5,221 to 5,230 of 11,437 Results
Comma Separated Values - 18.9 MB -
MD5: 6fde195cd3392ac4a547decbd1222fe1
Raw data downloaded from DOAJ on May 31st 2021 |
Comma Separated Values - 6.4 MB -
MD5: 761234fb010ddd15a4c7b5dd17290430
Original data file with information about publishing in journals and serials 2017-2020 for Norwegian authors, received from The Norwegian Directorate for Higher Education and Skills (HK-dir)/The Norwegian Register for Scientific Journals, Series and Publishers. |
Comma Separated Values - 190 B -
MD5: 9d197b0fb4b44c0fe1d2c00d67f6a638
Table to convert Norwegian subject area terms to English |
Comma Separated Values - 3.4 KB -
MD5: ae233456bc8a430b2f1e9660fa36c29f
Table to convert Norwegian subject field terms to English |
Comma Separated Values - 9.0 MB -
MD5: 1816b5345bbbafd92e96d8ba73b9e781
This are the data from the HK-dir file, augmented with information from the DOAJ file and with subject field and subject area fields translated to English. This is the basis for the construction of the tables in the Manuscript, through use of the Excel Pivot Table function. |
Mar 2, 2022 - Tromsø Geophysical Observatory
Tromsø Geophysical Observatory, 2022, "TGO Ramfjordmoen Ionosonde Data February 2022", https://doi.org/10.18710/YTMWGQ, DataverseNO, V1
About this dataset: This dataset contains ionosonde data in SAO format and ionograms in PNG format, and covers data from February 01-28, 2022. About the Tromsø Ionosonde (1993-present): Since 1980, the ionosonde was situated at 69° 35' N, 19° 13' E at Ramfjordmoen near Tromsø, Norway and operated by the Auroral Observatory of the University of Trom... |
Mar 2, 2022 -
TGO Ramfjordmoen Ionosonde Data February 2022
Plain Text - 2.1 KB -
MD5: 669765b414f6fe3c0782dbcd9048573c
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Mar 2, 2022 -
TGO Ramfjordmoen Ionosonde Data February 2022
ZIP Archive - 39.6 MB -
MD5: 2717bb632a5d7db55b7b3eb46d7fd17c
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Mar 2, 2022 -
TGO Ramfjordmoen Ionosonde Data February 2022
ZIP Archive - 7.9 MB -
MD5: f195c5ed1a59000b377ac3e77d6c165f
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Feb 28, 2022
Tedeschi, Enrico, 2022, "Bitcoin blockchain optimized for machine learning prediction model", https://doi.org/10.18710/8IKVEU, DataverseNO, V1
This dataset stores part of the Bitcoin blockchain. Blocks are sampled every month and information about transactions and blocks are separated to save disk space and avoid redundancies. This dataset is used in the work presented by Tedeschi et al.[1], in order to generate a machine learning model that predicts transaction inclusion. In each month o... |
