FAIR Datasets

The datasets in this collection obtain the badge because:
★ The dataset adheres to the FAIR (Findable, Accessible, Interoperable, Reusable) principles, and provide documentation to support reusability.
★ The dataset's DOI is mentioned in the associated article, enhancing transparency.
★ The associated article is open access via DR-NTU.

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141 to 150 of 873 Results

Scales-saddle.stl Jul 16, 2024 - Related Data for: Scale-Inspired Programmable Robotic Structures with Concurrent Shape Morphing and Stiffness Variation STL Format - 63.1 KB - MD5: 1e86eed222fb6adbab5af21161022e46
amss_insitu_participant_data.tab Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas Tabular Data - 55.0 KB - 90 Variables, 205 Observations - UNF:6:52pESJGuyfEQILbc8nImyQ== Participant responses to site evaluation questionnaire and participant information questionnaire
comb_obj_insitu_session_data.tab Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas Tabular Data - 33.3 KB - 10 Variables, 440 Observations - UNF:6:auze+RNDNLrv5GvfQpfEWg== Per session combined objective acoustic measurement and subjective response data
enviro_session_data.tab Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas Tabular Data - 4.2 KB - 9 Variables, 68 Observations - UNF:6:DLP7Ahd3xy0l7c3DDjEBew== Environmental data logged during the 10-min listening period per session
fullData.RData Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas R Data - 21.0 KB - MD5: 9cb65580c64235ae0119048ad9646203 RData file containing all the csv files in this repository as individual dataframes
predict_session_data.tab Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas Tabular Data - 19.3 KB - 3 Variables, 481 Observations - UNF:6:bFsD8nvT4ywfzYFWDh7zqA== Predicted bird maskers logged during the 10-min listening period per session
Code for plotting PCC for increasing photon number and coupling strength.py Jun 6, 2024 - Replication Data for: Strongly correlated multielectron bunches from interaction with quantum light Python Source Code - 7.2 KB - MD5: 70a607d351cb4b5a8b08052fed6d58d1
Code for Successive Interaction of Two QEWs with Quantized Light.py Jun 6, 2024 - Replication Data for: Strongly correlated multielectron bunches from interaction with quantum light Python Source Code - 3.3 KB - MD5: c7206311460167c8c832573f7242523f
Code for Interaction of Two QEWs with Non-Quantized Light.py Mar 2, 2024 - Replication Data for: Strongly correlated multielectron bunches from interaction with quantum light Python Source Code - 1.8 KB - MD5: d0fca895a500cf962734879a5d1e88a8 Code
Code for Simultaenous Interaction of Three QEWs with Quantized Light after Post-selecting QEW 1.py Mar 2, 2024 - Replication Data for: Strongly correlated multielectron bunches from interaction with quantum light Python Source Code - 4.6 KB - MD5: 38a9993609b490d84ee41fc95bfc29ff Code

Scales-saddle.stl

Jul 16, 2024 - Related Data for: Scale-Inspired Programmable Robotic Structures with Concurrent Shape Morphing and Stiffness Variation

STL Format - 63.1 KB -

amss_insitu_participant_data.tab

Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas

Tabular Data - 55.0 KB - 90 Variables, 205 Observations -

Participant responses to site evaluation questionnaire and participant information questionnaire

comb_obj_insitu_session_data.tab

Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas

Tabular Data - 33.3 KB - 10 Variables, 440 Observations -

Per session combined objective acoustic measurement and subjective response data

enviro_session_data.tab

Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas

Tabular Data - 4.2 KB - 9 Variables, 68 Observations -

Environmental data logged during the 10-min listening period per session

fullData.RData

Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas

R Data - 21.0 KB -

RData file containing all the csv files in this repository as individual dataframes

predict_session_data.tab

Jul 6, 2024 - Replication Data for: Automating Urban Soundscape Enhancements with AI: In-situ Assessment of Quality and Restorativeness in Traffic-Exposed Residential Areas

Tabular Data - 19.3 KB - 3 Variables, 481 Observations -

Predicted bird maskers logged during the 10-min listening period per session

Code for plotting PCC for increasing photon number and coupling strength.py

Jun 6, 2024 - Replication Data for: Strongly correlated multielectron bunches from interaction with quantum light

Python Source Code - 7.2 KB -

Code for Successive Interaction of Two QEWs with Quantized Light.py

Jun 6, 2024 - Replication Data for: Strongly correlated multielectron bunches from interaction with quantum light

Python Source Code - 3.3 KB -

Code for Interaction of Two QEWs with Non-Quantized Light.py

Mar 2, 2024 - Replication Data for: Strongly correlated multielectron bunches from interaction with quantum light

Python Source Code - 1.8 KB -

Code

Code for Simultaenous Interaction of Three QEWs with Quantized Light after Post-selecting QEW 1.py

Mar 2, 2024 - Replication Data for: Strongly correlated multielectron bunches from interaction with quantum light

Python Source Code - 4.6 KB -

Code

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