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101 to 110 of 121 Results

train_cbd_classifier.py Feb 4, 2025 - A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia Python Source Code - 6.6 KB - MD5: ec288e1f754bbf4e48cce1cea4a230ef
train_condition_classifier.py Feb 4, 2025 - A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia Python Source Code - 6.1 KB - MD5: c875a54fee45377b8c440c6ce57e855a
Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network Apr 29, 2024 Tong, Daniel Quansong, 2024, "Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network", https://doi.org/10.13021/ORC2020/EOL1WJ, George Mason University Dataverse, V1 This dataset contains daily observations of PM10, PM2.5 and chemical composition measured by the Interagency Monitoring of Protected Visual Environment (IMPROVE) network. In addition the raw IMPROVE data, local dust storms and wildfire events are identified in a separate column b...
improve_events_2023_all.txt Apr 29, 2024 - Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network Plain Text - 260.4 MB - MD5: 7718dcb7a8d0b5012f33dbd450c3735e IMPROVE dust and wildfire events
Readme_IMPROVE_Events_20240428.pdf Apr 29, 2024 - Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network Adobe PDF - 44.6 KB - MD5: e5fc7cdf409af88bdda53343cd228526 Readme
Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation" Oct 23, 2023 Kelley, Matthew C; Perry, Scott James; Tucker, Benjamin V, 2023, "Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"", https://doi.org/10.13021/ORC2020/PDSAP7, George Mason University Dataverse, V1 These are the TextGrid outputs of the alignments run during the evaluation process for the MAPS paper. They are separated into train, validation, and test sets. The results from training and running the Montreal Forced Aligner (MFA) are also provided. The tar file for MFA contain...
mfa_tg.tar.bz2 Oct 23, 2023 - Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation" Compressed Archive - 3.0 MB - MD5: 9acf688c4867b034bfb77296f1515ae4
test_tg.tar.bz2 Oct 23, 2023 - Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation" Compressed Archive - 41.7 MB - MD5: 22bccff875b3414f048ee53f2963647a
train_tg.tar.bz2 Oct 23, 2023 - Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation" Compressed Archive - 245.9 MB - MD5: aad1b9d97eb50140984e00bcea8e4bd0
val_tg.tar.bz2 Oct 23, 2023 - Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation" Compressed Archive - 17.9 MB - MD5: a62a85d53f4a318711c75682a16e6286

train_cbd_classifier.py

Feb 4, 2025 - A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia

Python Source Code - 6.6 KB -

train_condition_classifier.py

Feb 4, 2025 - A predictive machine learning model for cannabinoid effect based on image detection of reactive oxygen species in microglia

Python Source Code - 6.1 KB -

Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network

Apr 29, 2024

Tong, Daniel Quansong, 2024, "Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network", https://doi.org/10.13021/ORC2020/EOL1WJ, George Mason University Dataverse, V1

This dataset contains daily observations of PM10, PM2.5 and chemical composition measured by the Interagency Monitoring of Protected Visual Environment (IMPROVE) network. In addition the raw IMPROVE data, local dust storms and wildfire events are identified in a separate column b...

improve_events_2023_all.txt

Apr 29, 2024 - Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network

Plain Text - 260.4 MB -

IMPROVE dust and wildfire events

Readme_IMPROVE_Events_20240428.pdf

Apr 29, 2024 - Aerosol Composition during Dust Storms and Wildfires from the IMPROVE Network

Adobe PDF - 44.6 KB -

Readme

Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"

Oct 23, 2023

Kelley, Matthew C; Perry, Scott James; Tucker, Benjamin V, 2023, "Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"", https://doi.org/10.13021/ORC2020/PDSAP7, George Mason University Dataverse, V1

These are the TextGrid outputs of the alignments run during the evaluation process for the MAPS paper. They are separated into train, validation, and test sets. The results from training and running the Montreal Forced Aligner (MFA) are also provided. The tar file for MFA contain...

mfa_tg.tar.bz2

Oct 23, 2023 - Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"

Compressed Archive - 3.0 MB -

test_tg.tar.bz2

Oct 23, 2023 - Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"

Compressed Archive - 41.7 MB -

train_tg.tar.bz2

Oct 23, 2023 - Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"

Compressed Archive - 245.9 MB -

val_tg.tar.bz2

Oct 23, 2023 - Replication Data for "The Mason-Alberta Phonetic Segmenter: A forced alignment system based on deep neural networks and interpolation"

Compressed Archive - 17.9 MB -

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