Machine Learning

Visible Light Positioning is an indoor localization technology that uses wireless transmission of visible light signals to obtain a location estimate of a mobile receiver.
This dataset can be used to validate supervised machine learning approaches in the context of Received Signal Strength Based Visible Light Positioning.
The set is acquired in an experimental setup that consists of 4 LED transmitter beacons and a photodiode as receiving element that can move in 2D.
- Categories:

A dataset from semiconductor assembly and testing processes is used to evaluate the model selection prediction method. The response variable refers to the throughput rate of a specific machine–product combination in one of the assembly and testing process steps based on historical data. This data set includes 1 response variable, 5 categorical machine and product attributes and 11 numerical attributes. The dataset contains 13186 observations.
- Categories:
Tactile perception of the material properties in real-time using tiny embedded systems is a challenging task and of grave importance for dexterous object manipulation such as robotics, prosthetics and augmented reality [1-4] . As the psychophysical dimensions of the material properties cover a wide range of percepts, embedded tactile perception systems require efficient signal feature extraction and classification techniques to process signals collected by tactile sensors in real-time.
- Categories:
GPS spoofing and jamming are common attacks against the UAV, however, conducting these experiments for research can be difficult in many areas. This dataset consists of a logs from simulation and live fights. Logs include data from a benign flight as well as one where the UAV experiences an attack.
Simulated Attacks
Note: This is not the most accurate of the data. We recommend using the live GPS Spoofing and Jamming data if possible.
- Categories:
This dataset is part of my PhD research on malware detection and classification using Deep Learning. It contains static analysis data: Top-1000 imported functions extracted from the 'pe_imports' elements of Cuckoo Sandbox reports. PE malware examples were downloaded from virusshare.com. PE goodware examples were downloaded from portableapps.com and from Windows 7 x86 directories.
- Categories:
This dataset is part of my PhD research on malware detection and classification using Deep Learning. It contains static analysis data: Raw PE byte stream rescaled to a 32 x 32 greyscale image using the Nearest Neighbor Interpolation algorithm and then flattened to a 1024 bytes vector. PE malware examples were downloaded from virusshare.com. PE goodware examples were downloaded from portableapps.com and from Windows 7 x86 directories.
- Categories: