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09/06/2023
Expert Uncertainty and Severity Aware Chest X-Ray Classification by Multi-Relationship Graph Learning
Patients undergoing chest X-rays (CXR) often endure multiple lung diseas...
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08/15/2023
Potential of Deep Operator Networks in Digital Twin-enabling Technology for Nuclear System
This research introduces the Deep Operator Network (DeepONet) as a robus...
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07/22/2023
Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering
To contribute to automating the medical vision-language model, we propos...
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03/07/2023
Sketch-based Medical Image Retrieval
The amount of medical images stored in hospitals is increasing faster th...
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02/19/2023
Interpretable Medical Image Visual Question Answering via Multi-Modal Relationship Graph Learning
Medical visual question answering (VQA) aims to answer clinically releva...
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01/17/2023
Operator Learning Framework for Digital Twin and Complex Engineering Systems
With modern computational advancements and statistical analysis methods,...
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01/17/2023
Explainable, Interpretable Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life
Machine learning (ML) and Artificial Intelligence (AI) are increasingly ...
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11/24/2022
Non-Intrusive Uncertainty Quantification for U3Si2 and UO2 Fuels with SiC/SiC Cladding using BISON for Digital Twin-Enabling Technology
U.S. Nuclear Regulatory Committee (NRC) and U.S. Department of Energy (D...
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11/23/2022
Physics-Informed Multi-Stage Deep Learning Framework Development for Digital Twin-Centred State-Based Reactor Power Prediction
Computationally efficient and trustworthy machine learning algorithms ar...
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10/14/2022
Uncertainty Quantification and Sensitivity analysis for Digital Twin Enabling Technology: Application for BISON Fuel Performance Code
To understand the potential of intelligent confirmatory tools, the U.S. ...
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10/14/2022
Reliability-Based Robust Design Optimization Method for Engineering Systems with Uncertainty Quantification
Robust optimization is a method for optimization under uncertainties in ...
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10/13/2022
Surrogate Modeling-Driven Physics-Informed Multi-fidelity Kriging: Path Forward to Digital Twin Enabling Simulation for Accident Tolerant Fuel
The Gaussian Process (GP)-based surrogate model has the inherent capabil...
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10/13/2022
Data-driven multi-scale modeling and robust optimization of composite structure with uncertainty quantification
It is important to accurately model materials' properties at lower lengt...
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09/30/2022
Leveraging Industry 4.0 – Deep Learning, Surrogate Model and Transfer Learning with Uncertainty Quantification Incorporated into Digital Twin for Nuclear System
Industry 4.0 targets the conversion of the traditional industries into i...
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09/25/2022
Machine Learning and Artificial Intelligence-Driven Multi-Scale Modeling for High Burnup Accident-Tolerant Fuels for Light Water-Based SMR Applications
The concept of small modular reactor has changed the outlook for tacklin...
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03/23/2021
Decomposing Normal and Abnormal Features of Medical Images into Discrete Latent Codes for Content-Based Image Retrieval
In medical imaging, the characteristics purely derived from a disease sh...
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11/12/2020
Decomposing Normal and Abnormal Features of Medical Images for Content-based Image Retrieval
Medical images can be decomposed into normal and abnormal features, whic...
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05/26/2020