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Dynamic data driven applications systems = 4th International Conference, DDDAS 2022, Cambridge, MA, USA, October 6-10, 2022 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Dynamic data driven applications systems/ edited by Erik Blasch, Frederica Darema, Alex Aved.
其他題名:	4th International Conference, DDDAS 2022, Cambridge, MA, USA, October 6-10, 2022 : proceedings /
其他題名:	DDDAS 2022
其他作者:	Blasch, Erik.
團體作者:	DDDAS (Conference)
出版者:	Cham :Springer Nature Switzerland : : 2024.,
面頁冊數:	xiv, 441 p. :ill. (some col.), digital ;24 cm.
內容註:	DDDAS2022 Main-Track Plenary Presentations -- Aerospace I -- Generalized multifidelity active learning for Gaussian-process-based reliability analysis -- Essential Properties of a Multimodal Hypersonic Object Detection and Tracking System -- Aerospace II -- Dynamic Airspace Control via Spatial Network Morphing -- Towards the formal verification of data-driven flight awareness: Leveraging the Cramér-Rao lower bound of stochastic functional time series models -- Coupled Sensor Configuration and Path-Planning in a Multimodal Threat Field -- Space Systems -- Probabilistic Admissible Region Based Track Initialization -- Radar cross-section modeling of space debris -- High Resolution Imaging Satellite Constellation -- Network Systems -- Reachability Analysis to Track Non-cooperative Satellite in Cislunar Regime -- Physics-Aware Machine Learning for Dynamic, Data-Driven Radar Target Recognition -- DDDAS for Optimized Design and Management of Wireless Cellular Networks -- Systems Support Methods -- DDDAS-based Learning for Edge Computing at 5G and Beyond 5G -- Monitoring and Secure Communications for Small Modular Reactors -- Data Augmentation of High-Rate Dynamic Testing via a Physics-Informed GAN Approach -- Unsupervised Wave Physics-Informed Representation Learning for Guided Wavefield Reconstruction -- Passive Radio Frequency-based 3D Indoor Positioning System via Ensemble Learning -- Deep Learning - I -- Deep Learning Approach for Data and Computing Efficient Situational Assessment and Awareness in Human Assistance and Disaster Response and Damage Assessment Applications -- SpecAL: Towards Active Learning for Semantic Segmentation of Hyperspectral Imagery -- Multimodal IR and RF based sensor system for real-time human target detection, identification, and Geolocation -- Deep Learning - II -- Learning Interacting Dynamic Systems with Neural Ordinary Differential Equations -- Relational Active Feature Elicitation for DDDAS -- Explainable Human-in-the-loop Dynamic Data-Driven Digital Twins -- Tracking -- Transmission Censoring and Information Fusion for Communication-Efficient Distributed Nonlinear Filtering -- Distributed Estimation of the Pelagic Scattering Layer using a Buoyancy Controlled Robotic System -- Towards a data-driven bilinear Koopman operator for controlled nonlinear systems and sensitivity analysis -- Security -- Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach -- Dynamic Data-Driven Digital Twins for Blockchain Systems -- Adversarial Forecasting through Adversarial Risk Analysis within a DDDAS Framework -- Distributed Systems -- Power Grid Resilience: Data Gaps for Data-Driven Disruption Analysis -- Attack-resilient Cyber-physical System State Estimation for Smart Grid Digital Twin Design -- Applying DDDAS Principles for Realizing Optimized and Robust Deep Learning Models at the Edge -- Keynotes -- Keynotes Overview -- DDDAS for Systems Analytics in Applied Mechanics -- Computing for Emerging Aerospace Autonomous Vehicles -- From genomics to therapeutics: Single-cell dissection and manipulation of disease circuitry -- Data Augmentation to Improve Adversarial Robustness of AI-Based Network Security Monitoring -- Improving Predictive Models for Environmental Monitoring using Distributed Spacecraft Autonomy -- Towards Continual Unsupervised Data Driven Adaptive Learning -- DDDAS2022 Main-Track: Wildfires Panel -- Wildfires Panel Overview -- Using Dynamic Data Driven Cyberinfrastructure for Next Generation Disaster Intelligence -- Simulating large wildland & WUI fires with a physics-based weather-fire behavior model: Understanding, prediction, and data-shaped products -- Autonomous Unmanned Aerial Vehicle systems in Wildfire Detection and Management-Challenges and Opportunities -- Role of Autonomous Unmanned Aerial Systems in Prescribed Burn Projects -- Towards a Dynamic Data Driven Wildfire Digital Twin (WDT): Impact on Deforestation, Air Quality and Cardiopulmonary Disease -- Earth System Digital Twin for Air Quality -- Dynamic Data Driven Applications for Atmospheric Monitoring and Tracking -- Workshop on Climate, Life, Earth, Planets -- Dynamic Data-Driven Downscaling to Quantify Extreme Rainfall and Flood Loss Risk -- DDDAS 2022 Conference Agenda -- Agenda, DDDAS 2022, October 6-10.
Contained By:	Springer Nature eBook
標題:	Cooperating objects (Computer systems) - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-52670-1
ISBN:	9783031526701

Dynamic data driven applications systems = 4th International Conference, DDDAS 2022, Cambridge, MA, USA, October 6-10, 2022 : proceedings /
Dynamic data driven applications systems4th International Conference, DDDAS 2022, Cambridge, MA, USA, October 6-10, 2022 : proceedings /[electronic resource] :DDDAS 2022edited by Erik Blasch, Frederica Darema, Alex Aved. - Cham :Springer Nature Switzerland :2024. - xiv, 441 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,139840302-9743 ;. - Lecture notes in computer science ;13984..

DDDAS2022 Main-Track Plenary Presentations -- Aerospace I -- Generalized multifidelity active learning for Gaussian-process-based reliability analysis -- Essential Properties of a Multimodal Hypersonic Object Detection and Tracking System -- Aerospace II -- Dynamic Airspace Control via Spatial Network Morphing -- Towards the formal verification of data-driven flight awareness: Leveraging the Cramér-Rao lower bound of stochastic functional time series models -- Coupled Sensor Configuration and Path-Planning in a Multimodal Threat Field -- Space Systems -- Probabilistic Admissible Region Based Track Initialization -- Radar cross-section modeling of space debris -- High Resolution Imaging Satellite Constellation -- Network Systems -- Reachability Analysis to Track Non-cooperative Satellite in Cislunar Regime -- Physics-Aware Machine Learning for Dynamic, Data-Driven Radar Target Recognition -- DDDAS for Optimized Design and Management of Wireless Cellular Networks -- Systems Support Methods -- DDDAS-based Learning for Edge Computing at 5G and Beyond 5G -- Monitoring and Secure Communications for Small Modular Reactors -- Data Augmentation of High-Rate Dynamic Testing via a Physics-Informed GAN Approach -- Unsupervised Wave Physics-Informed Representation Learning for Guided Wavefield Reconstruction -- Passive Radio Frequency-based 3D Indoor Positioning System via Ensemble Learning -- Deep Learning - I -- Deep Learning Approach for Data and Computing Efficient Situational Assessment and Awareness in Human Assistance and Disaster Response and Damage Assessment Applications -- SpecAL: Towards Active Learning for Semantic Segmentation of Hyperspectral Imagery -- Multimodal IR and RF based sensor system for real-time human target detection, identification, and Geolocation -- Deep Learning - II -- Learning Interacting Dynamic Systems with Neural Ordinary Differential Equations -- Relational Active Feature Elicitation for DDDAS -- Explainable Human-in-the-loop Dynamic Data-Driven Digital Twins -- Tracking -- Transmission Censoring and Information Fusion for Communication-Efficient Distributed Nonlinear Filtering -- Distributed Estimation of the Pelagic Scattering Layer using a Buoyancy Controlled Robotic System -- Towards a data-driven bilinear Koopman operator for controlled nonlinear systems and sensitivity analysis -- Security -- Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach -- Dynamic Data-Driven Digital Twins for Blockchain Systems -- Adversarial Forecasting through Adversarial Risk Analysis within a DDDAS Framework -- Distributed Systems -- Power Grid Resilience: Data Gaps for Data-Driven Disruption Analysis -- Attack-resilient Cyber-physical System State Estimation for Smart Grid Digital Twin Design -- Applying DDDAS Principles for Realizing Optimized and Robust Deep Learning Models at the Edge -- Keynotes -- Keynotes Overview -- DDDAS for Systems Analytics in Applied Mechanics -- Computing for Emerging Aerospace Autonomous Vehicles -- From genomics to therapeutics: Single-cell dissection and manipulation of disease circuitry -- Data Augmentation to Improve Adversarial Robustness of AI-Based Network Security Monitoring -- Improving Predictive Models for Environmental Monitoring using Distributed Spacecraft Autonomy -- Towards Continual Unsupervised Data Driven Adaptive Learning -- DDDAS2022 Main-Track: Wildfires Panel -- Wildfires Panel Overview -- Using Dynamic Data Driven Cyberinfrastructure for Next Generation Disaster Intelligence -- Simulating large wildland & WUI fires with a physics-based weather-fire behavior model: Understanding, prediction, and data-shaped products -- Autonomous Unmanned Aerial Vehicle systems in Wildfire Detection and Management-Challenges and Opportunities -- Role of Autonomous Unmanned Aerial Systems in Prescribed Burn Projects -- Towards a Dynamic Data Driven Wildfire Digital Twin (WDT): Impact on Deforestation, Air Quality and Cardiopulmonary Disease -- Earth System Digital Twin for Air Quality -- Dynamic Data Driven Applications for Atmospheric Monitoring and Tracking -- Workshop on Climate, Life, Earth, Planets -- Dynamic Data-Driven Downscaling to Quantify Extreme Rainfall and Flood Loss Risk -- DDDAS 2022 Conference Agenda -- Agenda, DDDAS 2022, October 6-10.

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.

ISBN: 9783031526701

Standard No.: 10.1007/978-3-031-52670-1doiSubjects--Topical Terms:

3218484
Cooperating objects (Computer systems)
--Congresses.

LC Class. No.: TK7895.E42

Dewey Class. No.: 006.22

Dynamic data driven applications systems = 4th International Conference, DDDAS 2022, Cambridge, MA, USA, October 6-10, 2022 : proceedings /
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