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Handbook of Dynamic Data Driven Applications Systems [[electronic resource] ] : Volume 2 / / edited by Frederica Darema, Erik P. Blasch, Sai Ravela, Alex J. Aved
Handbook of Dynamic Data Driven Applications Systems [[electronic resource] ] : Volume 2 / / edited by Frederica Darema, Erik P. Blasch, Sai Ravela, Alex J. Aved
Autore Darema Frederica
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (937 pages)
Disciplina 003.3
Altri autori (Persone) BlaschErik P
RavelaSai
AvedAlex J
Soggetto topico Computer simulation
Big data
Computers, Special purpose
Dynamics
Nonlinear theories
Dynamical systems
Quantitative research
Computer Modelling
Big Data
Special Purpose and Application-Based Systems
Applied Dynamical Systems
Dynamical Systems
Data Analysis and Big Data
ISBN 3-031-27986-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNISA-996550557203316
Darema Frederica  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Handbook of Dynamic Data Driven Applications Systems : Volume 2 / / edited by Frederica Darema, Erik P. Blasch, Sai Ravela, Alex J. Aved
Handbook of Dynamic Data Driven Applications Systems : Volume 2 / / edited by Frederica Darema, Erik P. Blasch, Sai Ravela, Alex J. Aved
Autore Darema Frederica
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (937 pages)
Disciplina 003.3
Altri autori (Persone) BlaschErik P
RavelaSai
AvedAlex J
Soggetto topico Computer simulation
Big data
Computers, Special purpose
Dynamics
Nonlinear theories
Dynamical systems
Quantitative research
Computer Modelling
Big Data
Special Purpose and Application-Based Systems
Applied Dynamical Systems
Dynamical Systems
Data Analysis and Big Data
ISBN 3-031-27986-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNINA-9910746100403321
Darema Frederica  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui