11 to 20 of 267 Results
Jun 9, 2026 -
EC3 Steel Portal Frame Structural Analysis Dataset
Unknown - 23.8 MB -
MD5: af553cc7a6ae6ac21458991f4acecaee
17,168 records - one per structural element (columns and rafters). Contains section properties, EC3 utilization ratios, buckling parameters, axial forces per load case, and governing check identification. Links to frames.jsonl via run_id. |
Jun 9, 2026 -
EC3 Steel Portal Frame Structural Analysis Dataset
Unknown - 28.3 MB -
MD5: 6baca1c520676be159aed9e87807dbd2
4,940 records - one per portal frame. Contains geometry, load parameters, steel weight, nodal displacements, maximum deflections, and EC3 compliance flag. Links to elements.jsonl via run_id. |
Jun 5, 2026 - Social Sciences
Lāma, Gatis; Kosīte, Daina; Rozenberga, Gita; Melderis, Mikus; Andersone, Iveta; Badūne, Laura; Dukulis, Ilmars; Judrups, Janis; Vecpuise, Elza, 2026, "Dataset for survey "Open Science and Research Data Management Practices in Latvia" / Aptaujas dati "Atvērtās zinātnes un pētniecības datu pārvaldības prakse Latvijā"", https://doi.org/10.71782/DATA/VASTUK, DataverseLV, V2, UNF:6:B7hQczM3ChoTPq7qwNhC9w== [fileUNF]
EN: This dataset supports a study that analyzes Latvian researchers’ understanding, skills, and practices in the fields of open science and research data management, with particular attention devoted to the data lifecycle. The empirical research was conducted within the framework of the project “Support for the Implementation of Open Science in Pra... |
Plain Text - 3.0 KB -
MD5: 8028515564dd0bd21e5aa81fe110214b
ReadMe file describing the dataset, authors, data collection, data structure, access rights, license, and related documentation. |
The Latvian State Forest Research Institute "Silava" Dataverse contains research data produced by LSFRI "Silava" scientists in studies related to forest ecosystem research. The repository collection includes data on the occurrence of species across various organism groups, water and soil quality indicators from study sites, forest recreation area v... |
May 28, 2026 - Natural Sciences
Locs, Mārtiņš, 2026, "Assessment of BirdNetR classification accuracy in passive acoustic monitoring of reedbed birds / BirdNet klasifikatora precizitātes novērtējums niedrāju putnu pasīvā akustiskajā monitoringā", https://doi.org/10.71782/DATA/FGYBPI, DataverseLV, V1, UNF:6:066QXtZICNQDYrxCHKAufg== [fileUNF]
[ENG] This repository was created to maintain and ensure the storage of large files of the bachelor's thesis, as well as to reproduce the work progress and results. The study evaluated the accuracy of the deep learning classifier BirdNet in passive acoustic monitoring of reed birds in Latvia. Autonomous recording units were placed in 24 randomly se... |
TIFF Image - 209.2 MB -
MD5: 2ab3e8e1c953043857b0d467b350592b
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Plain Text - 5.2 KB -
MD5: 1c44461fd0d64300ef02da301844203c
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Plain Text - 5.4 KB -
MD5: 6c82839ccbcc1fbee77f62f150f2c131
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Tabular Data - 489.7 MB - 17 Variables, 2730524 Observations - UNF:6:Y759rEEHYAdz4h5qg49Q5A==
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