Описание: In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data.
Автор: Solomon Michael G. Название: Blockchain Data Analytics for Dummies ISBN: 1119651778 ISBN-13(EAN): 9781119651772 Издательство: Wiley Рейтинг: Цена: 4117.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Get ahead of the curve-learn about big data on the blockchain Blockchain came to prominence as the disruptive technology that made cryptocurrencies work. Now, data pros are using blockchain technology for faster real-time analysis, better data security, and more accurate predictions. Blockchain Data Analytics For Dummies is your quick-start guide to harnessing the potential of blockchain.
Inside this book, technologists, executives, and data managers will find information and inspiration to adopt blockchain as a big data tool. Blockchain expert Michael G. Solomon shares his insight on what the blockchain is and how this new tech is poised to disrupt data.
Set your organization on the cutting edge of analytics, before your competitors get there! Learn how blockchain technologies work and how they can integrate with big dataDiscover the power and potential of blockchain analyticsEstablish data models and quickly mine for insights and resultsCreate data visualizations from blockchain analysis Discover how blockchains are disrupting the data world with this exciting title in the trusted For Dummies line!
Management of V.U.C.A. (Volatility, Uncertainty, Complexity and Ambiguity) using Machine Learning Techniques in Industry 4.0 Paradigm.- Role of Industry 4.0 in Performance Improvement of Furniture Cluster.- Imparting Industry 4.0 Education using Open Source Tools: A Case.- Decision support framework for smart implementation of green supply chain management practices.- Decision Support System for Supply Chain Performance Measurement: Case of Textile Industry.- On the Condition Monitoring and Maintenance Approaches for Corrosive Sulphur Deposition in Oil-Filled Electrical Transformers.- Principal Components based Multivariate Statistical Process Monitoring of Machining Process using Machine Vision Approach.- Green IS - Exploring Environmental Sensitive IS through the Lens of Enterprise Architecture.
Автор: Miao Pan; Jingyi Wang; Sai Mounika Errapotu; Xinyu Название: Big Data Privacy Preservation for Cyber-Physical Systems ISBN: 3030133699 ISBN-13(EAN): 9783030133696 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This SpringerBrief mainly focuses on effective big data analytics for CPS, and addresses the privacy issues that arise on various CPS applications. The authors develop a series of privacy preserving data analytic and processing methodologies through data driven optimization based on applied cryptographic techniques and differential privacy in this brief. This brief also focuses on effectively integrating the data analysis and data privacy preservation techniques to provide the most desirable solutions for the state-of-the-art CPS with various application-specific requirements. Cyber-physical systems (CPS) are the “next generation of engineered systems,” that integrate computation and networking capabilities to monitor and control entities in the physical world. Multiple domains of CPS typically collect huge amounts of data and rely on it for decision making, where the data may include individual or sensitive information, for e.g., smart metering, intelligent transportation, healthcare, sensor/data aggregation, crowd sensing etc. This brief assists users working in these areas and contributes to the literature by addressing data privacy concerns during collection, computation or big data analysis in these large scale systems. Data breaches result in undesirable loss of privacy for the participants and for the entire system, therefore identifying the vulnerabilities and developing tools to mitigate such concerns is crucial to build high confidence CPS.This Springerbrief targets professors, professionals and research scientists working in Wireless Communications, Networking, Cyber-Physical Systems and Data Science. Undergraduate and graduate-level students interested in Privacy Preservation of state-of-the-art Wireless Networks and Cyber-Physical Systems will use this Springerbrief as a study guide.
Management of V.U.C.A. (Volatility, Uncertainty, Complexity and Ambiguity) using Machine Learning Techniques in Industry 4.0 Paradigm.- Role of Industry 4.0 in Performance Improvement of Furniture Cluster.- Imparting Industry 4.0 Education using Open Source Tools: A Case.- Decision support framework for smart implementation of green supply chain management practices.- Decision Support System for Supply Chain Performance Measurement: Case of Textile Industry.- On the Condition Monitoring and Maintenance Approaches for Corrosive Sulphur Deposition in Oil-Filled Electrical Transformers.- Principal Components based Multivariate Statistical Process Monitoring of Machining Process using Machine Vision Approach.- Green IS - Exploring Environmental Sensitive IS through the Lens of Enterprise Architecture.
Автор: Stimmel Carol L. Название: Big Data Analytics Strategies for the Smart Grid ISBN: 1482218283 ISBN-13(EAN): 9781482218282 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments.
Readable and accessible, Big Data Analytics Strategies for the Smart Grid addresses the needs of applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. It supplies industry stakeholders with an in-depth understanding of the engineering, business, and customer domains within the power delivery market. The book explores the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers. It not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls. Discussing security and data privacy, it explores the role of the utility in protecting their customers' right to privacy while still engaging in forward-looking business practices. The book includes discussions of:
SAS for asset management tools
The AutoGrid approach to commercial analytics
Space-Time Insight's work at the California ISO (CAISO)
This book is an ideal resource for mid- to upper-level utility executives who need to understand the business value of smart grid data analytics. It explains critical concepts in a manner that will better position executives to make the right decisions about building their analytics programs.
At the same time, the book provides sufficient technical depth that it is useful for data analytics professionals who need to better understand the nuances of the engineering and business challenges unique to the utilities industry.
Описание: The authors consider methods, architectures, and technologies applicable in use cases according to the viewpoints of product engineering and production system engineering, and regarding the triangle of (1) product to be produced by a (2) production process executed on (3) a production system resource.
Автор: Tekinerdogan, Bedir Название: Multi-Paradigm Modelling Approaches For Cyber-Physical Systems ISBN: 0128191058 ISBN-13(EAN): 9780128191057 Издательство: Elsevier Science Рейтинг: Цена: 19875.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Truly complex, engineered systems, known as Cyber Physical Systems (CPS), are emerging to integrate physical, software, and network domains. To date, no unifying theory, systematic design methods, techniques or tools exist for such systems. Individual (mechanical, electrical, network or software) engineering disciplines offer only partial solutions. Multi-paradigm Modelling (MPM) proposes to model every aspect of these complex systems, at the most appropriate level(s) of abstraction and using the most appropriate modelling formalism(s). Modelling language engineering, including model transformation, and the study of their semantics, are used to realize MPM, which is seen as an effective answer to the challenges of designing Cyber Physical Systems.
Multi-Paradigm Modelling for Cyber-Physical Systems will explore modelling and analysis as crucial activities in the development of Cyber-Physical Systems, which are inherently cross-disciplinary in nature and require distinct modelling techniques related to different disciplines, as well as a common background knowledge bridge to enable communication between all specialties. The book will serve as a reference for anyone starting in the field of CPS who will need a solid foundation of modelling CPS and a comprehensive introduction to the distinct existing techniques, with clear explanations of their advantages and limitations. Although most of these techniques are already used as a matter of common practice in certain disciplines, the knowledge of their fundamentals and applications is typically unfamiliar to practitioners of another area. The net result is the tendency for CPS practitioners to use the technique that they are most comfortable with, disregarding the technique that would be the most adequate for the problem and modelling goal.
This book is aimed at both researchers and practitioners who are interested in various modelling paradigms across computer science and engineering. Researchers will gain novel insights into the basic theories and background, cutting-edge research topics, as well as the related challenges and research directions for model management and analytics. Practitioners will benefit from the presentation of key problems, solution approaches and tools which have been developed or are necessary for model management and analytics.
Автор: Ali Tajer, Samir M. Perlaza, H. Vincent Poor Название: Advanced Data Analytics for Power Systems ISBN: 1108494757 ISBN-13(EAN): 9781108494755 Издательство: Cambridge Academ Рейтинг: Цена: 16474.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Experts in data analytics and power engineering present theories addressing the needs of modern power systems. Covering theory and application to the solution of power system problems relating to reliability, efficiency, and security, this is an essential resource for graduate students and researchers in academia and industry.
Описание: This book covers cutting-edge and advanced research on data processing techniques and applications for cyber-physical systems, gathering the proceedings of the International Conference on Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2020), held in Laibin City, Guangxi Province, China, on December 11-12, 2020.
Introduction.- Foundations and Related Literature.- SPNTA: Stochastic Petri-Net-Based Reliability Analysis under Topology Attacks.- DHCD: Distributed Host-Based Collaborative Detection for FDI Attacks.- DDOA: Dirichlet-Based Detection for Opportunistic Attacks.- PFDD: On Feasibility and Limitations of Detecting FDI Attacks Using DFACTS.- Conclusion.
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