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2,541 to 2,550 of 11,426 Results

Full_dataset.txt Apr 5, 2023 - Replication Data for HgCl2 addition to pore water samples from cold seeps can affect the geochemistry of dissolved inorganic carbon ([DIC], d13CDIC) Plain Text - 5.9 KB - MD5: f49d21d5d641778886cf69d1b1e84bb7
Swedish observations of the Aurora Borealis in the period 1716-1732 in contemporaneous scholarly publications Apr 4, 2023 Aspaas, Per Pippin, 2023, "Swedish observations of the Aurora Borealis in the period 1716-1732 in contemporaneous scholarly publications", https://doi.org/10.18710/G5J4YS, DataverseNO, V1 This dataset gives an overview of all Swedish observations of the aurora borealis that were published in various Latin publications from the first half of the eighteenth century.
01_ReadMe_Swedish-observations-of-the-aurora-borealis_1716-1732.txt Apr 4, 2023 - Swedish observations of the Aurora Borealis in the period 1716-1732 in contemporaneous scholarly publications Plain Text - 5.0 KB - MD5: a5f115d06462dd231e8abb61a8cc8f5c Read Me file
02_Swedish-observations-of-the-aurora-borealis_1716-1732.csv Apr 4, 2023 - Swedish observations of the Aurora Borealis in the period 1716-1732 in contemporaneous scholarly publications Comma Separated Values - 39.7 KB - MD5: 0df96f5eb3da3a5538d6b52320a4f2b1 Dataset file
Replication Data for: Dataset of motivational factors for using mobile health applications and systems Mar 31, 2023 Henriksen, André; Woldaregay, Ashenafi Zebene; Issom, David-Zacharie; Pfuhl, Gerit; Sato, Keiichi; Årsand, Eirik; Hartvigsen, Gunnar, 2023, "Replication Data for: Dataset of motivational factors for using mobile health applications and systems", https://doi.org/10.18710/AOQF05, DataverseNO, V1 This dataset contains responses from a questionnaire about what motivates people to collect and share their health data for research and public health benefits. The online questionnaire was open for data collection between November 2018 and March 2020. The questionnaire was published in a Norwegian, English and French version, and published online....
00_ReadMe.txt Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems Plain Text - 23.1 KB - MD5: d29a0fa833e1d0878531dd44fccd154a
Question-metadata.csv Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems Comma Separated Values - 26.1 KB - MD5: d2413d54d36192d98442c49e22bdd9f0 Describes which answer options are available for each question
Questionnaire.pdf Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems Adobe PDF - 142.7 KB - MD5: bdc00c7afcaca72a27f9e4be30b87114
Responses.csv Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems Comma Separated Values - 281.0 KB - MD5: c3b1ace55b8d7348abe8c22d7b8b6039 Questionnaire responses
Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images Mar 29, 2023 Gupta, Deepak K.; Bhamba, Udbhav; Thakur, Abhishek; Gupta, Akash; Sharan, Suraj; Demir, Ertugrul; Prasad, Dilip K., 2023, "Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images", https://doi.org/10.18710/4F4KJS, DataverseNO, V1 Convolutional neural network (CNN) approaches available in the current literature are designed to work primarily with low-resolution images. When applied on very large images, challenges related to GPU memory, smaller receptive field than needed for semantic correspondence and the need to incorporate multi-scale features arise. The resolution of in...

Full_dataset.txt

Apr 5, 2023 - Replication Data for HgCl2 addition to pore water samples from cold seeps can affect the geochemistry of dissolved inorganic carbon ([DIC], d13CDIC)

Plain Text - 5.9 KB -

Swedish observations of the Aurora Borealis in the period 1716-1732 in contemporaneous scholarly publications

Apr 4, 2023

Aspaas, Per Pippin, 2023, "Swedish observations of the Aurora Borealis in the period 1716-1732 in contemporaneous scholarly publications", https://doi.org/10.18710/G5J4YS, DataverseNO, V1

This dataset gives an overview of all Swedish observations of the aurora borealis that were published in various Latin publications from the first half of the eighteenth century.

01_ReadMe_Swedish-observations-of-the-aurora-borealis_1716-1732.txt

Apr 4, 2023 - Swedish observations of the Aurora Borealis in the period 1716-1732 in contemporaneous scholarly publications

Plain Text - 5.0 KB -

Read Me file

02_Swedish-observations-of-the-aurora-borealis_1716-1732.csv

Apr 4, 2023 - Swedish observations of the Aurora Borealis in the period 1716-1732 in contemporaneous scholarly publications

Comma Separated Values - 39.7 KB -

Dataset file

Replication Data for: Dataset of motivational factors for using mobile health applications and systems

Mar 31, 2023

Henriksen, André; Woldaregay, Ashenafi Zebene; Issom, David-Zacharie; Pfuhl, Gerit; Sato, Keiichi; Årsand, Eirik; Hartvigsen, Gunnar, 2023, "Replication Data for: Dataset of motivational factors for using mobile health applications and systems", https://doi.org/10.18710/AOQF05, DataverseNO, V1

This dataset contains responses from a questionnaire about what motivates people to collect and share their health data for research and public health benefits. The online questionnaire was open for data collection between November 2018 and March 2020. The questionnaire was published in a Norwegian, English and French version, and published online....

00_ReadMe.txt

Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems

Plain Text - 23.1 KB -

Question-metadata.csv

Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems

Comma Separated Values - 26.1 KB -

Describes which answer options are available for each question

Questionnaire.pdf

Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems

Adobe PDF - 142.7 KB -

Responses.csv

Mar 31, 2023 - Replication Data for: Dataset of motivational factors for using mobile health applications and systems

Comma Separated Values - 281.0 KB -

Questionnaire responses

Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images

Mar 29, 2023

Gupta, Deepak K.; Bhamba, Udbhav; Thakur, Abhishek; Gupta, Akash; Sharan, Suraj; Demir, Ertugrul; Prasad, Dilip K., 2023, "Supporting Data for: UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images", https://doi.org/10.18710/4F4KJS, DataverseNO, V1

Convolutional neural network (CNN) approaches available in the current literature are designed to work primarily with low-resolution images. When applied on very large images, challenges related to GPU memory, smaller receptive field than needed for semantic correspondence and the need to incorporate multi-scale features arise. The resolution of in...

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