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making algorithm » learning algorithm (Expand Search), finding algorithm (Expand Search), means algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
elements making » elements during (Expand Search), element mapping (Expand Search), elemental mapping (Expand Search)
complement td3 » complement c3 (Expand Search), complement _ (Expand Search), complement low (Expand Search)
td3 algorithm » cc3d algorithm (Expand Search), _ algorithm (Expand Search), ii algorithm (Expand Search)
level coding » level according (Expand Search), level modeling (Expand Search), level using (Expand Search)
making algorithm » learning algorithm (Expand Search), finding algorithm (Expand Search), means algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), modeling algorithm (Expand Search), finding algorithm (Expand Search)
elements making » elements during (Expand Search), element mapping (Expand Search), elemental mapping (Expand Search)
complement td3 » complement c3 (Expand Search), complement _ (Expand Search), complement low (Expand Search)
td3 algorithm » cc3d algorithm (Expand Search), _ algorithm (Expand Search), ii algorithm (Expand Search)
level coding » level according (Expand Search), level modeling (Expand Search), level using (Expand Search)
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181
Video 1_A hybrid elastic-hyperelastic approach for simulating soft tactile sensors.mp4
Published 2025“…A significant challenge for simulating tactile sensors is balancing the trade-off between accuracy and processing time in simulation algorithms and models. To address this, we propose a hybrid approach that combines elastic and hyperelastic finite element simulations, complemented by convolutional neural networks (CNNs), to generate synthetic tactile maps of a soft capacitive tactile sensor. …”
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182
Data Sheet 1_Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model.docx
Published 2025“…Considering the increased detection range of EDARM and the requirements for computational efficiency, this paper presents a 2.5-dimensional (2.5D) finite element method (FEM). By leveraging the symmetry of simulated signals in the spectral domain, the algorithm reduces computation time by 50%, significantly enhancing computational efficiency while preserving accuracy. …”
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183
Fire Lab tree list: A tree-level model of the conterminous United States landscape circa 2014
Published 2025“…Forest Service’s Forest and Inventory Analysis program (FIA) version 1.7.1 and 2) the landscape target data, which consisted of raster data at 30x30 meter (m) resolution provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE; https://landfire.gov/) FIA plots were imputed to the raster data by the random forests algorithm, providing a tree-level model of all forested areas in the conterminous U.S. …”
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TreeMap 2020 CONUS: A tree-level model of the forests of the conterminous United States circa 2020
Published 2025“…The raster of plot identifiers can be linked to the FIA databases available through the FIA DataMart to map hundreds of attributes available there, or to the comma-separated file included in this data publication to access a more limited set of tree-level attributes. The data files included in this publication also contain attributes for each tree in the plots that were assigned, including the FIA plot PLT_CN for the plot on which the tree was measured (or control number, a unique identifier for each time a plot is measured), the subplot number, the tree record number, the corresponding number of trees per acre it represents due to the study design, the status (live or dead), species, diameter, height, actual height (where broken), crown ratio and a code for cause of death where applicable. …”
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186
TreeMap 2022 CONUS: A tree-level model of the forests of the conterminous United States circa 2022
Published 2025“…The raster of plot identifiers can be linked to the FIA databases available through the FIA DataMart to map hundreds of attributes available there, or to the comma-separated file included in this data publication to access a more limited set of tree-level attributes. The data files included in this publication also contain attributes for each tree in the plots that were assigned, including the FIA plot PLT_CN for the plot on which the tree was measured (or control number, a unique identifier for each time a plot is measured), the subplot number, the tree record number, the corresponding number of trees per acre it represents due to the study design, the status (live or dead), species, diameter, height, actual height (where broken), crown ratio and a code for cause of death where applicable. …”
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