Standards Research Data

https://www.scholat.com/teamworkdownloadscholar.html?id=5885&teamId=612
Note that, you must register on https://www.scholat.com, and join our team "new_media", finally download the dataset. Pretecting the user pravicy.
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Crowds express emotions as a collective individual, which is evident from the sounds that a crowd produces in particular events, e.g., collective booing, laughing or cheering in sports matches, movies, theaters, concerts, political demonstrations, and riots. Crowd sounds can be characterized by frequency-amplitude features, using analysis techniques similar to those applied on individual voices, where deep learning classification is applied to spectrogram images derived by sound transformations.
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N/A
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The data include:
- Demographic data of the participants including: gender, group of participation and number of years in the company.
- Results of the use of Ethool including: expended time and subjective evaluation of if using a Likert of 5 points. Two different files are available corresponding to each iteration (prototype 1 and prototype 2).
- Results of the SUS questionnaire for both iterations (prototype 1 and prototype 2).
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The current dataset – crowdbot – presents outdoor pedestrian tracking from onboard sensors on a personal mobility robot navigating in crowds. The robot Qolo, a personal mobility vehicle for people with lower-body impairments was equipped with a reactive navigation control operating in shared-control or autonomous mode when navigating on three different streets of the city of Lausanne, Switzerland during farmer’s market days and Christmas market. Full Dataset here: DOI:10.21227/ak77-d722
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This dataset presents collisions between a service robot - Qolo - and pedestrian dummies: male adult Hybrid-III (H3) and child model 3-years-old (Q3). We present a set of collision scenarios for the assessment of pedestrian safety, considering possible impacts at the legs for adult pedestrians, and legs, chest and head for children.
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Each record in the dataset includes 7 fields:
UserID, CurrentChannel, NextChannel, Date, TimeSection, StartTime, Duration.
The meanings of them are respectively as follows,
1. UserID : the number of a user, sorted in descending order by the number of channels he/she has switched during the period of time; [1, 13246].
2. CurrentChannel: the channel ID viewed by the user in the current time section.
3. NextChannel: the channel ID which the user would view in the next time section.
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The data are associated with a submitted journal paper.
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