11 to 20 of 13,068 Results
Jun 7, 2023 - University of Inland Norway
Nacey, Susan, 2021, "Replication data for: Learner translation of metaphor: Smooth sailing?", https://doi.org/10.18710/TG0I6G, DataverseNO, V3
The datasets, R code and informant information letter for the article 'Learner metaphor in translation: Smooth sailing?' The article abstract is as follows: This article explores metaphor translation strategies of novice translators: university students translating from L1 Norweg... |
Plain Text - 9.6 KB -
MD5: 368f6e11ed70fcaa8d106992f4a10e52
Explanatory information about the following text files: 1) Replication data_Learner_translation_of_metaphor, 2) NaceyFürst_Learner_translation_NorwegianST_and_EnglishTTs, and 3) NaceyFürst_Learner_translation_dataset |
Aug 17, 2022 - NTNU – Norwegian University of Science and Technology
Fuglerud, Silje Skeide, 2021, "Aqueous glucose measured by NIR spectroscopy", https://doi.org/10.18710/NSHFAK, DataverseNO, V2
Near infrared spectroscopy (NIR) is a promising technique that could be used for continuous blood glucose monitoring in the treatment of diabetic patients. Four interferents (lactate, ethanol, caffeine and acetaminophen) were introduced to study how the glucose predictions varied... |
Aug 17, 2022 -
Aqueous glucose measured by NIR spectroscopy
Plain Text - 3.1 KB -
MD5: 202f7cc7c9a528d65a75aceaa6222790
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Jun 2, 2022 - UiT The Arctic University of Norway
Kilvaer, Thomas K, 2021, "UiT_TILs - Replication Data for "A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images"", https://doi.org/10.18710/4YN9SZ, DataverseNO, V2
This dataset can be used to replicate the findings in "A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images". The motivation for this paper is that increased levels of tumor infiltrating lymphocytes (TILs) indicate favorable outco... |
Plain Text - 19.9 KB -
MD5: 321381ea19852b69daecc042fa9526ef
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Unknown - 1.9 GB -
MD5: b1694ccd6eeb408182170dc065f2672a
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Unknown - 1.9 GB -
MD5: e74f5a2f7fc8a8e39a4b04d1e5c28fc9
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Unknown - 849.8 MB -
MD5: 49a781e0c1a8a525bbf1bf76fc7cf229
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TAR Archive - 1.8 GB -
MD5: 825b003ced6f2ba8c35a6a5a247b2bc7
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