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Dynamic Data Driven Applications Systems : 5th International Conference, DDDAS/Infosymbiotics for Reliable AI 2024, New Brunswick, NJ, USA, November 6–8, 2024, Proceedings / / edited by Erik Blasch, Frederica Darema, Dimitris Metaxas
| Dynamic Data Driven Applications Systems : 5th International Conference, DDDAS/Infosymbiotics for Reliable AI 2024, New Brunswick, NJ, USA, November 6–8, 2024, Proceedings / / edited by Erik Blasch, Frederica Darema, Dimitris Metaxas |
| Autore | Blasch Erik |
| Edizione | [1st ed. 2026.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026 |
| Descrizione fisica | 1 online resource (664 pages) |
| Disciplina | 003.3 |
| Altri autori (Persone) |
DaremaFrederica
MetaxasDimitris |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
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 |
| ISBN | 9783031948954 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Introduction to the Proceedings. -- Introduction to the DDDAS2024 Conference Infosymbiotics/DDDAS and AI: Towards Reliable AI. -- Plenary Papers. -- Materials, Aerospace, and Geomechanics Systems Methods. -- Online Fault Detection for Metal Additive Manufacturing with Data Driven Time Series Models. -- Weight Decay Optimized Unsupervised Autoencoder Based Anomaly Detection in Uncontrolled Dynamic Structural Health Monitoring. -- Novel Deep Learning Image Registration Techniques with Application to Microscopy Images of Metal Alloys. -- A Probabilistic Machine Learning Pipeline Using Topological Descriptors for Real-Time State Estimation of High-Rate Dynamic Systems. -- Information Fusion of Ultrasonic Waves and Low-Frequency Vibrations: Leveraging Probabilistic Machine Learning and Stochastic Time Series Models for Structural Awareness. -- Earthen Embankment Monitoring using LiDAR data by Randomized Consensus of Topological Data Analysis. -- Environmental Systems-Assessment/Response, DT Methods. -- Large Language Models for Explainable Decisions in Dynamic Digital Twins. -- DDDAS Probability Learning for Natural Disaster Change Detection. -- Dynamic Data-Driven Digital Twin Testbed for Enhanced First Responder Training and Communication. -- A Dynamic Data Driven Agent Based Model for Characterizing the Space Utilization of Asian Elephants in Response to Water Availability. -- Adaptive Multi-stage Sensor Fusion under Neuro-symbolic Framework for The Multi-modal Ranging System in Adverse Weather Conditions. -- Towards a Dynamic Data Driven Al Regional Weather Forecast Model. -- Autonomous Uncrewed Aircraft for Mobile Operations in Severe Weather. -- Autonomous Planning for Targeted Observation of Severe Weather. -- Security Systems –Methods, infrastructures, applications. -- Dynamic Data Driven Security Framework for Industrial Control Networks using Programmable Switches. -- Security of RF Sensing and Imaging Systems in the Age of Digital Twins. -- CCTV-Gun: Benchmarking Handgun Detection in CCTV Images. -- D4: Dynamic Data-Driven Discovery of Adversarial Vehicle Maneuvers. -- Data Poisoning: An Overlooked Threat to Power Grid Resilience. -- GAN-Based Approach for Detecting Energy Deception Attacks in CPS. -- Adversarial Attacks and Data-Driven Dynamic Outlier Detection Systems. -- Utilizing Matrix Profile with the DDDAS Framework for Anomaly Detection in Nuclear Security. -- Development of an Edge Resilient ML Ensemble to Tolerate ICS Adversarial Attacks. -- Anomaly Detection Transformer: A Novel Approach for Time Series Analysis of Wearable Health Data. -- A Spiral-Theoretic Approach for Trustworthy Al/ML in DDDAS. -- Tracking Systems, Automation and Robotics. -- Data-Driven Pixel Control: Challenges and Prospects. -- Dynamic Data-Driven Approach for LEO PNT Selection of Satellites with Poorly Known Ephemerides. -- Improving Physics-based Motion and Physical Parameter Estimations of a Tumbling, Non-cooperative Space Object Through DDDAS. -- An Expected KLD Based Censoring Strategy for Target Tracking in Distributed Sensor Networks. -- Reliable Al for UAVs Through Control/Perception Co-Design. -- Constraint-Aware Diffusion Models for Trajectory Optimization. -- Data-Driven Dynamics of Robot Locomotion on Granular Media. -- Improving Physics-based Motion and Physical Parameter Estimations of a Tumbling, Non-cooperative Space Object Through DDDAS. -- A Physics-Enhanced Deep Learning Model for Fast Prediction of the Behavior of a Forced Dynamic System. -- Edge-to-Cloud Al-Assisted Augmented Reality for Robust and Real-time Assistance to Operators. -- CAD Model Guided Semantic Segmentation for Radar Micro-UAV Signature Synthesis Across Different Clutter Environments Transformer: A Novel Approach for Time Series Analysis of Wearable Health Data. -- Towards Reliable Neural Optimizers: A Permutation Equivariant Neural Approximation for Information Processing Applications. -- Fast Topological Data Analysis Feature for Nonstationary Time Series. -- Predictive Modeling of Application Runtime in Dragonfly Systems. -- Adaptive Data Driven Network Slicing and Resource Blocks Assignment using Deep Reinforcement Learning. -- Explainable Diffusion Model via Schroedinger Bridge in Multimodal Image Translation. -- Using Mamba for Modeling Dynamical Systems in a Limited Data Scenario. -- Application of a state space based neural network model for Uncertainty Propagation in dynamical systems. -- From Positive to Negative: On the Role of Negative Data in Enhancing Generative Models for Engineering Constraint Satisfaction. |
| Record Nr. | UNISA-996673178803316 |
Blasch Erik
|
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Dynamic Data Driven Applications Systems : 4th International Conference, DDDAS 2022, Cambridge, MA, USA, October 6-10, 2022, Proceedings
| Dynamic Data Driven Applications Systems : 4th International Conference, DDDAS 2022, Cambridge, MA, USA, October 6-10, 2022, Proceedings |
| Autore | Blasch Erik |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (434 pages) |
| Altri autori (Persone) |
DaremaFrederica
AvedAlex |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 3-031-52670-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Introduction to the DDDAS2022 Conference -- Introduction to the DDDAS2022 Conference Infosymbiotics/Dynamic Data Driven Applications Systems -- 1 DDAS Developments -- 2 DDDAS Concept Review -- 3 DDDAS2022 Conference - Proceedings Outline -- 4 DDDAS2022 - Main Track Plenary Presentations Overview -- 4.1 Space Systems -- 4.2 Aerospace Systems -- 4.3 Networked Systems and Security -- 4.4 Deep Learning Systems -- 4.5 Estimation and Tracking -- 5 Summary Remarks -- References -- Main-Track Plenary Presentations - Aerospace -- Generalized Multifidelity Active Learning for Gaussian-process-based Reliability Analysis -- 1 Introduction -- 2 Multifidelity Active Learning for Reliability Analysis -- 2.1 Multifidelity Active Learning Method Overview -- 2.2 Sample Location: EFF/AK-MCS/TIMSE -- 2.3 Information Source: Weighted Lookahead Information Gain -- 3 Numerical Experiment: Reliability Analysis of Acoustic Horn -- 4 Conclusions and Future Directions -- References -- Essential Properties of a Multimodal Hypersonic Object Detection and Tracking System -- 1 Introduction -- 2 Sensing Modalities for Hypersonic Detection -- 2.1 Radar -- 2.2 Thermal -- 3 Tracking -- 4 Iterative Sensor Operation in DDDAS System -- 5 Conclusion -- 6 Disclaimer -- References -- Dynamic Airspace Control via Spatial Network Morphing -- 1 Introduction -- 2 Background -- 3 Structured Airspace and Aircraft Trajectories -- 4 A DDDAS Approach to Multiple Aircraft Deconfliction -- 5 Experiments -- 6 Conclusion -- References -- On Formal Verification of Data-Driven Flight Awareness: Leveraging the Cramér-Rao Lower Bound of Stochastic Functional Time Series Models -- 1 Introduction -- 2 Functionally Pooled Time Series Models -- 2.1 CRLB Formulation for VFP-AR Models -- 3 Machine-Checked Proof of the CRLB Theorem.
4 Experimental Results and Discussion -- 5 Conclusions -- References -- Coupled Sensor Configuration and Path-Planning in a Multimodal Threat Field -- 1 Introduction -- 2 Problem Formulation -- 3 Multimodal Field Estimation -- 4 Coupled Sensor Configuration -- 5 Results and Discussion -- 5.1 Demonstrative Example -- 6 Conclusion -- References -- Main-Track Plenary Presentations - Space Systems -- Geometric Solution to Probabilistic Admissible Region Based Track Initialization -- 1 Introduction -- 2 Geometric Solution to Probabilistic Admissible Region -- 2.1 Probabilistic Admissible Region -- 2.2 G-PAR Algorithm -- 3 G-PAR for Short-Arc Radar Observations -- 3.1 Initialization: G-PAR MC Particle Cloud -- 4 G-PAR for Angles-Only, Short-Arc, Telescope Observation -- 4.1 Initialization: G-PAR MC Particle Cloud -- 5 Conclusion -- References -- Radar Cross-Section Modeling of Space Debris -- 1 Introduction -- 2 Mie Scattering Modeling Motivation -- 3 Bistatic Radar Characteristics and RCS -- 3.1 Forward Scatter Geometry -- 3.2 Radar Cross Section (RCS) -- 3.3 Velocity-Induced Doppler Shift -- 3.4 Rotation-Induced Micro-doppler Shift -- 4 Simulation Results -- 4.1 RCS vs. Silhouette Area -- 4.2 Translation (Velocity-Induced) Doppler Shift -- 4.3 Translation-Doppler-Shifted RCS -- 4.4 Micro-doppler (Rotation-Induced) Shift -- 4.5 Translation- and Rotation-Shifted RCS -- 5 Conclusions -- References -- High-Resolution Imaging Satellite Constellation -- 1 Introduction -- 2 Model of Satellite Constellation Imaging -- 3 Imaging Algorithm and Resolution -- 4 Simulation Results -- 5 Conclusions -- References -- Main-Track Plenary Presentations - Network Systems -- Reachability Analysis to Track Non-cooperative Satellite in Cislunar Regime -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Limits of the Method -- 5 Conclusions -- References. Physics-Aware Machine Learning for Dynamic, Data-Driven Radar Target Recognition -- 1 Introduction -- 2 Physics-Based Models for μD Signature Synthesis -- 3 Adversarial Learning-Based μD Signature Synthesis -- 4 Physics-Aware GAN Design -- 5 Conclusion -- References -- DDDAS for Optimized Design and Management of 5G and Beyond 5G (6G) Networks -- 1 Introduction -- 2 Background of 5G and 6G Technologies -- 3 DDDAS for 5G Network Design and Optimization -- 3.1 Case Study I: Transmission of Multimedia Content to Mobile Wireless Users -- 3.2 Case Study II: Collaborative Microgrids -- 4 Conclusion -- References -- Plenary Presentations - Systems Support Methods -- DDDAS-Based Learning for Edge Computing at 5G and Beyond 5G -- 1 Introduction -- 2 Proposed Joint Optimization Approach -- 2.1 Task Scheduling and Offloading (TSO) -- 2.2 Microgrid Operational Planning -- 3 Simulation Results and Analysis -- 4 Conclusion -- References -- Monitoring and Secure Communications for Small Modular Reactors -- 1 Introduction -- 2 Model Development and Results -- 2.1 Liquid Sodium Vessel Monitoring Using LSTM Models -- 2.2 Secure Communications Using BB84 and AES Protocols -- 3 Conclusions -- References -- Data Augmentation of High-Rate Dynamic Testing via a Physics-Informed GAN Approach -- 1 Introduction -- 2 Theory Background -- 2.1 Dataset and Preprocessing -- 2.2 Convolutional Variational Autoencoders (CVAE) -- 2.3 FEM Based Conditional Generative Adversarial Networks (cGAN) -- 2.4 Support Vector Machine (SVM) -- 3 Validation of Damage Classifications -- 3.1 Convolutional Variational Autoencoder (CVAE) -- 3.2 FEM Based Conditional Generative Adversarial Network -- 3.3 Classification Results -- 4 Conclusions -- References -- Unsupervised Wave Physics-Informed Representation Learning for Guided Wavefield Reconstruction -- 1 Introduction -- 1.1 Overview. 2 Wave-Informed Regression Methodology -- 2.1 Mean Squared Error Loss -- 2.2 Wave-Informed Loss -- 2.3 Mode Number Loss -- 2.4 Wave-Informed Regression -- 2.5 Wave-Informed Algorithm -- 3 Simulation Setup -- 4 Results -- 5 Conclusions -- References -- Passive Radio Frequency-Based 3D Indoor Positioning System via Ensemble Learning -- 1 Introduction -- 2 Frequency-Adaptive PIPS -- 3 Experiment and Results -- 3.1 Experimental Setup -- 3.2 Results and Evaluation -- 4 Discussion -- 5 Conclusion -- References -- Plenary Presentations - Deep Learning -- Deep Learning Approach for Data and Computing Efficient Situational Assessment and Awareness in Human Assistance and Disaster Response and Battlefield Damage Assessment Applications -- 1 Introduction -- 2 Methodology -- 2.1 DDDAS -- 2.2 IP2CL -- 3 IP2CL Applications -- 3.1 IP2CL Applications in Semantic Segmentation -- 3.2 Patch-Based Damage Classification -- 4 Conclusion -- References -- SpecAL: Towards Active Learning for Semantic Segmentation of Hyperspectral Imagery -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Utilization -- 3.2 Neural Network Design -- 3.3 Acquisition Factor -- 4 Experiments and Results -- 4.1 Hyperparameters -- 4.2 Results -- 5 Conclusion -- References -- Multimodal IR and RF Based Sensor System for Real-Time Human Target Detection, Identification, and Geolocation -- 1 Introduction -- 2 System Architecture -- 2.1 RF Subsystem -- 2.2 IR Subsystem -- 2.3 Sensor System Integration -- 3 Experimental Results -- 4 Conclusion -- References -- Learning Interacting Dynamic Systems with Neural Ordinary Differential Equations -- 1 Introduction -- 2 Related Work -- 2.1 Neural Ordinary Differential Equations -- 2.2 Interacting Systems -- 3 Methodology -- 3.1 Problem Formulation and Notation -- 3.2 ISODE -- 4 Experiments -- 5 Conclusion -- References. Relational Active Feature Elicitation for DDDAS -- 1 Introduction -- 2 Interactive Feature Elicitation for DDDAS -- 2.1 Preliminary Results -- 3 Conclusion -- References -- Explainable Human-in-the-Loop Dynamic Data-Driven Digital Twins -- 1 Introduction -- 2 Background and Related Work -- 3 Motivating Example -- 4 A Reference Architecture for Explainable Digital Twins Leveraging DDDAS Principles -- 4.1 Explainable Decisions for Human-in-the-Loop Digital Twins -- 5 Discussion -- 5.1 Trade-Off Analysis -- 5.2 Architecture Evaluation -- 6 Conclusion -- References -- Plenary Presentations - Tracking -- Transmission Censoring and Information Fusion for Communication-Efficient Distributed Nonlinear Filtering -- 1 Introduction -- 2 Jeffreys Divergence Based Sensor Censoring -- 2.1 Jeffreys Divergence -- 2.2 Evaluation of Jeffreys Divergence -- 3 Estimation of Posterior PDFs via GMM -- 4 Fusion of Gaussian Mixtures -- 5 Numerical Results for a Radar Tracking Example -- 5.1 System Model -- 5.2 Performance Evaluation in a Two-Radar Network -- 6 Conclusion -- References -- Distributed Estimation of the Pelagic Scattering Layer Using a Buoyancy Controlled Robotic System -- 1 Introduction -- 2 Preliminary -- 2.1 Perron-Frobenius Operator -- 2.2 Ensemble Kalman Filter -- 3 Estimation of the Scattering Layer -- 4 Numerical Results -- 5 Conclusion -- References -- Towards a Data-Driven Bilinear Koopman Operator for Controlled Nonlinear Systems and Sensitivity Analysis -- 1 Introduction -- 2 Continuous Bilinear System Identification with Specialized Input -- 3 Numerical Simulations -- 3.1 Hovering Helicopter -- 3.2 Controlled Duffing Oscillator -- 4 Conclusion -- References -- Main-Track Plenary Presentations - Security -- Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach -- 1 Introduction -- 2 Problem Formulation and Algorithm. 3 Theoretical Result: Optimal Weight Sequence. |
| Record Nr. | UNISA-996587859803316 |
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Blasch Erik
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| Cham : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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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
| 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 |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (434 pages) |
| Disciplina | 005.7 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
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 |
| ISBN | 3-031-52670-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. -- . |
| Record Nr. | UNINA-9910841872703321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Dynamic Data Driven Applications Systems [[electronic resource] ] : Third International Conference, DDDAS 2020, Boston, MA, USA, October 2-4, 2020, Proceedings / / edited by Frederica Darema, Erik Blasch, Sai Ravela, Alex Aved
| Dynamic Data Driven Applications Systems [[electronic resource] ] : Third International Conference, DDDAS 2020, Boston, MA, USA, October 2-4, 2020, Proceedings / / edited by Frederica Darema, Erik Blasch, Sai Ravela, Alex Aved |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XIII, 360 p. 134 illus., 115 illus. in color.) |
| Disciplina | 004.6 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computers, Special purpose
Database management Artificial intelligence Computers Computer networks Computer systems Special Purpose and Application-Based Systems Database Management Artificial Intelligence Computing Milieux Computer Communication Networks Computer System Implementation |
| ISBN | 3-030-61725-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Digital Twins -- Environment Cognizant Adaptive-Planning Systems -- Energy Systems -- Materials Systems -- Physics-based Systems Analysis -- Imaging Methods and Systems -- Learning Systems. |
| Record Nr. | UNISA-996418208403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Dynamic Data Driven Applications Systems : Third International Conference, DDDAS 2020, Boston, MA, USA, October 2-4, 2020, Proceedings / / edited by Frederica Darema, Erik Blasch, Sai Ravela, Alex Aved
| Dynamic Data Driven Applications Systems : Third International Conference, DDDAS 2020, Boston, MA, USA, October 2-4, 2020, Proceedings / / edited by Frederica Darema, Erik Blasch, Sai Ravela, Alex Aved |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XIII, 360 p. 134 illus., 115 illus. in color.) |
| Disciplina | 004.6 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computers, Special purpose
Database management Artificial intelligence Computers Computer networks Computer systems Special Purpose and Application-Based Systems Database Management Artificial Intelligence Computing Milieux Computer Communication Networks Computer System Implementation |
| ISBN | 3-030-61725-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Digital Twins -- Environment Cognizant Adaptive-Planning Systems -- Energy Systems -- Materials Systems -- Physics-based Systems Analysis -- Imaging Methods and Systems -- Learning Systems. |
| Record Nr. | UNINA-9910427676003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||