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Found 1168 dataset(s) matching "work sampling".
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Definition of terms used in manuscript's technical descriptions, tables and figure. This dataset is associated with the following publication: Wroble, J., T. Frederick, A. Frame, and D. Vallero....
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This table contains an all-sky sample of ~1.4 million active galactic nuclei (AGNs) meeting a two-color infrared photometric selection criterion for AGNs as applied to sources from the Wide-field...
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The dataset documents results from particle size analysis (PSA) and portable X-ray fluorescence (pXRF) analysis conducted on a suite of sediment samples from U.S. Army Base Fort Drum, Jefferson...
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Understanding the relationship between stress state, strain state and fracture initiation and propagation is critical to the improvement of fracture simulation capability if it is to be used as a...
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This metadata record document contains 7 tables used to assess factors influencing long-term water quality changes in the Gwynns Falls, Baltimore, MD, 1998-2016. Included are daily discharge...
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These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed...
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Data for Artificial Intelligence: Data-Centric AI for Transportation: Work Zone Use Case proposes a data integration pipeline that enhances the utilization of work zone and traffic data from...
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<p dir="ltr">Two .csv files: Metadata and Master Data. The Metadata describes column variables for the Master Data file that contains all of the information used in the analyses. This project...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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nv_lvl1_finescale: Nevada hierarchical cluster level 1 (fine-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the...
