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Physics Aware Deep Learning For Radar Based Cyber Physical Human Systems
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Book Synopsis Women in Telecommunications by : Maria Sabrina Greco
Download or read book Women in Telecommunications written by Maria Sabrina Greco and published by Springer Nature. This book was released on 2023-11-06 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a breadth of innovative and impactful research in the field of telecommunications led by women investigators. Topics covered include satellite communications, cognitive radars, remote sensing sensor networks, quantum Internet, and cyberspace. These topics touch on many of the challenges facing the world today and these solutions by women researchers are valuable for their technical excellence and their non-traditional perspective. As an important part of the Women in Engineering and Science book series, the work highlights the contribution of women leaders in telecommunications, inspiring women and men, girls and boys to enter and apply themselves to secure our future in.
Book Synopsis Machine Learning and Knowledge Discovery in Databases by : Massih-Reza Amini
Download or read book Machine Learning and Knowledge Discovery in Databases written by Massih-Reza Amini and published by Springer Nature. This book was released on 2023-03-16 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge graphs; social network analysis; graph neural networks; natural language processing and text mining; conversational systems; Part III: Deep learning; robust and adversarial machine learning; generative models; computer vision; meta-learning, neural architecture search; Part IV: Reinforcement learning; multi-agent reinforcement learning; bandits and online learning; active and semi-supervised learning; private and federated learning; . Part V: Supervised learning; probabilistic inference; optimal transport; optimization; quantum, hardware; sustainability; Part VI: Time series; financial machine learning; applications; applications: transportation; demo track.
Book Synopsis Millimeter Wave Radar by : Stephen L. Johnston
Download or read book Millimeter Wave Radar written by Stephen L. Johnston and published by . This book was released on 1980 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence Methods in the Environmental Sciences by : Sue Ellen Haupt
Download or read book Artificial Intelligence Methods in the Environmental Sciences written by Sue Ellen Haupt and published by Springer Science & Business Media. This book was released on 2008-11-28 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.
Book Synopsis Introduction to Embedded Systems, Second Edition by : Edward Ashford Lee
Download or read book Introduction to Embedded Systems, Second Edition written by Edward Ashford Lee and published by MIT Press. This book was released on 2017-01-06 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the engineering principles of embedded systems, with a focus on modeling, design, and analysis of cyber-physical systems. The most visible use of computers and software is processing information for human consumption. The vast majority of computers in use, however, are much less visible. They run the engine, brakes, seatbelts, airbag, and audio system in your car. They digitally encode your voice and construct a radio signal to send it from your cell phone to a base station. They command robots on a factory floor, power generation in a power plant, processes in a chemical plant, and traffic lights in a city. These less visible computers are called embedded systems, and the software they run is called embedded software. The principal challenges in designing and analyzing embedded systems stem from their interaction with physical processes. This book takes a cyber-physical approach to embedded systems, introducing the engineering concepts underlying embedded systems as a technology and as a subject of study. The focus is on modeling, design, and analysis of cyber-physical systems, which integrate computation, networking, and physical processes. The second edition offers two new chapters, several new exercises, and other improvements. The book can be used as a textbook at the advanced undergraduate or introductory graduate level and as a professional reference for practicing engineers and computer scientists. Readers should have some familiarity with machine structures, computer programming, basic discrete mathematics and algorithms, and signals and systems.
Book Synopsis Autonomous Horizons by : Greg Zacharias
Download or read book Autonomous Horizons written by Greg Zacharias and published by Independently Published. This book was released on 2019-04-05 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr. Greg Zacharias, former Chief Scientist of the United States Air Force (2015-18), explores next steps in autonomous systems (AS) development, fielding, and training. Rapid advances in AS development and artificial intelligence (AI) research will change how we think about machines, whether they are individual vehicle platforms or networked enterprises. The payoff will be considerable, affording the US military significant protection for aviators, greater effectiveness in employment, and unlimited opportunities for novel and disruptive concepts of operations. Autonomous Horizons: The Way Forward identifies issues and makes recommendations for the Air Force to take full advantage of this transformational technology.
Book Synopsis Explainable AI: Interpreting, Explaining and Visualizing Deep Learning by : Wojciech Samek
Download or read book Explainable AI: Interpreting, Explaining and Visualizing Deep Learning written by Wojciech Samek and published by Springer Nature. This book was released on 2019-09-10 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
Book Synopsis Deep Learning for Human Activity Recognition by : Xiaoli Li
Download or read book Deep Learning for Human Activity Recognition written by Xiaoli Li and published by Springer Nature. This book was released on 2021-02-17 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the Second International Workshop on Deep Learning for Human Activity Recognition, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, in Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic the workshop was postponed to the year 2021 and held in a virtual format. The 10 presented papers were thorougly reviewed and included in the volume. They present recent research on applications of human activity recognition for various areas such as healthcare services, smart home applications, and more.
Book Synopsis Gaussian Processes for Machine Learning by : Carl Edward Rasmussen
Download or read book Gaussian Processes for Machine Learning written by Carl Edward Rasmussen and published by MIT Press. This book was released on 2005-11-23 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Book Synopsis Context-Enhanced Information Fusion by : Lauro Snidaro
Download or read book Context-Enhanced Information Fusion written by Lauro Snidaro and published by Springer. This book was released on 2016-05-25 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text reviews the fundamental theory and latest methods for including contextual information in fusion process design and implementation. Chapters are contributed by the foremost international experts, spanning numerous developments and applications. The book highlights high- and low-level information fusion problems, performance evaluation under highly demanding conditions, and design principles. A particular focus is placed on approaches that integrate research from different communities, emphasizing the benefit of combining different techniques to overcome the limitations of a single perspective. Features: introduces the terminology and core elements in information fusion and context; presents key themes for context-enhanced information fusion; discusses design issues in developing context-aware fusion systems; provides mathematical grounds for modeling the contextual influences in representative fusion problems; describes the fusion of hard and soft data; reviews a diverse range of applications.
Book Synopsis Dynamic Data Driven Applications Systems by : Frederica Darema
Download or read book Dynamic Data Driven Applications Systems written by Frederica Darema and published by Springer Nature. This book was released on 2020-11-02 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Dynamic Data Driven Application Systems, DDDAS 2020, held in Boston, MA, USA, in October 2020. The 21 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 40 submissions. They cover topics such as: digital twins; environment cognizant adaptive-planning systems; energy systems; materials systems; physics-based systems analysis; imaging methods and systems; and learning systems.
Book Synopsis Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021) by : Rajiv Misra
Download or read book Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021) written by Rajiv Misra and published by Springer Nature. This book was released on 2021-09-29 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.
Book Synopsis Optical and Laser Remote Sensing by : D.K. Killinger
Download or read book Optical and Laser Remote Sensing written by D.K. Killinger and published by Springer. This book was released on 2013-06-29 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of optical and laser remote sensing has grown rapidly in recent years. This dynamic growth has been stimulated not only by technological advances in lasers, detectors, and optical system design, but also by the potential application of remote sensing systems to a wide variety of atmo spheric measurements. Optical and laser remote sensing can allow single ended measurement capability not offered by conventional point-detection techniques. While many past measurements have been associated with labo ratory research. practical systems have recently been developed which are capable of remotely detecting. measuring. and tracking a wide range of molecular and atomic species in the atmosphere with concentrations of parts per billion and at ranges over 100 km. This book is a compilation of papers which represent an overview of the present state of development of optical and laser remote sensing tech nology. The subjects covered include both passive and active remote sen sing techniques in the UV, visible, and IR spectral regions. related laser and detector technology, and atmospheric propagation and system analysis considerations. While the papers do not constitute an exhaustive treat ment of the excellent research being conducted in this field, they are representative of the wide diversity of present efforts. It is hoped that the reader will gain a general understanding of the current research in optical and laser remote sensing as well as an overview of current systems development.
Book Synopsis Flood Forecasting Using Machine Learning Methods by : Fi-John Chang
Download or read book Flood Forecasting Using Machine Learning Methods written by Fi-John Chang and published by MDPI. This book was released on 2019-02-28 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays, the degree and scale of flood hazards has been massively increasing as a result of the changing climate, and large-scale floods jeopardize lives and properties, causing great economic losses, in the inundation-prone areas of the world. Early flood warning systems are promising countermeasures against flood hazards and losses. A collaborative assessment according to multiple disciplines, comprising hydrology, remote sensing, and meteorology, of the magnitude and impacts of flood hazards on inundation areas significantly contributes to model the integrity and precision of flood forecasting. Methodologically oriented countermeasures against flood hazards may involve the forecasting of reservoir inflows, river flows, tropical cyclone tracks, and flooding at different lead times and/or scales. Analyses of impacts, risks, uncertainty, resilience, and scenarios coupled with policy-oriented suggestions will give information for flood hazard mitigation. Emerging advances in computing technologies coupled with big-data mining have boosted data-driven applications, among which Machine Learning technology, with its flexibility and scalability in pattern extraction, has modernized not only scientific thinking but also predictive applications. This book explores recent Machine Learning advances on flood forecast and management in a timely manner and presents interdisciplinary approaches to modelling the complexity of flood hazards-related issues, with contributions to integrative solutions from a local, regional or global perspective.
Book Synopsis What Video Games Have to Teach Us About Learning and Literacy. Second Edition by : James Paul Gee
Download or read book What Video Games Have to Teach Us About Learning and Literacy. Second Edition written by James Paul Gee and published by Macmillan. This book was released on 2014-12-02 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive Development in a Digital Age James Paul Gee begins his classic book with "I want to talk about video games–yes, even violent video games–and say some positive things about them." With this simple but explosive statement, one of America's most well-respected educators looks seriously at the good that can come from playing video games. This revised edition expands beyond mere gaming, introducing readers to fresh perspectives based on games like World of Warcraft and Half-Life 2. It delves deeper into cognitive development, discussing how video games can shape our understanding of the world. An undisputed must-read for those interested in the intersection of education, technology, and pop culture, What Video Games Have to Teach Us About Learning and Literacy challenges traditional norms, examines the educational potential of video games, and opens up a discussion on the far-reaching impacts of this ubiquitous aspect of modern life.
Book Synopsis Forest Fire Risk Prediction by : Rachael Nolan
Download or read book Forest Fire Risk Prediction written by Rachael Nolan and published by Mdpi AG. This book was released on 2021-09-30 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Globally, fire regimes are being altered by changing climatic conditions and land use changes. This has the potential to drive species extinctions and cause ecosystem state changes, with a range of consequences for ecosystem services. Accurate prediction of the risk of forest fires over short timescales (weeks or months) is required for land managers to target suppression resources in order to protect people, property, and infrastructure, as well as fire-sensitive ecosystems. Over longer timescales, prediction of changes in forest fire regimes is required to model the effect of wildfires on the terrestrial carbon cycle and subsequent feedbacks into the climate system. This was the motivation to publish this book, which is focused on quantifying and modelling the risk factors of forest fires. More specifically, the chapters in this book address four topics: (i) the use of fire danger metrics and other approaches to understand variation in wildfire activity; (ii) understanding changes in the flammability of live fuel; (iii) modeling dead fuel moisture content; and (iv) estimations of emission factors. The book will be of broad relevance to scientists and managers working with fire in different forest ecosystems globally.
