Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This data set contains the research data for the master's thesis: Integrating Explainability into Federated Learning: A Non-functional Requirement Perspective. The master's thesis was written by Nicolas Sebastian Schuler at the Computer Science Department at Karlsruhe Institute for Technology (KIT) in Germany. The data set contains: - Associate Jupyter notebooks for reproducing the figures in the master's thesis. - Generated experiment data by the federated learning simulations. - Results of the user survey conducted for the master's thesis. - Used Python Libraries. It also includes the submitted final thesis. Notice: The research data is split into multiple chunks and can be combined via the following command after downloading: $ cat thesis-results-part-* > thesis-results.tar.zst and extracted via: $ tar --zstd -xvf thesis-results.tar.zst
This dataset provides information about the number of properties, residents, and average property values for Harvard Street cross streets in Cleveland, MS.
GC-MS data files for the analysis of fly cuticular hydrocarbons
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Data on Leadership skills and qualities developed by master degree students
1000 simulated data sets stored in a list of R dataframes used in support of Reisetter et al. (submitted) 'Mixture model normalization for non-targeted gas chromatography / mass spectrometry metabolomics data'. These are results after normalization using mean centering as described in Reisetter et al.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This study is an assessment of the dataverse network with regard to its effectiveness in GC/MS data.
1000 simulated data sets stored in a list of R dataframes used in support of Reisetter et al. (submitted) 'Mixture model normalization for non-targeted gas chromatography / mass spectrometry metabolomics data'. These are simulated data sets that include batch effects and data truncation and are not yet normalized.
Data for manuscript: EEG Theta/Beta Ratio Neurofeedback Training in Healthy Females See ReadMe file for detailed description
Data is in txt or CSV format Can be opened with MS XCEL or any statistical software such as STATA or STAT transfer
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
1000 simulated data sets stored in a list of R dataframes used in support of Reisetter et al. (submitted) 'Mixture model normalization for non-targeted gas chromatography / mass spectrometry metabolomics data'. These are results after normalization using quantile + ComBat (Johnson et al. 2007).
The master crosswalk file maps U.S. ZIP codes to their respective ZIP Code Tabulation Areas (ZCTAs), capturing the discrepancies and characteristics of the ZIP-ZCTA relationships across the different yearly UDS crosswalks. ZCTAs allow for consistent analysis over time while accommodating changes in the underlying ZIP Code system and geographic boundaries. It helps ensure that researchers and policymakers are working with data that accurately reflects the geographic realities of their study period.
https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.6/customlicense?persistentId=doi:10.7910/DVN/573BWWhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.6/customlicense?persistentId=doi:10.7910/DVN/573BWW
The Pre-1990 HMDA Aggregation Data were prepared annually during this period by the FFIEC on behalf of institutions reporting HMDA data. The Aggregation Data consists of home purchase and home improvement loans that a depository institution originated or purchased during each calendar year. The collected HMDA data were individually aggregated up to the tract level by the reporting depository institution and submitted accordingly to the FFIEC. Individual records are the summary of loan activity for the specified respondent for the indicated census tract except when the census tract numbers were either 888888 or 999999. The 888888 tract records are the sum of all loan activity by the reporter outside of the MSA being reported, but not appearing in any other MSA report. The 999999 tract records are the consolidated county summary data for loans made in untracted counties or counties with 1980 total population less than 30,000. The 1988 and 1989 Aggregation Data files include aggregated data from nondepository institutions, specifically mortgage banking subsidiaries of bank holding companies.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The Exempt Organization Business Master File Extract (EO BMF) includes cumulative information on exempt organizations. The data are extracted monthly and are available by state and region. https://www.irs.gov/charities-non-profits/exempt-organizations-business-master-file-extract-eo-bmf https://github.com/lecy/Open-Data-for-Nonprofit-Research/blob/master/Build_Datasets/master_exempt_list_w_ntee.Rmd
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Replication Data for Internal Migration and Labor Market Outcomes in Indonesia Please follow the instructions in the Read Me document.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Supplementary data files for the MS "Senescent cells and the incidence of age-related diseases" submitted to Aging Cell.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This file contains the replication data and Stata codes to replicate the results in Baskaran, T. and Z. Hessami (2023). Women in Political Bodies as Policymakers. Review of Economics and Statistics. MS 26114.
https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/VCXPUDhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/VCXPUD
The Record of American Democracy (ROAD) data provide election returns, socioeconomic summaries, and demographic details about the American public at unusually low levels of geographic aggregation. The NSF-supported ROAD project spans every state in the country from 1984 through 1990 (including some off-year elections). These data enable research on topics such as electoral behavior, the political characteristics of local community context, electoral geography, the role of minority groups in elections and legislative redistricting, split ticket voting and divided government, and elections under federalism. Another set of files has added to these roughly 30-40 political variables an additional 3,725 variables merged from the 1990 United States Census for 47,327 aggregate units called MCD Groups. The MCD Group is a construct for purposes of this data collection. It is based on a merging of the electoral precincts and Census Minor Civil Divisions (MCDs). An MCD is about the size of a city or town. An MCD Group is smaller than or equal to a county and (except in California) is greater than or equal to the size of an MCD. The MCD Group units completely tile the United States landmass. This particular study contains the files for the State Level MCD Group Data for the state of Mississippi. Documentation and frequently asked questions are available online at the ROAD Website. A downloadable PDF codebook is also available in the files section of this study.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Replication data sets, Stata .do files, and codebooks for 2010 ANES EGSS, 2008 CCES, 2004 Knowledge Networks survey, and 2001 Virginia and New Jersey surveys
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
MS research data
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Easily accessible with an active internet connection, D*****Key's web-based Microsoft 365 Administrator MS-102 practice exam software stands out as a beacon of reliability. Seamlessly aligned with the actual Microsoft MS-102 exam syllabus, it tracks your Microsoft MS-102 practice exam performance and offers invaluable insights into the MS-102 real exam format. You have the option to select the number of Microsoft 365 MS-102 practice exam’s questions and time limits according to your needs and witness instant results that enhance your degree of Microsoft MS-102 certification exam preparation. Another excellent feature of the Microsoft 365 MS-102 web-based practice exam software is that it can be used on all browsers and operating systems. MS-102 Microsoft 365 Administrator Certification Prep MS-102 Microsoft 365 Administrator Certification Exam Prep MS-102 Microsoft Azure Administrator Certification Practice Test Prep
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This data set contains the research data for the master's thesis: Integrating Explainability into Federated Learning: A Non-functional Requirement Perspective. The master's thesis was written by Nicolas Sebastian Schuler at the Computer Science Department at Karlsruhe Institute for Technology (KIT) in Germany. The data set contains: - Associate Jupyter notebooks for reproducing the figures in the master's thesis. - Generated experiment data by the federated learning simulations. - Results of the user survey conducted for the master's thesis. - Used Python Libraries. It also includes the submitted final thesis. Notice: The research data is split into multiple chunks and can be combined via the following command after downloading: $ cat thesis-results-part-* > thesis-results.tar.zst and extracted via: $ tar --zstd -xvf thesis-results.tar.zst