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A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.
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.
Water heaters and heating, ventilation, and air conditioning (HVAC) systems collectively consume about 58% of home energy use.
MAPSTER is a lightweight software package that automatically searches deployed laptops for geospatial data and complies metadata (GPS coordinates, file size, etc) at a central checkpoint.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.