Handbook of Dynamic Data Driven Applications Systems (Record no. 184829)

MARC details
000 -LEADER
fixed length control field 07370nam a22006375i 4500
001 - CONTROL NUMBER
control field 978-3-031-27986-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423130059.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 230914s2023 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031279867
-- 978-3-031-27986-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-031-27986-7
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.9.C65
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYM
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM072000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYM
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 003.3
Edition number 23
245 10 - TITLE STATEMENT
Title Handbook of Dynamic Data Driven Applications Systems
Medium [electronic resource] :
Remainder of title Volume 2 /
Statement of responsibility, etc edited by Frederica Darema, Erik P. Blasch, Sai Ravela, Alex J. Aved.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2023.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2023.
300 ## - PHYSICAL DESCRIPTION
Extent X, 956 p. 316 illus., 281 illus. in color.
Other physical details online resource.
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505 0# - FORMATTED CONTENTS NOTE
Formatted contents note The Dynamic Data Driven Applications Systems (DDDAS) Paradigm and Emerging Directions -- Dynamic Data Driven Applications Systems and Information-Inference Couplings -- Polynomial Chaos Expansion Based Nonlinear Filtering for Dynamic State Estimation -- Measure-Invariant Symbolic Systems for Pattern Recognition and Anomaly Detection -- Equation–Free Computations as DDDAS Protocols for Bifurcation Studies: A Granular Chain Example -- A Stochastic Dynamic Data-Driven Framework for Real-time Prediction of Materials Damage in Composites -- Dynamic Data-Driven Monitoring of Nanoparticle Self Assembly Processes -- From Data to Decisions: A Real-Time Measurement -Inversion-Prediction-Steering Framework for Hazardous Events and Structural Health Monitoring -- Bayesian Computational Sensor Networks: Small-Scale Structural Health Monitoring -- A Dynamic Data Driven Sensor Tasking with Application of Aerospace Systems -- Dynamic Data-Driven Application Systems for Reservoir Simulation-Based Optimization: Lessons Learned and Future Trends -- DDDAS within the Oil and Gas Industry -- A Simulation-Based Online Dynamic Data-Driven Framework for Large-Scale Wind-turbine Farm Systems Operation -- Towards Dynamic Data Driven Systems for Rapid Adaptive Interdisciplinary Ocean Forecasting -- Towards Cyber-Eco Systems: Networked Sensing, Inference and Control for Ecological and Agricultural Systems -- An Energy-Aware Airborne Dynamic Data-Driven Application System for Persistent Sampling and Surveillance -- Using Dynamic Data Driven Cyberinfrastructure for Next Generation Wildland Fire Intelligence -- Autonomous Monitoring of Wildfires with Vision-Equipped UAS and Temperature Sensors via Evidential Reasoning -- Airborne Fire Detection and Modeling using Unmanned Aerial Vehicles Imagery: Datasets and Approaches -- DDDAS-based Remote Sensing -- Advances in Domain Adaptation for Aerial Imagery -- Retrospective Cost Parameter Estimation with Application to Space Weather Modeling -- A Dynamic Data Driven Approach to Space Situational Awareness -- Data driven cancer research with digital microscopy and Pathomics -- Robust Data Driven Region of Interest Segmentation for Breast Thermography -- Adaptive Data Stream Mining (DSM) Systems -- Deception Detection in Videos using Robust Facial Features with Attention Feedback -- Manufacturing the Future via Dynamic Data Driven Applications Systems (DDDAS) -- DDDAS in the Social Sciences -- Anomaly-Detection Defense against Test-Time Evasion Attacks on Robust DNNs -- Dynamic Data-Driven Approach for Cyber Resilient and Secure Critical Energy Systems -- Dynamic Network-centric Multi-cloud Platform for Real-Time and Data-Intensive Science Workflows -- INDICES: Applying DDDAS Principles for Performance Interference‐aware Cloud‐to‐Fog Application Migration -- Adaptive Routing for Hybrid Photonic-Plasmonic (HyPPI) Interconnection Network for Manycore Processors using DDDAS on the Chip.
520 ## - SUMMARY, ETC.
Summary, etc 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 ofmany of the important research and development efforts conducted under the rubric of DDDAS through the examples and case studies presented, either within their own field or other fields of study. DDDAS has proven to be a transformative technology as data has become the third part of the triad, with theory and computation as the other two parts. Initially DDDAS was part of control theory but as data have become ubiquitous there has been a paradigm shift, initiated by DDDAS, from simulation to effectively using data for prediction. John Cherniavsky, retired, as Division Director, NSF - US National Science Foundation The DDDAS paradigm integrates and enhances the deepest, most well-grounded foundations and tools - both from expert based methods and from learning-based methods, building well beyond more popular and limited forms of AI. This book provides a unique breadth and depth of scope across many science and technology fields, showing how DDDAS is an overarching concept that connects and unifies the wide diversity across these fields. Paul Werbos, retired, as Program Director, NSF - US National Science Foundation .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer simulation.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Big data.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computers, Special purpose.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Dynamics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Nonlinear theories.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Dynamical systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Quantitative research.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Modelling.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Big Data.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Special Purpose and Application-Based Systems.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Applied Dynamical Systems.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Dynamical Systems.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Analysis and Big Data.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Darema, Frederica.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Blasch, Erik P.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Ravela, Sai.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Aved, Alex J.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031279850
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031279874
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783031279881
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-27986-7">https://doi.org/10.1007/978-3-031-27986-7</a>
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Koha item type eBooks-CSE-Springer

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