721 to 730 of 1,004 Results
Apr 14, 2020
Kvammen, Andreas; Wickstrøm, Kristoffer; McKay, Derek; Partamies, Noora, 2020, "Replication Data for: Auroral Image Classification with Deep Neural Networks", https://doi.org/10.18710/SSA38J, DataverseNO, V3
Results from a study of automatic aurora classification using machine learning techniques are presented. The aurora is the manifestation of physical phenomena in the ionosphere magnetosphere environment. Automatic classification of millions of auroral images from the Arctic and Antarctic is therefore an attractive tool for developing auroral statis... |
Mar 9, 2021
Nierenberg, Ellen; Låg, Torstein; Dahl, Tove I., 2020, "Replication Data for: Knowing and doing: The development of information literacy measures to assess knowledge and practice", https://doi.org/10.18710/L60VDI, DataverseNO, V2
This data set contains the replication data for the article "Knowing and doing: The development of information literacy measures to assess knowledge and practice." This article was published in the Journal of Information Literacy, in June 2021. The data was collected as part of the contact author's PhD research on information literacy (IL). One goa... |
Mar 15, 2022
Juskewitz, Eric, 2022, "Replication Data for: "Lulworthinone: In vitro mode of action investigation of an antibacterial dimeric naphthopyrone isolated from a marine fungus."", https://doi.org/10.18710/6Z0VJX, DataverseNO, V1
Treatment options for infections caused by antimicrobial-resistant bacteria are rendered ineffective, and drug alternatives are needed - either from new chemical classes or drugs with new modes of action. Historically, natural products have been important contributors to drug discovery. The search for new antimicrobials from marine fungi led to the... |
Jan 24, 2018 - NMDC Node UiT
UiT The Arctic University of Norway, 2018, "Scenery photos without the frame (2010)", https://doi.org/10.18710/XJW2FZ, DataverseNO, V1, UNF:6:rGhX9wmNXa2evtJwr7XRTw== [fileUNF]
Contains photographs documenting under-water scenery and fauna across Svalbard. The data base contains photographs documenting under-water scenery and fauna across Svalbard and mainland at depths from ca. 5 to 30 m at non-marked, non-revisited locations. These non-scaled photographs were taken by divers. These photographs were taken in support of t... |
Jan 24, 2018 - NMDC Node UiT
UiT The Arctic University of Norway, 2018, "Scenery photos without the frame (1989)", https://doi.org/10.18710/4U1PKN, DataverseNO, V1, UNF:6:Si7NPSvJvaK9adoJbZ6WGg== [fileUNF]
Contains photographs documenting under-water scenery and fauna across Svalbard. The data base contains photographs documenting under-water scenery and fauna across Svalbard and mainland at depths from ca. 5 to 30 m at non-marked, non-revisited locations. These non-scaled photographs were taken by divers. These photographs were taken in support of t... |
Jan 24, 2018 - NMDC Node UiT
UiT The Arctic University of Norway, 2018, "Photo frames on non-permanent stations (1998)", https://doi.org/10.18710/D6PKJF, DataverseNO, V1, UNF:6:PxhTxT94IitV7/sVGrSZCA== [fileUNF]
Contains under-water photographs taken with a standardized frame at non-permanent stations across Svalbard. The database contains photographs documenting under-water scenery and fauna across Svalbard and mainland at depths from ca. 5 to 30 m at non-marked, non-revisited locations. These scaled photographs were taken by divers. These photographs wer... |
Feb 19, 2018
Amundsen, Per-Arne, 2018, "Fish ecology data from 16 lakes on Finnmarksvidda, Norway 2005-2009", https://doi.org/10.18710/FDOXMA, DataverseNO, V1, UNF:6:EsEgjJn2GfsaZxrN18G3zw== [fileUNF]
The database contains biological and ecological data from freshwater fish collected from 16 lake localities situated on the Finnmarksvidda highland plateau from 2005 to 2009. Fish sampling was carried out after standard protocols using multimesh gillnets in littoral, pelagic and profundal habitats. Parameters include species, morphotype of whitefis... |
Jul 4, 2022 - Tromsø Geophysical Observatory
Tromsø Geophysical Observatory, 2018, "TGO Ramfjordmoen Ionosonde Data July 1993", https://doi.org/10.18710/QBLIP8, DataverseNO, V4
About this dataset: This dataset contains ionosonde data in SAO format, and covers data from July 01-31, 1993. 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 Tromsø and later on, in collaboratio... |
May 22, 2019
Blanco Gonzalez, Enrique; Espeland, Sigurd Heiberg; Jentoft, Sissel; Hansen, Michael Møller; Robalo, Joana Isabel; Stenseth, Nils Christian; Jorde, Per Erik, 2019, "Replication Data for: Interbreeding between local and translocated populations of a cleaner fish in an experimental mesocosm predicts risk of disrupted local adaptation", https://doi.org/10.18710/DSAPAP, DataverseNO, V2, UNF:6:GM79SmL+2M9XhptSGoPwVA== [fileUNF]
This data file contains genotypic information at 11 microsatellite loci for parental analysis of corkwing wrasse (Symphodus melops). Additionally, it also contains phenotypic information from breeders. Abstract: Translocation of organisms within or outside its native range carries the risk of modifying the community of the recipient ecosystems and... |
May 11, 2021 - Spawning behavior of Arctic charr
Egeland, Torvald B.; Folstad, Ivar; Nordeide, Jarle Tryti, 2021, "Video recordings of spawning behavior of Arctic charr; date: 2016-09-19; spawning ground: 3; time: afternoon; camera no: 3", https://doi.org/10.18710/LIN7TX, DataverseNO, V1
This dataset contains video recordings of spawning behavior of Arctic charr (Salvelinus alpinus) in Lake Fjellfrøsvatnet (69°08′N 19°34′E), Troms, Northern Norway. The recordings were made with camera no. 3 at spawning ground 3 in the afternoon of 19 September 2016. A description of the data structure and format is gathered in the documentation dat... |
