*.csv; *.txt

These datasets report data of 64 Force Sensing Resistors at multiple voltages. It was foun that the input voltage can be used to trim sensors' sensitivity and ultimately to reduce dispersion. The DMAIC cycle was used to reduce process variability on the basis of the Six Sigma Methodology. The zip folder contains:

1) a Matlab file for loading the data

2) four .txt files with the experimental data of Force Sensing resistors

The Dada dataset is associated with the paper “Debiasing Android Malware Datasets: How can I trust your results if your dataset is biased?”. The goal of this dataset is to provide a new updated dataset of goodware/malware applications that can be used by other researchers for performing experiments, for example, detection or classification algorithms. The dataset contains the applications hashes and some characteristics.

This dataset is taken from 20 subjects over a duration of 1 hour where experiments were done on the upper body bio-impedance with the following objectives:

a)     Evaluate the effect of externally induced perturbance at the SE interface caused by motion, applied pressure, temperature variation and posture change on bio-impedance measurements.

b)     Evaluate the degree of distortion due to artefact at multiple frequencies (10kHz-100kHz) in the bio-impedance measurements.

Amidst the COVID-19 pandemic, cyberbullying has become an even more serious threat. Our work aims to investigate the viability of an automatic multiclass cyberbullying detection model that is able to classify whether a cyberbully is targeting a victim’s age, ethnicity, gender, religion, or other quality. Previous literature has not yet explored making fine-grained cyberbullying classifications of such magnitude, and existing cyberbullying datasets suffer from quite severe class imbalances.