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Managing beetles that infest stored products is crucial for reducing losses in harvest supply chains and improving food security and safety. Successful pest management programs require effective...
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Ensuring consistent bread quality is vital for maintaining industry standards, reducing waste, and keeping consumer satisfaction. Traditional methods of bread quality analysis which rely on manual...
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The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods that provide consistent and accurate real-time knowledge of system states from...
Search relevance: 1.00 | Views last month: 7 | Catalog Last Checked: September 10, 2026 at 05:52 PM -
Data from: Efficient imaging and computer vision detection of two cell shapes in young cotton fibers
Methods Cotton plants were grown in a well-controlled greenhouse in the NC State Phytotron as described previously (Pierce et al, 2019). Flowers were tagged on the day of anthesis and harvested...
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This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a...
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The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design...
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This dataset catalogs a long-term high-resolution data set characterizing the near-surface hourly wind speed variations at two solar sites in the Southwest U.S. This dataset demonstrates the...
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Machine learning (ML) models were used to forecast streamflow drought from 1 to 13 weeks into the future at more than 3,000 streamgage locations across the conterminous United States. Long...
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Classified map of crop types in California's Central Valley generated using artificial neural network multilayer perceptron models and Harmonized Landsat-8 Sentinel-2 Landsat 30m (HLSL30) data....
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We applied machine learning (ML) models to forecast streamflow drought from 1 to 13 weeks into the future at more than 3,000 streamgage locations across the Conterminous United States. We applied...
Search relevance: 1.00 | Views last month: 1 | Catalog Last Checked: September 10, 2026 at 09:48 PM -
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission...
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This data matrix contains the codebook vectors for a 82 x 50 neuron Emergent Self-Organizing Map which describes the multivariate topology of reservoir temperature and geochemical data for 190...
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This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany...
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This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir...
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