*.csv; *.mat

We consider a

large location with M number of grid points, each grid point is labeled with a unique fingerprint consisting of the received signal

strength (RSS) values measured from N number of Bluetooth Low Energy (BLE) beacons. Given the fingerprint observed by the

smartphone, the user’s current location can be estimated by finding the top-k similar fingerprints from the list of fingerprints registered

in the database.


This is a protein negative interaction dataset, generated by our proposed method the “Features Dissimilarity-based Negative Generation” approach to generate protein negative sampling based on sequence data. It measures similarity of sequence characteristics without alignment based on Protein similarity. It achieved results of 97% compared to randomly generated negative dataset.


This is a comprehensive dataset of human arm motion during Activities of Daily Living (ADL). The Cartesian locations of the head, torso, and arm segments were recorded using a motion capture system (Vicon) from 12 participants (ages 18-72, 6 male, 6 female) performing 24 unique tasks. These include both standing and sitting tasks, as well as repetitions, selected based on what would be most useful for prosthesis users, resulting in 72 recorded trials per subject.


There is an unmet need for quick, physically small, and cost-effective office-based techniques that can measure bone properties without the use of ionizing radiation. The present study reports application of a neural network classifier to the processing of previously collected data on very low power radiofrequency propagation through the wrist with the goal to detect osteoporotic/osteopenic conditions. Our approach categorizes the data obtained for two dichotomic groups. Group 1 included 27 osteoporotic/osteopenic subjects with low BMD (DXA T score below - 1) measured within one year.


This dataset contains synthetic data for training the two KNN algorithms in the paper A. Coluccia, A. Fascista, and G. Ricci, "A KNN-based Radar Detector for Coherent Targets in non-Gaussian Noise", IEEE Signal Processing Letters, 2021.




Underground UE statistics measurements captured on u-blox SARAN211 NB-IoT device, frequency band 20. Signal waveform captured by means of Rohde&Schwartz TSMW device. The samples were taken along ca. 1600m of level -2 underground tunnel system under Lyngby Campus of Technical University of Denmark.


*This datasheet is being updated progressively to provide more details.

This datasheet provides the phasor measurement data in actual power systems.

These PMU data were recorded during a Low Frequency Oscillation incident and a Short Circuit Incident, respectively.

These PMU data are used for the studies in wide-area control systems (WACS) and PMU data compressions.

Please cite this datasheet and the papers in your work if they help.


We introduce a novel dataset containing a total of 61 distinct HEAs. The proposed appliances (e.g. fans, fridges, washers, etc.) are of different kinds, ages, brands and power
levels. They have been recorded in steady-state conditions in a French 50 Hz electrical grid. The measurement setup consists of an AC current probe (E3N Chauvin Arnoux) with a 10 mV/A sensitivity and a differential voltage probe with