Dynamic Data Driven Applications Systems : 4th International Conference, DDDAS 2022, Cambridge, MA, USA, October 6–10, 2022, Proceedings / edited by Erik Blasch, Frederica Darema, Alex Aved.

Format:

Book

Contributor:

Blasch, Erik, editor.

Darema, Frederica, editor.

Aved, Alex, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 13984

Language:

English

Subjects (All):

Computer simulation.

Computers, Special purpose.

Quantitative research.

Dynamics.

Nonlinear theories.

Computer Modelling.

Special Purpose and Application-Based Systems.

Data Analysis and Big Data.

Applied Dynamical Systems.

Local Subjects:

Computer Modelling.

Special Purpose and Application-Based Systems.

Data Analysis and Big Data.

Applied Dynamical Systems.

Physical Description:

1 online resource (434 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

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.

Contents:

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.

.

Notes:

Includes bibliographical references and index.

ISBN:

3-031-52670-8