courses on automated essay evaluation taught in education, computer science, language, linguistics, and cognitive psychology.
Handbook of Automated Scoring: Theory into Practice (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
by Duanli Yan André A. Rupp Peter W. Foltz"Automated scoring engines […] require a careful balancing of the contributions of technology, NLP, psychometrics, artificial intelligence, and the learning sciences. The present handbook is evidence that the theories, methodologies, and underlying technology that surround automated scoring have reached maturity, and that there is a growing acceptance of these technologies among experts and the public." From the Foreword by Alina von Davier, ACTNext Senior Vice President Handbook of Automated Scoring: Theory into Practice provides a scientifically grounded overview of the key research efforts required to move automated scoring systems into operational practice. It examines the field of automated scoring from the viewpoint of related scientific fields serving as its foundation, the latest developments of computational methodologies utilized in automated scoring, and several large-scale real-world applications of automated scoring for complex learning and assessment systems. The book is organized into three parts that cover (1) theoretical foundations, (2) operational methodologies, and (3) practical illustrations, each with a commentary. In addition, the handbook includes an introduction and synthesis chapter as well as a cross-chapter glossary.
Handbook of Automotive Human Factors
by Motoyuki AkamatsuThanks to advances in computer technology in the last twenty years, navigation system, cabin environment control, ACC, advanced driver assistance system (ADAS) and automated driving have become a part of the automobile experience. Improvement in technology enables us to design these with greater flexibility and provide greater value to the driver (human centered design). To achieve this, research is required by laboratories, automobile and auto parts manufacturers. Although there has been a lot of effort in human factors research and development, starting from basic research to product development, the knowledge and experience has not been integrated optimally. <p><P>The aim of this book is to collect and review the information for researchers, designers and developers to learn and apply them for further research and development of human centered design of future automotive technologies. Automotive human factors include psychological, physiological, mathematical, engineering and even sociological aspects. This book offers valuable insights to applying the right approach in the right place.
Handbook of Aviation Human Factors
by John A. Wise V. David Hopkin Daniel J. GarlandA complete examination of issues and concepts relating to human factors in simulation, this book covers theory and application in space, ships, submarines, naval aviation, and commercial aviation. The authors examine issues of simulation and their effect on the validity and functionality of simulators as a training device. The chapters contain in d
Handbook of Big Data (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
by Peter Bühlmann Petros Drineas Michael Kane Mark van der LaanHandbook of Big Data provides a state-of-the-art overview of the analysis of large-scale datasets. Featuring contributions from well-known experts in statistics and computer science, this handbook presents a carefully curated collection of techniques from both industry and academia. Thus, the text instills a working understanding of key statistical
Handbook of Big Data Analytics (Springer Handbooks Of Computational Statistics Ser.)
by Xiaotong Shen Henry Horng-Shing Lu Wolfgang Karl HärdleAddressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Handbook of Big Data Analytics and Forensics
by Kim-Kwang Raymond Choo Ali DehghantanhaThis handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics. The second chapter comprehensively reviews IoT security, privacy, and forensics literature, focusing on IoT and unmanned aerial vehicles (UAVs). The authors propose a deep learning-based approach to process cloud’s log data and mitigate enumeration attacks in the third chapter. The fourth chapter proposes a robust fuzzy learning model to protect IT-based infrastructure against advanced persistent threat (APT) campaigns. Advanced and fair clustering approach for industrial data, which is capable of training with huge volume of data in a close to linear time is introduced in the fifth chapter, as well as offering an adaptive deep learning model to detect cyberattacks targeting cyber physical systems (CPS) covered in the sixth chapter. The authors evaluate the performance of unsupervised machine learning for detecting cyberattacks against industrial control systems (ICS) in chapter 7, and the next chapter presents a robust fuzzy Bayesian approach for ICS’s cyber threat hunting. This handbook also evaluates the performance of supervised machine learning methods in identifying cyberattacks against CPS. The performance of a scalable clustering algorithm for CPS’s cyber threat hunting and the usefulness of machine learning algorithms for MacOS malware detection are respectively evaluated.This handbook continues with evaluating the performance of various machine learning techniques to detect the Internet of Things malware. The authors demonstrate how MacOSX cyberattacks can be detected using state-of-the-art machine learning models. In order to identify credit card frauds, the fifteenth chapter introduces a hybrid model. In the sixteenth chapter, the editors propose a model that leverages natural language processing techniques for generating a mapping between APT-related reports and cyber kill chain. A deep learning-based approach to detect ransomware is introduced, as well as a proposed clustering approach to detect IoT malware in the last two chapters.This handbook primarily targets professionals and scientists working in Big Data, Digital Forensics, Machine Learning, Cyber Security Cyber Threat Analytics and Cyber Threat Hunting as a reference book. Advanced level-students and researchers studying and working in Computer systems, Computer networks and Artificial intelligence will also find this reference useful.
Handbook of Big Data Privacy
by Kim-Kwang Raymond Choo Ali DehghantanhaThis handbook provides comprehensive knowledge and includes an overview of the current state-of-the-art of Big Data Privacy, with chapters written by international world leaders from academia and industry working in this field. The first part of this book offers a review of security challenges in critical infrastructure and offers methods that utilize acritical intelligence (AI) techniques to overcome those issues. It then focuses on big data security and privacy issues in relation to developments in the Industry 4.0. Internet of Things (IoT) devices are becoming a major source of security and privacy concern in big data platforms. Multiple solutions that leverage machine learning for addressing security and privacy issues in IoT environments are also discussed this handbook. The second part of this handbook is focused on privacy and security issues in different layers of big data systems. It discusses about methods for evaluating security and privacy of big data systems on network, application and physical layers. This handbook elaborates on existing methods to use data analytic and AI techniques at different layers of big data platforms to identify privacy and security attacks. The final part of this handbook is focused on analyzing cyber threats applicable to the big data environments. It offers an in-depth review of attacks applicable to big data platforms in smart grids, smart farming, FinTech, and health sectors. Multiple solutions are presented to detect, prevent and analyze cyber-attacks and assess the impact of malicious payloads to those environments. This handbook provides information for security and privacy experts in most areas of big data including; FinTech, Industry 4.0, Internet of Things, Smart Grids, Smart Farming and more. Experts working in big data, privacy, security, forensics, malware analysis, machine learning and data analysts will find this handbook useful as a reference. Researchers and advanced-level computer science students focused on computer systems, Internet of Things, Smart Grid, Smart Farming, Industry 4.0 and network analysts will also find this handbook useful as a reference.
Handbook of Big Data Technologies
by Albert Y. Zomaya Sherif SakrThis handbook offers comprehensive coverage of recent advancements in Big Data technologies and related paradigms. Chapters are authored by international leading experts in the field, and have been reviewed and revised for maximum reader value. The volume consists of twenty-five chapters organized into four main parts. Part one covers the fundamental concepts of Big Data technologies including data curation mechanisms, data models, storage models, programming models and programming platforms. It also dives into the details of implementing Big SQL query engines and big stream processing systems. Part Two focuses on the semantic aspects of Big Data management including data integration and exploratory ad hoc analysis in addition to structured querying and pattern matching techniques. Part Three presents a comprehensive overview of large scale graph processing. It covers the most recent research in large scale graph processing platforms, introducing several scalable graph querying and mining mechanisms in domains such as social networks. Part Four details novel applications that have been made possible by the rapid emergence of Big Data technologies such as Internet-of-Things (IOT), Cognitive Computing and SCADA Systems. All parts of the book discuss open research problems, including potential opportunities, that have arisen from the rapid progress of Big Data technologies and the associated increasing requirements of application domains. Designed for researchers, IT professionals and graduate students, this book is a timely contribution to the growing Big Data field. Big Data has been recognized as one of leading emerging technologies that will have a major contribution and impact on the various fields of science and varies aspect of the human society over the coming decades. Therefore, the content in this book will be an essential tool to help readers understand the development and future of the field.
Handbook of Big Geospatial Data
by Martin Werner Yao-Yi ChiangThis handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms. This handbook provides an overview of how spatial computing technologies for big data can be organized and implemented to solve real-world problems. Diverse subdomains ranging from indoor mapping and navigation over trajectory computing to earth observation from space, are also present in this handbook. It combines fundamental contributions focusing on spatio-textual analysis, uncertain databases, and spatial statistics with application examples such as road network detection or colocation detection using GPUs. In summary, this handbook gives an essential introduction and overview of the rich field of spatial information science and big geospatial data. It introduces three different perspectives, which together define the field of big geospatial data: a societal, governmental, and governance perspective. It discusses questions of how the acquisition, distribution and exploitation of big geospatial data must be organized both on the scale of companies and countries. A second perspective is a theory-oriented set of contributions on arbitrary spatial data with contributions introducing into the exciting field of spatial statistics or into uncertain databases. A third perspective is taking a very practical perspective to big geospatial data, ranging from chapters that describe how big geospatial data infrastructures can be implemented and how specific applications can be implemented on top of big geospatial data. This would include for example, research in historic map data, road network extraction, damage estimation from remote sensing imagery, or the analysis of spatio-textual collections and social media. This multi-disciplinary approach makes the book unique.This handbook can be used as a reference for undergraduate students, graduate students and researchers focused on big geospatial data. Professionals can use this book, as well as practitioners facing big collections of geospatial data.
Handbook of Biochips: Integrated Circuits and Systems for Biology and Medicine
by Mohamad SawanThis book provides a broad survey of the field of biochips, including fundamentals of microelectronics and biomaterials interaction with various, living tissues, as well as numerous, diverse applications. Although a wide variety of biochips will be described, there will be a focus on those at the brain-machine interface. Analysis is included of the relationship between different categories of biochips and their interactions with the body and coverage includes wireless remote control of biochips and arrays of microelectrodes, based on new biomaterials.