The file 'GPS_P2.zip' is the dataset collected from the GNSS sensor of "Xinda" autonomous vehicle in the Connected Autonomous Vehicles Test Fields (the CAVs Test Fields) Weishui Campus,Chang'an University.

The file 'fault.zip' is the simulated faults in the healthy data in '.mat' format, where X_abrupt, X_noise and X_drift represent abrupt faults, noise and drift in the long run are added into the healthy data, respectively.

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The Heidelberg Spiking Datasets comprise two spike-based classification datasets: The Spiking Heidelberg Digits (SHD) dataset and the Spiking Speech Command (SSC) dataset. The latter is derived from Pete Warden's Speech Commands dataset (https://arxiv.org/abs/1804.03209), whereas the former is based on a spoken digit dataset recorded in-house and included in this repository. Both datasets were generated by applying a detailed inner ear model to audio recordings. We distribute the input spikes and target labels in HDF5 format.

Instructions: 

We provide two distinct classification datasets for spiking neural networks. | Name | Classes | Samples (train/valid/test) | Parent dataset | URL | | ---- | ------- | ------ | ------------------------- | --- | | SHD | 20 | 8332/-/2088 | Heidelberg Digits (HD) | https://compneuro.net/datasets/hd_audio.tar.gz | | SSC | 35 | 75466/9981/20382 | Speech Commands v0.2 | https://arxiv.org/abs/1804.03209 | Both datasets are based on respective audio datasets. Spikes in 700 input channels were generated using an artificial cochlea model. The SHD consists of approximately 10000 high-quality aligned studio recordings of spoken digits from 0 to 9 in both German and English language. Recordings exist of 12 distinct speakers two of which are only present in the test set. The SSC is based on the Speech Commands release by Google which consists of utterances recorded from a larger number of speakers under less controlled conditions. It contains 35 word categories from a larger number of speakers.

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The development of electronic nose (e-nose) for a rapid, simple, and low-cost meat assessment system becomes the concern of researchers in recent years. Hence, we provide time-series datasets that were recorded from e-nose for beef quality monitoring experiment. This dataset is originated from 12 type of beef cuts including round (shank), top sirloin, tenderloin, flap meat (flank), striploin (shortloin), brisket, clod/chuck, skirt meat (plate), inside/outside, rib eye, shin, and fat.

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BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer participants), and (2) Emotiv based Dataset (collected from 27 volunteer participants over several months in 2019). 

Instructions: 

There are two folders under each user; session I and sessions II. Each session folder contains four different folders; one for each activity performed by the user. Each activity folder contains .csv files; (1) EEG Data (brainwave.csv), (2) Handmovement Accelerometer Data (accelerometer.csv), and (3) Handmovement Gyroscope Data (gyroscope.csv).

A more deatailed description of the data is given in BS-HMS-Dataset-Documentation.pdf file.

Acknowledgement: This data collection was supported in part by the National Science Foundation (NSF) under grant SaTC-1527795.

Please cite: [1] Diksha Shukla, Sicong Chen, Yao Lu, Partha Pratim Kundu, Ravichandra Malapati, Sujit Poudel, Zhanpeng Jin, Vir Phoha, "Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset)", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/my1k-dd23. Accessed: Dec. 05, 2019.

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Instructions: 

The data in xssed.csv comes from XSSed(http://www.XSSed.com)

The data in normal_example.csv from DMOZ(http://www.dmoztools.net/)

Data are URL formed. IP address and domain name are all removed.

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Trained NN

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A reliable and comprehensive public WiFi fingerprinting database for researchers to implement and compare the indoor localization’s methods.The database contains RSSI information from 6 APs conducted in different days with the support of autonomous robot.

Instructions: 

Database Folder name "RSSI_6AP_Experiments" which includes:

+ Nexus 4 database

+ Nexus 5 database

Training & Testing data are seperated & collected in different time with different locations.

* The general format for csv data file is:

-- X & Y & The list of RSSI

-- X | Y | RSSI Vector

 

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2133 Views

This is an observation data for water quality monitoring. 

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526 Views

Dataset for Telugu Handwritten Gunintam

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Multi-type residual data (vibrations, sound, magnetic intensity) collected from 3D printers & CNC machines.

Instructions: 

1) Unzip file2) Folders contain raw data and features from different type of 3D printers and CNC machines.

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