Search Constraints
« Previous |
1 - 10 of 289
|
Next »
Number of results to display per page
View results as:
Search Results
-
- Creator:
- Foltynek, Tomas, Ruas, Terry, Scharpf, Philipp , Meuschke, Norman, Schubotz, Moritz , Grosky, William , and Gipp, Bela
- Description:
- This data set is comprised of multiple folders. The corpus folder contains raw text used for training and testing in two splits, "document" and "paragraph". The Spun documents and paragraphs are generated using the SpinBot tool ( https://spinbot.com/API). The paragraph split is generated by only selecting paragraphs with 3 or more sentences in the document split. Each folder is divided in mg (i.e., machine generated through SpinBot) and og (i.e., original generated file), The human judgement folder contains the human evaluation between original and spun documents (sample). It also contains the answers (keys) and survey results. , The models folder contains the machine learning classifier models for each word embedding technique used (only for document split training). The models were exported using pickle (Python 3.6). The grid search for hyperparameter adjustments is described in the paper. , and The vector folders (train and test) contains the average of all word vectors for each document and paragraph. Each line has the number of dimensions of the word embeddings technique used (see paper for more details) followed by its respective class (i.e, label mg or og). Each file belong to one class, either "mg" or "og". The values are comma-separated (.csv). The extension is .arff can be read as a normal .txt file.
- Keyword:
- paraphrase detection, plagiarism detection, document classification, and word embeddings
- Citation to related publication:
- Discipline:
- General Information Sources
- Title:
- Detecting Machine-obfuscated Plagiarism
-
- Creator:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research
- Description:
- Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler, http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015., More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015: https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/, and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Discipline:
- Engineering and Science
- Title:
- Large Lake Statistical Water Balance Model - Laurentian Great Lakes - 1 month time window - 1980 through 2015 monthly summary data and model output
-
- Creator:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research
- Description:
- Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler, http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015., More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015: https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/ , and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Discipline:
- Engineering and Science
- Title:
- Large Lake Statistical Water Balance Model - Laurentian Great Lakes - 6 month time window - 1980 through 2015 monthly summary data and model output
-
- Creator:
- Bustamante, Angela C., Opron, Kristopher, Ehlenbach, William J., Crane, Paul K., Keene, Dirk, Standiford, Theodore J., and Singer, Benjamin H.
- Description:
- This study was conducted to detect and analyze modules, or clusters of genes, associated with sepsis, using RNAseq data obtained from 12 participants who died of sepsis and 12 participants who died of non-infectious critical illness while hospitalized. This deposit contains the input data and parameters needed to reproduce the weighted gene co-expression network analysis (WGCNA) and gene enrichment analysis performed on this data. This analysis requires the R packages "WGCNA" version 1.68 and "DESeq2" version 1.22.2 available for download from bioconductor ( http://bioconductor.org). The external bioinformatics tool DAVID version 6.8 ( https://david.ncifcrf.gov/) was used as an additional gene enrichment analysis. Please see the supplemental methods document within this deposit and published research letter for more detailed information.
- Keyword:
- Sepsis, RNAseq, Transcriptomics, Human, and Brain
- Citation to related publication:
- Discipline:
- Science
- Title:
- Transcriptomic Profiles of Sepsis in the Human Brain
-
- Creator:
- Niemi, Nathan A. and Abbey, Alyssa L.
- Description:
- These data were produced in the scope of research into the timing, rate, and magnitude of extensional exhumation along the length of the Rio Grande Rift in Colorado and New Mexico. The low-temperature (apatite and zircon (U-Th)/He) thermochronometric ages presented in this data set are sensitive to near-surface temperatures (~80C and 180C, respectively) and record the progressive exhumation of the rock mass from which the samples were collected towards the Earth's surface. These thermochronometric ages, and the differences between them, provide insight into the absolute timing, exhumation rate and total magnitude of exhumation on the normal faults that bound the Rio Grande Rift. and The QTQt program mentioned (Version QTQt64R5.6.2a was used for the data presented in this deposit) is not openly available for download, but is described in the Gallagher 2012 publication referenced, and can be requested from its author. For more information on the request process and a user guide, see http://www.iearth.org.au/codes/QTQt/
- Keyword:
- thermochronology, helium dating, (U-Th)/He, Rio Grande Rift, New Mexico, Colorado, and extensional tectonics
- Citation to related publication:
- Abbey, A. L. and Niemi, N. A., in press, Perspectives on continental rifting processes from spatiotemporal patterns of faulting and magmatism in the Rio Grande rift, USA: Tectonics
- Discipline:
- Science
- Title:
- Dataset of apatite and zircon (U-Th)/He thermochronologic analyses from the Rio Grande Rift, Colorado and New Mexico, USA to accompany Abbey and Niemi, 2019, Tectonics.
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:mammals:124092 (Phyllops falcatus) - WholeBody. Raw - Dataset includes 1601 TIF images (each 1085 x 1386 x 1 voxel at 0.0328326086085239 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:mammals:124092 (Phyllops falcatus) - WholeBody. Reconstructed - Dataset includes 2000 TIF images (each 1085 x 1386 x 1 voxel at 0.032833 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Mammalia, Chiroptera, Phyllostomidae, Phyllops falcatus, 1987339099, computed tomography, X-ray, and 3D
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1987339099
- Discipline:
- Science
- Title:
- Computed tomography voxel dataset for ummz:mammals:124092-Phyllops falcatus-WholeBody
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:herps:246849 (THAMNODYNASTES PALLIDUS) - Skull. Raw - Dataset includes 1601 TIF images (each 1416 x 914 x 1 voxel at 0.0150099083890765 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:herps:246849 (THAMNODYNASTES PALLIDUS) - Skull. Reconstructed - Dataset includes 654 TIF images (each 1416 x 914 x 1 voxel at 0.015010 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Reptilia, OPHIDIA, COLUBRIDAE, THAMNODYNASTES PALLIDUS, 1987213257, computed tomography, X-ray, and 3D
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1987213257
- Discipline:
- Science
- Title:
- Computed tomography voxel dataset for ummz:herps:246849-THAMNODYNASTES PALLIDUS-Skull
-
- Creator:
- University of Michigan Museum of Zoology
- Description:
- Scan of specimen ummz:herps:246849 (THAMNODYNASTES PALLIDUS) - WholeBody. Raw - Dataset includes 1601 TIF images (each 2000 x 2000 x 1 voxel at 0.0327439804971583 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction. and Scan of specimen ummz:herps:246849 (THAMNODYNASTES PALLIDUS) - WholeBody. Reconstructed - Dataset includes 1240 TIF images (each 2000 x 2000 x 1 voxel at 0.032744 mm resolution, derived from 1601 scan projections), xtek and vgi files for volume reconstruction.
- Keyword:
- Animalia, Chordata, Reptilia, OPHIDIA, COLUBRIDAE, THAMNODYNASTES PALLIDUS, 1987213257, computed tomography, X-ray, and 3D
- Citation to related publication:
- For more information on the original UMMZ specimen, see: https://www.gbif.org/occurrence/1987213257
- Discipline:
- Science
- Title:
- Computed tomography voxel dataset for ummz:herps:246849-THAMNODYNASTES PALLIDUS-WholeBody
-
- Creator:
- Smith, Joeseph P., Gronewold, Andrew D., Read, Laura, Crooks, James L., School for Environment and Sustainability, University of Michigan, Department of Civil and Environmental Engineering, University of Michigan, and Cooperative Institute for Great Lakes Research, University of Michigan
- Description:
- Using the statistical programming package R ( https://cran.r-project.org/), and JAGS (Just Another Gibbs Sampler, http://mcmc-jags.sourceforge.net/), we processed multiple estimates of the Laurentian Great Lakes water balance components -- over-lake precipitation, evaporation, lateral tributary runoff, connecting channel flows, and diversions -- feeding them into prior distributions (using data from 1950 through 1979), and likelihood functions. The Bayesian Network is coded in the BUGS language. Water balance computations assume that monthly change in storage for a given lake is the difference between beginning of month water levels surrounding each month. For example, the change in storage for June 2015 is the difference between the beginning of month water level for July 2015 and that for June 2015., More details on the model can be found in the following summary report for the International Watersheds Initiative of the International Joint Commission, where the model was used to generate a new water balance historical record from 1950 through 2015: https://www.glerl.noaa.gov/pubs/fulltext/2018/20180021.pdf. Large Lake Statistical Water Balance Model (L2SWBM): https://www.glerl.noaa.gov/data/WaterBalanceModel/, and This data set has a shorter timespan to accommodate a prior which uses data not used in the likelihood functions.
- Keyword:
- Water, Balance, Great Lakes, Laurentian, Machine Learning, Machine, Learning, Lakes, Bayesian, and Network
- Citation to related publication:
- Discipline:
- Engineering and Science
- Title:
- Large Lake Statistical Water Balance Model - 12 month time window - 1980 through 2015 monthly summary data and model output
-
- Creator:
- Tye, Alexander R, Niemi, Nathan A, Safarov, Rafig T, Kadirov, Fakhraddin A, Babayev, Gulam R
- Description:
- Apatite fission track thermochronometry data were collected from the Eastern Greater Caucasus orogen, Azerbaijan. Thermochronometry data constrain the history of exhumation and deformation of rocks within the orogen, which is an active accretionary prism. Thermochronometry data record the timing of cooling of a rock sample beneath a given closure temperature. Given an assumed or inferred geothermal gradient, thermochronometric ages can be used to infer exhumation rates and make interpretations about rates of deformation in orogens. The apatite fission track data presented here are analyzed in concert with apatite (U-Th)/He and zircon (U-Th)/He ages reported in Tye et al., in prep., to characterize the exhumation history of the Eastern Greater Caucasus.
- Keyword:
- thermochronometry, apatite fission track, Caucasus
- Citation to related publication:
- Tye, A. R., Niemi, N. A., Safarov, R. T., Kadirov, F. A., and Babayev, G. R., Structural and thermochronometric data provide insight into strain accommodation within an active accretionary prism, the Eastern Greater Caucasus. In prep.
- Discipline:
- Science
- Title:
- Apatite fission track thermochronometry data from the Eastern Greater Caucasus, Azerbaijan