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Machine Learning For Cyber Physical System
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Book Synopsis Machine Learning for Cyber Physical Systems by : Jürgen Beyerer
Download or read book Machine Learning for Cyber Physical Systems written by Jürgen Beyerer and published by Springer. This book was released on 2018-12-17 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
Book Synopsis Reinforcement Learning for Cyber-Physical Systems by : Chong Li
Download or read book Reinforcement Learning for Cyber-Physical Systems written by Chong Li and published by CRC Press. This book was released on 2019-02-22 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reinforcement Learning for Cyber-Physical Systems: with Cybersecurity Case Studies was inspired by recent developments in the fields of reinforcement learning (RL) and cyber-physical systems (CPSs). Rooted in behavioral psychology, RL is one of the primary strands of machine learning. Different from other machine learning algorithms, such as supervised learning and unsupervised learning, the key feature of RL is its unique learning paradigm, i.e., trial-and-error. Combined with the deep neural networks, deep RL become so powerful that many complicated systems can be automatically managed by AI agents at a superhuman level. On the other hand, CPSs are envisioned to revolutionize our society in the near future. Such examples include the emerging smart buildings, intelligent transportation, and electric grids. However, the conventional hand-programming controller in CPSs could neither handle the increasing complexity of the system, nor automatically adapt itself to new situations that it has never encountered before. The problem of how to apply the existing deep RL algorithms, or develop new RL algorithms to enable the real-time adaptive CPSs, remains open. This book aims to establish a linkage between the two domains by systematically introducing RL foundations and algorithms, each supported by one or a few state-of-the-art CPS examples to help readers understand the intuition and usefulness of RL techniques. Features Introduces reinforcement learning, including advanced topics in RL Applies reinforcement learning to cyber-physical systems and cybersecurity Contains state-of-the-art examples and exercises in each chapter Provides two cybersecurity case studies Reinforcement Learning for Cyber-Physical Systems with Cybersecurity Case Studies is an ideal text for graduate students or junior/senior undergraduates in the fields of science, engineering, computer science, or applied mathematics. It would also prove useful to researchers and engineers interested in cybersecurity, RL, and CPS. The only background knowledge required to appreciate the book is a basic knowledge of calculus and probability theory.
Book Synopsis Artificial Intelligence Paradigms for Smart Cyber-Physical Systems by : Luhach, Ashish Kumar
Download or read book Artificial Intelligence Paradigms for Smart Cyber-Physical Systems written by Luhach, Ashish Kumar and published by IGI Global. This book was released on 2020-11-13 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyber-physical systems (CPS) have emerged as a unifying name for systems where cyber parts (i.e., the computing and communication parts) and physical parts are tightly integrated, both in design and during operation. Such systems use computations and communication deeply embedded in and interacting with human physical processes as well as augmenting existing and adding new capabilities. As such, CPS is an integration of computation, networking, and physical processes. Embedded computers and networks monitor and control the physical processes, with feedback loops where physical processes affect computations and vice versa. The economic and societal potential of such systems is vastly greater than what has been realized, and major investments are being made worldwide to develop the technology. Artificial Intelligence Paradigms for Smart Cyber-Physical Systems focuses on the recent advances in Artificial intelligence-based approaches towards affecting secure cyber-physical systems. This book presents investigations on state-of-the-art research issues, applications, and achievements in the field of computational intelligence paradigms for CPS. Covering topics that include autonomous systems, access control, machine learning, and intrusion detection and prevention systems, this book is ideally designed for engineers, industry professionals, practitioners, scientists, managers, students, academicians, and researchers seeking current research on artificial intelligence and cyber-physical systems.
Book Synopsis Deep Learning Applications for Cyber-Physical Systems by : Mundada, Monica R.
Download or read book Deep Learning Applications for Cyber-Physical Systems written by Mundada, Monica R. and published by IGI Global. This book was released on 2021-12-17 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.
Book Synopsis Big Data Analytics for Cyber-Physical Systems by : Guido Dartmann
Download or read book Big Data Analytics for Cyber-Physical Systems written by Guido Dartmann and published by Elsevier. This book was released on 2019-07-15 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics in Cyber-Physical Systems: Machine Learning for the Internet of Things examines sensor signal processing, IoT gateways, optimization and decision-making, intelligent mobility, and implementation of machine learning algorithms in embedded systems. This book focuses on the interaction between IoT technology and the mathematical tools used to evaluate the extracted data of those systems. Each chapter provides the reader with a broad list of data analytics and machine learning methods for multiple IoT applications. Additionally, this volume addresses the educational transfer needed to incorporate these technologies into our society by examining new platforms for IoT in schools, new courses and concepts for universities and adult education on IoT and data science. . Bridges the gap between IoT, CPS, and mathematical modelling. Features numerous use cases that discuss how concepts are applied in different domains and applications. Provides "best practices", "winning stories" and "real-world examples" to complement innovation. Includes highlights of mathematical foundations of signal processing and machine learning in CPS and IoT.
Book Synopsis Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis by : Sujit Rokka Chhetri
Download or read book Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis written by Sujit Rokka Chhetri and published by Springer Nature. This book was released on 2020-02-08 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS.
Book Synopsis Machine Learning for Cyber Physical System by : Janmenjoy Nayak
Download or read book Machine Learning for Cyber Physical System written by Janmenjoy Nayak and published by Springer Nature. This book was released on 2024 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive platform for learning the state-of-the-art machine learning algorithms for solving several cybersecurity issues. It is helpful in guiding for the implementation of smart machine learning solutions to detect various cybersecurity problems and make the users to understand in combating malware, detect spam, and fight financial fraud to mitigate cybercrimes. With an effective analysis of cyber-physical data, it consists of the solution for many real-life problems such as anomaly detection, IoT-based framework for security and control, manufacturing control system, fault detection, smart cities, risk assessment of cyber-physical systems, medical diagnosis, smart grid systems, biometric-based physical and cybersecurity systems using advance machine learning approach. Filling an important gap between machine learning and cybersecurity communities, it discusses topics covering a wide range of modern and practical advance machine learning techniques, frameworks, and development tools to enable readers to engage with the cutting-edge research across various aspects of cybersecurity.
Book Synopsis Machine Learning for Cyber Physical Systems by : Jürgen Beyerer
Download or read book Machine Learning for Cyber Physical Systems written by Jürgen Beyerer and published by Springer Nature. This book was released on 2020-12-23 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
Book Synopsis Real-Time Applications of Machine Learning in Cyber-Physical Systems by : Easwaran, Balamurugan
Download or read book Real-Time Applications of Machine Learning in Cyber-Physical Systems written by Easwaran, Balamurugan and published by IGI Global. This book was released on 2022-03-11 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.
Book Synopsis Cognitive Engineering for Next Generation Computing by : Kolla Bhanu Prakash
Download or read book Cognitive Engineering for Next Generation Computing written by Kolla Bhanu Prakash and published by John Wiley & Sons. This book was released on 2021-03-19 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: The cognitive approach to the IoT provides connectivity to everyone and everything since IoT connected devices are known to increase rapidly. When the IoT is integrated with cognitive technology, performance is improved, and smart intelligence is obtained. Discussed in this book are different types of datasets with structured content based on cognitive systems. The IoT gathers the information from the real time datasets through the internet, where the IoT network connects with multiple devices. This book mainly concentrates on providing the best solutions to existing real-time issues in the cognitive domain. Healthcare-based, cloud-based and smart transportation-based applications in the cognitive domain are addressed. The data integrity and security aspects of the cognitive computing main are also thoroughly discussed along with validated results.
Book Synopsis Cyber-Physical Systems by : Houbing Herbert Song
Download or read book Cyber-Physical Systems written by Houbing Herbert Song and published by Morgan Kaufmann. This book was released on 2016-08-27 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyber-Physical Systems: Foundations, Principles and Applications explores the core system science perspective needed to design and build complex cyber-physical systems. Using Systems Science’s underlying theories, such as probability theory, decision theory, game theory, organizational sociology, behavioral economics, and cognitive psychology, the book addresses foundational issues central across CPS applications, including System Design -- How to design CPS to be safe, secure, and resilient in rapidly evolving environments, System Verification -- How to develop effective metrics and methods to verify and certify large and complex CPS, Real-time Control and Adaptation -- How to achieve real-time dynamic control and behavior adaptation in a diverse environments, such as clouds and in network-challenged spaces, Manufacturing -- How to harness communication, computation, and control for developing new products, reducing product concepts to realizable designs, and producing integrated software-hardware systems at a pace far exceeding today's timeline. The book is part of the Intelligent Data-Centric Systems: Sensor-Collected Intelligence series edited by Fatos Xhafa, Technical University of Catalonia. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS Includes in-depth coverage of the latest models and theories that unify perspectives, expressing the interacting dynamics of the computational and physical components of a system in a dynamic environment Focuses on new design, analysis, and verification tools that embody the scientific principles of CPS and incorporate measurement, dynamics, and control Covers applications in numerous sectors, including agriculture, energy, transportation, building design and automation, healthcare, and manufacturing
Book Synopsis Machine Learning for Cyber Physical Systems by : Oliver Niggemann
Download or read book Machine Learning for Cyber Physical Systems written by Oliver Niggemann and published by . This book was released on 2020-10-08 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Open Access proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Book Synopsis Cyber-Physical, IoT, and Autonomous Systems in Industry 4.0 by : Vikram Bali
Download or read book Cyber-Physical, IoT, and Autonomous Systems in Industry 4.0 written by Vikram Bali and published by CRC Press. This book was released on 2021-12-23 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses topics related to the Internet of Things (IoT), machine learning, cyber-physical systems, cloud computing, and autonomous vehicles in Industry 4.0. It investigates challenges across multiple sectors and industries and considers Industry 4.0 for operations research and supply chain management. Cyber-Physical, IoT, and Autonomous Systems in Industry 4.0 encourages readers to develop novel theories and enrich their knowledge to foster sustainability. It examines the recent research trends and the future of cyber-physical systems, IoT, and autonomous systems as they relate to Industry 4.0. This book is intended for undergraduates, postgraduates, academics, researchers, and industry individuals to explore new ideas, techniques, and tools related to Industry 4.0.
Book Synopsis Machine Learning for Cyber Physical Systems by : Jürgen Beyerer
Download or read book Machine Learning for Cyber Physical Systems written by Jürgen Beyerer and published by Springer. This book was released on 2019-04-09 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Lemgo, October 25th-26th, 2017. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
Book Synopsis Explainable AI Within the Digital Transformation and Cyber Physical Systems by : Moamar Sayed-Mouchaweh
Download or read book Explainable AI Within the Digital Transformation and Cyber Physical Systems written by Moamar Sayed-Mouchaweh and published by Springer Nature. This book was released on 2021-10-30 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
Book Synopsis Machine Learning for Cyber-Physical Systems by : Oliver Niggemann
Download or read book Machine Learning for Cyber-Physical Systems written by Oliver Niggemann and published by Springer Nature. This book was released on 2024 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Zusammenfassung: This open access proceedings presents new approaches to Machine Learning for Cyber-Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS - Machine Learning for Cyber- Physical Systems, which was held in Hamburg (Germany), March 29th to 31st, 2023. Cyber-Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments. The Editors Prof. Dr. Oliver Niggemann held the professorship at the Institute for Industrial Information Technologies (inIT) in Lemgo (Germany) from 2008 to 2019 and was also deputy head of the Fraunhofer IOSB-INA until 2019. In 2019, he took over the university professorship "Computer Science in Mechanical Engineering" at the Helmut Schmidt University in Hamburg. His research at the Institute for Automation Technology is in the field of artificial intelligence and machine learning for cyber-physical systems. Prof. Dr.-Ing. Jürgen Beyerer is a full professor for informatics at the Institute for Anthropomatics and Robotics at the Karlsruhe Institute of Technology KIT and director of the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. Research interests include automated visual inspection, signal and image processing, active vision, metrology, information theory, fusion of data and information from heterogeneous sources, system theory, autonomous systems and automation. Dr. Maria Krantz is a Postdoc at the Helmut Schmidt University in Hamburg. Her main research interests are causality in Cyber-Physical Systems and applications of diagnosis algorithms in production systems. Dr. Christian Kühnert is senior scientist at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. His research interests are in the field of machine-learning, data-fusion and data analytics for cyber-physical systems
Book Synopsis Cyber-Physical Systems by : Ramesh Poonia
Download or read book Cyber-Physical Systems written by Ramesh Poonia and published by Academic Press. This book was released on 2021-10-30 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS). The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture. Offers perspectives on the design, development and commissioning of intelligent applications Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of COVID-19 Puts forth insights on how future illnesses can be supported using intelligent corona virus monitoring techniques
