1. Image Recognition Task Execution Times in Mobile Edge Computing: This file contains four (4) datasets of the execution times for image recognition tasks executed in different edge computing servers.
2. Image Recognition Task Execution Times in Mobile Edge Computing: Recorded task execution times for four Edge Servers submitted by edge node; node sends images to servers for image recognition tasks. The servers perform the tasks and return the results to nodes.
3. UrbanGB, urban road accidents coordinates labelled by the urban center: Coordinates (longitude and latitude) of 360177 road accidents occurred in urban areas in Great Britain, and labelled according to the urban center where they occurred (469 possible labels).
4. Parking Birmingham: Data collected from car parks in Birmingham that are operated by NCP from
Birmingham City Council. UK Open Government Licence (OGL).
5. Carbon Nanotubes: This dataset contains 10721 initial and calculated atomic coordinates of carbon nanotubes.
6. Container Crane Controller Data Set: A container crane has the function of transporting containers from one point to another point.
7. microblogPCU: MicroblogPCU data is crawled from sina weibo microblog[http://weibo.com/]. This data can be used to study machine learning methods as well as do some social network research.
8. Perfume Data: This data consists of odors of 20 different perfumes. Data was obtained by using a handheld odor meter (OMX-GR sensor) per second for 28 seconds period.
9. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases.
10. Skin Segmentation: The Skin Segmentation dataset is constructed over B, G, R color space. Skin and Nonskin dataset is generated using skin textures from face images of diversity of age, gender, and race people.
11. Planning Relax: The dataset concerns with the classification of two mental stages from recorded EEG signals: Planning (during imagination of motor act) and Relax state.
12. Nomao: Nomao collects data about places (name, phone, localization...) from many sources.
Deduplication consists in detecting what data refer to the same place.
Instances in the dataset compare 2 spots.