This supplemental file contains (1) the warpage values of 201 sample points that were used to construct the Bivariate Cut-HDMR metamodel; (2) the warpage values of 1,045 sample points that were used to construct the CCD metamodel; and (3) the Monte Carlo simulation sample points that used for validation.

Categories:
63 Views

 

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.  

Categories:
413 Views

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.

Instructions: 

Extract locally the zip files, read the readme file.

Instructions for dataset usage are included in the open access paper: Franzoni, V., Biondi, G., Milani, A., Emotional sounds of crowds: spectrogram-based analysis using deep learning (2020) Multimedia Tools and Applications, 79 (47-48), pp. 36063-36075. https://doi.org/10.1007/s11042-020-09428-x

File are released under Creative Commons Attribution-ShareAlike 4.0 International License

Categories:
573 Views

The dataset contains information on 15 public failed software projects. It represents the primary behavior of a team against the failure process.

 

Categories:
27 Views

Segmentation of TC clouds in 2016. The segmentation task was accomplished by an algorithm which takes a time series of brightness temperature images of TCs and uses image processing techniques to acquire segmentation for each image in a semi-supervised manner. 

Instructions: 

2016 TC cloud segmentation animation

Categories:
246 Views

 

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).
Categories:
123 Views

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

Instructions: 

Download the data files and put them under data (place the uncompressed files or symbolic links)
cd path/to/crowdbot_tools/data
# (recommended) create symbolic links of rosbag folder instead of copying data:
ln -s /data_qolo/lausanne_2021/24_04_2021/shared_control 0424_shared_control
ln -s /data_qolo/lausanne_2021/24_04_2021/RDS/detector 0424_rds_detectorThe used file structure is as follows:

Examples of how to access the data can be found in the open repository: https://github.com/epfl-lasa/crowdbot-evaluation-tools 

Categories:
309 Views

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.

Instructions: 

This dataset contains the following main files:

 

  • collision_test_rawdata.zip:  This file contains all the raw data for each sensor as mentioned in table 3, organized in independent subfolders as described in table 2. ‘test_name’/01_values/’testName’_CFC1000.xlsx
  • collision_test_analysis.zip: This file contains all the processed data for each sensor in order to apply known injury metrics (Nij, HIC15, acc_3ms, TI, CC, VCI), organized in independent subfolders as described in table 2.‘test_name’/01_values/’testName’_Analysis_v2.xlsx
  • collision_data_matlab_structure.zip: Matlab containers with all data.
  • scripts-crash-test-service-robots.zip: processing of the dataset is provided in this file with structure of data in Matlab containers and scripts for visualizing the data (see section III), further analysis scripts in the linked GitHub: https://github.com/epfl-lasa/crash-tests-service-robots
Categories:
157 Views

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.

Instructions: 

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.

4. Date : the date of the viewing behavior record, [0, 31], August 1~31, 2014, here 0 denotes July 31, 2014.

5. TimeSection: the number of time section, [1, 144], we divide one day (24 hours) into 144 time sections, each of which is 10 minutes. For example, the number 1 means the record occurs between 00:00 and 00:10 on the day, and number 144 means that the record is between 23:50 and 24:00 on the day.

6.  StartTime: the time when the user starts to watch the current channel, whose value is the cumulative time interval is numbered with a value of 1-86400 in unit of second on the current day; for example, 62990 means 17:29:50.

7.   Duration: the duration the user watches current channel from the start time point, in unit of second, and we have deleted the records whose duration is less than 5 seconds as well as more than 3600*8 seconds. 

Please select your interested data from the dataset for your demand. 

Acknowledgement : We thanks the senior engineer, Mr. Songtao Wu, for the original dataset in GZTV station, Guangdong, China.

Qihu Yuan  and Can Yang

2021-01

Categories:
192 Views

Pages