1 - 10 of 17 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.
Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.
We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.
Due to a genes unique nucleotide sequences acquired through horizontal gene transfer, the gene has a transcriptional repressor activity and innate enzymatic role.
Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).