Sensors
![](https://ieee-dataport.org/sites/default/files/styles/3x2/public/tags/images/eeg-2680957_1920.jpg?itok=hBU0EX-n)
The data is obtained from electrocardiography, using flexible electrode, Ag/AgCl electrode and Metal Clamp electrode of a femal subject, age 22 years old.
- Categories:
![](https://ieee-dataport.org/sites/default/files/styles/3x2/public/tags/images/eeg-2680957_1920.jpg?itok=hBU0EX-n)
This data is for training and validating the neural networks.
- Categories:
![](https://ieee-dataport.org/sites/default/files/styles/3x2/public/tags/images/library-1666702_1920_0.jpg?itok=suvlOQtB)
The original AirQuality dataset is downloaded from UCI\footnote{http://archive.ics.uci.edu/ml/datasets/Air+Quality}. CentralAirConditioning is a semi-open access dataset for Chinese National Contest of Maths Models\footnote{http://www.tipdm.org/bdrace/index.html}.
- Categories:
These datasets are of the hydraulically actuated robot HyQ’s proprioceptive sensors. They include absolute and relative encoders, force and torque sensors, and MEMS-based and fibre optic-based inertial measurement units (IMUs). Additionally, a motion capture system recorded the ground truth data with millimetre accuracy. In the datasets HyQ was manually controlled to trot in place or move around the laboratory. The sequence includes: forward and backwards motion, side-to-side motion, zig-zags, yaw motion, and a mix of linear and yaw motion.
- Categories:
This dataset contains laser scans of PCBs as explained in "Fault Diagnosis in Microelectronics Attachment via Deep Learning Analysis of 3D Laser Scans". On the left and right image, we have a closer look at one circuit
module of a PCB , before and after die attachment. Notice the different types of glue annotated as A, B, C, D and E. On each circuit there are four glue deposits on each type where approximately the same quantity of glue has been placed. As explained
- Categories:
This dataset contains the resuts of an experiment in which an electronic nose implemented with six MOX sensors acquired samples of explosives in raw and combined states.
As for the collection of samples, a random experimentation was carried out in order to avoid that data generates any memory effect that could influence the results. Raw TNT and gunpowder data were taken in amounts of 0.1g to 2g. Soap and toothpaste were also used to be mixed with the explosives. In the end, we took samples of the explosive substances in raw and combined states.
- Categories:
![](https://ieee-dataport.org/sites/default/files/styles/3x2/public/tags/images/eeg-2680957_1920.jpg?itok=hBU0EX-n)
The dataset has 150 three-second sampling motor current signals from each synthetically-prepared motors. There are five motors with respective fault condition - bearing axis deviation (F1), stator coil inter-turn short circuit (F2), rotor broken strip (F3), outer bearing ring damage (F4), and healthy (H). The motors are run under five coupling loads - 0, 25, 50, 75, and 100%. The sampling signals are collected and processed into frequency occurrence plots (FOPs). Each image has a label, for example F2_L50_130, where F2 is the fault condition, L50 is the coupling load condition.
- Categories:
![](https://ieee-dataport.org/sites/default/files/styles/3x2/public/tags/images/eeg-2680957_1920.jpg?itok=hBU0EX-n)
This dataset is for the manuscript "TCAD model for TeraFET detectors operating in a large dynamic range" submitted to IEEE Transactions on Terahertz Science and Technology.
- Categories: