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- Type:
- Generic Work
- Description/Abstract:
- Data and replication package of the paper entitled, "Metamorphic Relation Construction: How Do Scientific Software Developers Do It?"
- Creator/Author:
- Peng, Zedong; Niu, Nan, and Kanewala, Upulee
- Submitter:
- Nan Niu
- Date Uploaded:
- 03/09/2023
- Date Modified:
- 03/09/2023
- Date Created:
- 2023-03-09
- License:
- Open Data Commons Open Database License (ODbL)
-
- Type:
- Document
- Description/Abstract:
- This dataset details the force-displacement response of porcine meniscus under tensile-fracture behavior. Samples are cut from the anterior, middle and posterior regions of the meniscus. Each specimen geometry dimension is included.
- Creator/Author:
- Chia-Ying Lin; Kumar Vemaganti, and Long, Teng
- Submitter:
- Teng Long
- Date Uploaded:
- 03/03/2023
- Date Modified:
- 03/03/2023
- Date Created:
- 2020-11
- License:
- Attribution 4.0 International
-
- Type:
- Dataset
- Description/Abstract:
- Data from qualitative study "Employing Strategies to Address Implicit Racial Bias in the Home Visit Setting" Includes: written reflections by FM residents, resident focus group data, commitments-to-change, and 3-month follow up survey data
- Creator/Author:
- Goroncy, Anna
- Submitter:
- Anna Goroncy
- Date Uploaded:
- 03/03/2023
- Date Modified:
- 03/03/2023
- Date Created:
- 2020-01
- License:
- Open Data Commons Attribution License (ODC-By)
-
- Type:
- Document
- Description/Abstract:
- An exploration of the use of virtual reality technology in the context of diversity and inclusion training. This manuscript describes two studies: Study 1 was longitudinal and investigated the impacts of a VR-based bias training. Cognitive and affective empathy levels and impact on behavior, attitude, and knowledge before and after the training were measured to test the hypotheses that (H1) cognitive empathy levels would increase and (H2) individuals with higher initial levels of empathy would demonstrate more pronounced changes in cognitive empathy following the training. H1 was supported but larger changes were found in affective empathy levels. H2 was also supported as individuals with higher initial empathy levels showed higher levels of cognitive empathy after the training compared to individuals with lower initial empathy levels. However, again, larger differences were found in affective empathy levels. Qualitative data revealed a lasting impact nine weeks after the training that was not present in the quantitative data. Study 2 surveyed healthcare professionals who previously participated in a VR-based DEI training that focused on social determinants of health and empathy in healthcare professionals. The purpose of this study was to gain insight into the longitudinal impacts of a VR-based DEI training by gathering qualitative data from the participants at least a year after they went through the training. The respondents reported a lasting influence from the training. Reasons for the discrepancy between the qualitative and quantitative results are discussed as are implications for organizations and future DEI training development and research.
- Creator/Author:
- Mason, Lauren
- Submitter:
- Lauren Mason
- Date Uploaded:
- 02/08/2023
- Date Modified:
- 02/08/2023
- Date Created:
- 2022
- License:
- Attribution 4.0 International
-
- Type:
- Dataset
- Description/Abstract:
- The Dataset contains raw data that indicates the start and stop time of water flowing at fixtures in the Marian Spencer Hall Cafeteria restroom during hours of operation. The data were collected as part of an effort to develop and test a novel method of measuring flow to calculate the probability that the fixture is busy (fixture p-value). The fixture p-value is one of the parameters necessary to predict peak demand in buildings for pipe sizing purposes. There are two .csv files, a README file and a sample of the data collection template with contact information. The dataset also contains a MATLAB code written to accept data in the suggested format and estimate the fixture probability of use.
- Creator/Author:
- Choudhary, Chandrashekhar ; Omaghomi, Toju; Buchberger, Steven; Wang, Tianshuo, and Tao, Li
- Submitter:
- Toju Omaghomi
- Date Uploaded:
- 12/19/2022
- Date Modified:
- 12/19/2022
- Date Created:
- 2022-12
- License:
- Open Data Commons Open Database License (ODbL)
-
- Type:
- Generic Work
- Description/Abstract:
- Aurek Chattopadhyay, Reagan Maddox, Glen Horton, Nan Niu, Ganesh Malla, Tanmay Bhowmik, Jianzhang Zhang, and Juha Savolainen, Completeness of Natural Language Requirements: A Comparative Study of User Stories and Feature Descriptions (submitted to REFSQ 2023: https://2023.refsq.org)
- Creator/Author:
- Chattopadhyay, Aurek and Niu, Nan
- Submitter:
- Aurek Chattopadhyay
- Date Uploaded:
- 11/21/2022
- Date Modified:
- 11/21/2022
- License:
- Open Data Commons Public Domain Dedication and License (PDDL)
-
- Type:
- Dataset
- Description/Abstract:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- Creator/Author:
- McCabe, Erin E.
- Submitter:
- Erin E. McCabe
- Date Uploaded:
- 11/12/2022
- Date Modified:
- 11/12/2022
- Date Created:
- 2022
- License:
- Open Data Commons Attribution License (ODC-By)
-
- Type:
- Dataset
- Description/Abstract:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- Creator/Author:
- McCabe, Erin E.
- Submitter:
- Erin E. McCabe
- Date Uploaded:
- 11/12/2022
- Date Modified:
- 11/12/2022
- Date Created:
- 2022
- License:
- Open Data Commons Attribution License (ODC-By)
-
- Type:
- Dataset
- Description/Abstract:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- Creator/Author:
- McCabe, Erin E.
- Submitter:
- Erin E. McCabe
- Date Uploaded:
- 11/12/2022
- Date Modified:
- 11/12/2022
- Date Created:
- 2022
- License:
- Open Data Commons Attribution License (ODC-By)
-
- Type:
- Dataset
- Description/Abstract:
- CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
- Creator/Author:
- McCabe, Erin E.
- Submitter:
- Erin E. McCabe
- Date Uploaded:
- 11/12/2022
- Date Modified:
- 11/12/2022
- Date Created:
- 2022
- License:
- Open Data Commons Attribution License (ODC-By)