TreeMap 2016 Stand Size Code Algorithm (Image Service) by U.S. Forest Service (17476914)

“…format=iso19139 "> ISO-19139 metadata</a></li><li> <a href="https://data-usfs.hub.arcgis.com/datasets/usfs::treemap-2016-stand-size-code-algorithm-image-service "> ArcGIS Hub Dataset</a></li><li> <a href="https://apps.fs.usda.gov/fsgisx01/rest/services/RDW_ForestEcology/TreeMap_2016_StandSizeCode_Algorithm/ImageServer "> ArcGIS GeoService</a></li></ul><div> For complete information, please visit <a href="https://data.gov">https://data.gov</a>.…”

Comparison of federated learning algorithms. by Duy-Dong Le (22057362)

The_Code_for_High_Order_Analytical_Continuation by Jian Ma (19747060)

“…Additionally, formulae for the first through sixth-order radial derivatives are also derived by a recursive method. Numerical test in a mountain area reveals theoretical defects exist in the high-order radical derivatives based on the direct derivation method, whereas the recursive method proves to be effective and practical. …”

Element model generation method with geometric distribution errors by Yiqi Liu (21357815)

“…The product surface geometric distribution error is directly attached to the element nodes of the product ideal element model using the error surface reconstruction method and the replacement algorithm of the element node vector height based on the product’s point cloud data. …”

S1 Data - A GNSS receiver positioning algorithm based on weighting the statistical properties of discontinuous signals at lower rotation speeds by Jiahui Gan (22793753)

“…Weighted Kalman Filter Algorithm in C Code. S3 File. NavSolveKalman.h. Weighted Kalman Filter Algorithm in C Code. …”

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

The CGO risk prediction process based on data augmentation and neuroevolution. by Wenbing Shi (5806160)

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Reported MATLAB data code. by Jotham Josephat Kimondo (19139409)

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Comparative analysis of spike sorting using Uniform Manifold Approximation and Projection (UMAP) vs. feature-based methods in in vivo extracellular recordings. by Daniel Suárez-Barrera (22676654)

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G R code algorithm. by R. Sakthivel (2589547)

“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”

Coding schematic. by Dongyan Wang (195482)

“…By comparing the fitting performance of several methods, including ZOA-LSSVM, Genetic Algorithm (GA)-LSSVM, LSSVM, and Least Squares Regression (LSR), the effectiveness of ZOA-LSSVM is validated. …”

The errors of the predictions based on different algorithm methods. by Zhang Wei (317854)

“…<p>The errors of the predictions based on different algorithm methods.</p>…”

Computation time as a function of the sample size on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

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Computation time as a function of the sample size on the random graph dataset. by Tomokaze Shiratori (9635271)

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F1 score of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

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Examples of ground-truth graph structures with (<i>p</i>, <i>n</i>_≠0) = (10, 10). by Tomokaze Shiratori (9635271)

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Number of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

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Number of edges selected through cross-validation on the random graph dataset. by Tomokaze Shiratori (9635271)

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