3,160 research outputs found

    Data for: Classification methods for point clouds in rock slope monitoring: a novel machine learning approach and comparative analysis

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    Data for the following submission: Title: Classification methods for point clouds in rock slope monitoring: a novel machine learning approach and comparative analysis Weidner, L.1*, Walton, G.1, Kromer, R.1 1Colorado School of Mines, Golden, USA *Corresponding author email: [email protected] In the event the manuscript is unavailable, please reach out to us for a copy. The main contents of this file are as follows: -Supplementary figures referenced in the manuscript -All processed point clouds used in the through-time analysis. (~9.3 GB) -Scripts used to calculate the results shown in Figures 11, 12 and 13. (~1.6 GB) -Numeric data in other tables, graphs, and figures. Due to the nature of the research, many large point clouds are created, too many to be all uploaded to this repository. If you are looking for data that is not provided in this dataset, please reach out to the authors and we would be happy to provide any additional data. Scripts labeled "RUNME" are found in the main file directory for creating the ML method results ('tests_RUNME.m'), and for hybrid and masking results. For the most part, scripts can be run without modification and should provide results (assuming the required MATLAB toolboxes are installed) Note that for hybrid and masking, multiple runs of the script are required, changing the filenames at the beginning of the script for each of the four dates calculated. The Random Forest TreeBagger object ('tb_t14_jun16dec18') is also included and all the feature sets used for training and validation ('date_struct.mat')

    Data for: A Hybrid Random Forest Algorithm for Accurate Multi-Feature Point Cloud Classification of Rock Slopes

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    Data for the following submission:Title: A Hybrid Random Forest Algorithm for Accurate Multi-Feature Point Cloud Classification of Rock SlopesWeidner, L.1*, Walton, G.1, Kromer, R.11Colorado School of Mines, Golden, USA*Corresponding author email: [email protected] the event the manuscript is unavailable, please reach out to us for a copy.The main contents of this file are as follows:-All processed point clouds used in the through-time analysis. (~9.3 GB)-Scripts used to calculate the results shown in Figures 11, 12 and 13. (~1.6 GB)-Numeric data in other tables, graphs, and figures.Due to the nature of the research, many large point clouds are created, too many to be all uploaded to this repository.If you are looking for data that is not provided in this dataset, please reach out to the authors and we would be happy to provide any additional data.Scripts labeled "RUNME" are found in the main file directory for creating the ML method results ('tests_RUNME.m'), and for hybrid and masking results. For the most part, scripts can be run without modification and should provide results (assuming the required MATLAB toolboxes are installed)Note that for hybrid and masking, multiple runs of the script are required, changing the filenames at the beginning of the script for each of the four dates calculated.The Random Forest TreeBagger object ('tb_t14_jun16dec18') is also included and all the feature sets used for training and validation ('date_struct.mat')

    First person – Jacqueline Weidner

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    First Person is a series of interviews with the first authors of a selection of papers published in Biology Open (BiO), helping early-career researchers promote themselves alongside their papers. Jacqueline Weidner is first author on ‘Hormones as adaptive control systems in juvenile fish’, published in BiO. Jacqueline conducted the research described in this article while a PhD student at the University of Bergen, Norway. She is now an assistant professor at the Western Norway University of Applied Sciences, Norway, investigating sexual selection and modelling of evolutionary patterns

    GHG modeling & analysis tools

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    principal authors: Alex Bettinardi, P.E. and Tara Weidner, P.E.Title from PDF cover (viewed on November 20, 2018).Covers OCLC #1066694554.This archived document is maintained by the State Library of Oregon as part of the Oregon Documents Depository Program. It is for informational purposes and may not be suitable for legal purposes.Includes bibliographical references.Funded in part by the Federal Highway Administration, U.S. Department of Transportation.Mode of access: Internet from the Oregon Government Publications Collection.Text in English
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