Handbook Of Dynamic Data Driven Applications Systems
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Handbook Of Dynamic Data Driven Applications Systems
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Author : Erik Blasch
language : en
Publisher: Springer
Release Date : 2018-11-13
Handbook Of Dynamic Data Driven Applications Systems written by Erik Blasch and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-13 with Computers categories.
The Handbook of Dynamic Data Driven Applications Systems establishes an authoritative reference of DDDAS, pioneered by Dr. Darema and the co-authors for researchers and practitioners developing DDDAS technologies. Beginning with general concepts and history of the paradigm, the text provides 32 chapters by leading experts in10 application areas to enable an accurate understanding, analysis, and control of complex systems; be they natural, engineered, or societal: Earth and Space Data Assimilation Aircraft Systems Processing Structures Health Monitoring Biological Data Assessment Object and Activity Tracking Embedded Control and Coordination Energy-Aware Optimization Image and Video Computing Security and Policy Coding Systems Design The authors explain how DDDAS unifies the computational and instrumentation aspects of an application system, extends the notion of Smart Computing to span from the high-end to the real-time data acquisition and control, and manages Big Data exploitation with high-dimensional model coordination.
Handbook Of Dynamic Data Driven Applications Systems
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Author : Erik Blasch
language : en
Publisher:
Release Date : 2025-07-09
Handbook Of Dynamic Data Driven Applications Systems written by Erik Blasch and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-09 with Computers categories.
This handbook is an authoritative reference on the Dynamic Data Driven Applications Systems paradigm, pioneered by Dr. Darema, and contains DDDAS-based work conducted by contributing co-authors in numerous areas, to benefit science and technology researchers and practitioners developing DDDAS-based technologies. Beginning with general concepts and history of the DDDAS paradigm in the introductory chapter, this Third Volume in the series contains 33 chapters contributed by leading experts and is organized in nine thematic areas, spanning natural, engineered, or societal systems to enable an accurate understanding, analysis, and control of corresponding complex systems. The thematic areas cover fundamental and foundational methods; materials, structural, and energy systems; healthcare and situation awareness systems; air and space, communications, and cyber systems. The work presented shows how DDDAS unifies the computational and instrumentation aspects of an application system, extends computing notions to span from the high-end to the edge computing and real-time data acquisition and control, adaptively manages the operation of complex, distributed, multimodal systems through high-dimensional, systems-cognizant model-coordination and multi-objective optimization of resources and service delivery; supports methodologies for achieving autonomic and enhanced AI capabilities; DDDAS is foundational concept for Predictive Digital Twins and Dynamic Digital Twins. The authorsexplain how DDDAS unifies the computational and instrumentation aspects of an application system, extends the notion of Smart Computing to span from the high-end to the real-time data acquisition and control, and manages Big Data exploitation with high-dimensional model coordination.
Handbook Of Dynamic Data Driven Applications Systems
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Author : Erik P. Blasch
language : en
Publisher: Springer Nature
Release Date : 2022-05-11
Handbook Of Dynamic Data Driven Applications Systems written by Erik P. Blasch and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-11 with Computers categories.
The Handbook of Dynamic Data Driven Applications Systems establishes an authoritative reference of DDDAS, pioneered by Dr. Darema and the co-authors for researchers and practitioners developing DDDAS technologies. Beginning with general concepts and history of the paradigm, the text provides 32 chapters by leading experts in ten application areas to enable an accurate understanding, analysis, and control of complex systems; be they natural, engineered, or societal: The authors explain how DDDAS unifies the computational and instrumentation aspects of an application system, extends the notion of Smart Computing to span from the high-end to the real-time data acquisition and control, and manages Big Data exploitation with high-dimensional model coordination. The Dynamically Data Driven Applications Systems (DDDAS) paradigm inspired research regarding the prediction of severe storms. Specifically, the DDDAS concept allows atmospheric observing systems, computer forecast models, and cyberinfrastructure to dynamically configure themselves in optimal ways in direct response to current or anticipated weather conditions. In so doing, all resources are used in an optimal manner to maximize the quality and timeliness of information they provide. Kelvin Droegemeier, Regents’ Professor of Meteorology at the University of Oklahoma; former Director of the White House Office of Science and Technology Policy We may well be entering the golden age of data science, as society in general has come to appreciate the possibilities for organizational strategies that harness massive streams of data. The challenges and opportunities are even greater when the data or the underlying system are dynamic - and DDDAS is the time-tested paradigm for realizing this potential. Sangtae Kim, Distinguished Professor of Mechanical Engineering and Distinguished Professor of Chemical Engineering at Purdue University
Handbook Of Dynamic Data Driven Applications Systems
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Author : Frederica Darema
language : en
Publisher: Springer Nature
Release Date : 2023-09-14
Handbook Of Dynamic Data Driven Applications Systems written by Frederica Darema and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-14 with Computers categories.
This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
Handbook Of Dynamic Data Driven Applications Systems
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Author : Frederica Darema
language : en
Publisher: Springer
Release Date : 2024-09-15
Handbook Of Dynamic Data Driven Applications Systems written by Frederica Darema and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-15 with Computers categories.
This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems' analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems ("applications systems"), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990's to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the "DDDAS-based Digital Twin" or "Dynamic Digital Twin", goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
Dynamic Data Driven Applications Systems
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Author : Erik Blasch
language : en
Publisher: Springer Nature
Release Date : 2024-02-26
Dynamic Data Driven Applications Systems written by Erik Blasch and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-26 with Computers categories.
This book constitutes the refereed proceedings of the 4th International Conference on Dynamic Data Driven Applications Systems, DDDAS 2022, which took place in Cambridge, MA, USA, during October 6–10, 2022. The 31 regular papers in the main track and 5 regular papers from the Wildfires panel, as well as one workshop paper, were carefully reviewed and selected for inclusion in the book. They were organized in following topical sections: DDAS2022 Main-Track Plenary Presentations; Keynotes; DDDAS2022 Main-Track: Wildfires Panel; Workshop on Climate, Life, Earth, Planets.
Dynamic Data Driven Applications Systems
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Author : Frederica Darema
language : en
Publisher: Springer Nature
Release Date : 2020-11-02
Dynamic Data Driven Applications Systems written by Frederica Darema and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-02 with Computers categories.
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.
Intelligent Human Systems Integration 2020
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Author : Tareq Ahram
language : en
Publisher: Springer Nature
Release Date : 2020-01-22
Intelligent Human Systems Integration 2020 written by Tareq Ahram and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-22 with Technology & Engineering categories.
This book presents cutting-edge research on innovative human systems integration and human–machine interaction, with an emphasis on artificial intelligence and automation, as well as computational modeling and simulation. It covers a wide range of applications in the areas of design, construction and operation of products, systems and services, and discusses the human factors in a wide range of settings. Gathering the proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020), held on February 19–21, 2020, in Modena, Italy, the book’s goal is to advance the theory and applications of artificial cognitive systems and improve human-artificial systems collaboration. Special emphasis is placed on automotive design, autonomous vehicles and the applications of artificial intelligence. The book offers a timely survey and source of inspiration for human factors engineers, automotive engineers, IT developers and UX designers who are working to shape the future of automated intelligent systems.
Machine Learning And Granular Computing A Synergistic Design Environment
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Author : Witold Pedrycz
language : en
Publisher: Springer Nature
Release Date : 2024-09-21
Machine Learning And Granular Computing A Synergistic Design Environment written by Witold Pedrycz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-21 with Computers categories.
This volume provides the reader with a comprehensive and up-to-date treatise positioned at the junction of the areas of Machine Learning (ML) and Granular Computing (GrC). ML offers a wealth of architectures and learning methods. Granular Computing addresses useful aspects of abstraction and knowledge representation that are of importance in the advanced design of ML architectures. In unison, ML and GrC support advances of the fundamental learning paradigm. As built upon synergy, this unified environment focuses on a spectrum of methodological and algorithmic issues, discusses implementations and elaborates on applications. The chapters bring forward recent developments showing ways of designing synergistic and coherently structured ML-GrC environment. The book will be of interest to a broad audience including researchers and practitioners active in the area of ML or GrC and interested in following its timely trends and new pursuits.
Recent Advances In Smart Self Healing Polymers And Composites
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Author : Guoqiang Li
language : en
Publisher: Woodhead Publishing
Release Date : 2022-06-08
Recent Advances In Smart Self Healing Polymers And Composites written by Guoqiang Li and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-08 with Technology & Engineering categories.
There have been many new developments since the first edition of this book was published back in 2015. These can be summarized as follows: integration of multiple properties into self-healing polymer materials, such as the shape memory effect and flame retardancy; beyond self-healing and the development of recyclable thermoset polymers; and the application of self-healing polymers in both 3D and 4D printing. Recent Advances in Smart Self-healing Polymers and Composites, Second Edition provides a comprehensive introduction to the fascinating field of smart self-healing polymers and composites. All chapters are brought fully-up-to-date with the addition of six brand new contributions on the characterization of self-healing polymers, light-triggered self-healing, additive manufacturing, multifunctional thermoset polymers with self-healing ability, and recyclable thermoset polymers and 4D printing. It is written for a large readership including not only R&D researchers from diverse backgrounds such as chemistry, materials science, aerospace, physics, and biological science, but also for graduate student working on self-healing technologies as well as their newly developed applications. - Features new chapters on characterization of self-healing polymers, light-triggered self-healing, additive manufacturing, multifunctional thermoset polymers with self-healing ability, recyclable thermoset polymers and 4D printing - All chapters have been significantly updated from the previous edition - Provides a grounding in all key areas of research to bring people up to speed with the latest developments