.csv.zip
Dataset of mobile phone usage records collected with Nodobo suite at the University of Strathclyde.
Dataset gathered by Nodobo, a suite of social sensor software for Android phones, during a study of the mobile phone usage at University of Strathclyde.
date/time of measurement start: 2010-09-09
date/time of measurement end: 2011-02-23
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321 Views
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2879 Views
This dataset was used to investigate numerical methods of integration of the Frenet-Serret equations as applied to the study of vessel shape. This data is a compliation of previously published data from the following papers:
A. V. Kamenskiy, J. N. MacTaggart, I. I. Pipinos, et al., “Three-dimensional geometry of the human carotid artery,” Journal of Biomechanical Engineering, vol. 134, no. 6, p. 064592, 2012.
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380 Views
This is a dataset consisting of 8 features extracted from 70,000 monochromatic still images adapted from the Genome Project Standford's database, that are labeled in two classes: LSB steganography (1) and without LSB Steganography (0). These features are Kurtosis, Skewness, Standard Deviation, Range, Median, Geometric Mean, Hjorth Mobility, and Hjorth Complexity, all extracted from the histograms of the still images, including random spatial transformations. The steganographic function embeds five types of payloads, from 0.1 to 0.5.
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2407 Views
This data contains EMG records of forearm movements. this data can be used for the learning process for students and lecturers or researchers. The sensor used to record data is "Myo Arm-Band". The data is equipped with eight features and ends with the arm movement label still using the Indonesian language term.
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665 Views
This data consists of ten gestures. The format is CSV, arranged in thirty features that end with a label. Each movement is repeated five times and the coordinates are obtained. The sensor used is LeapMotion. This data can be used as a means of machine learning exercises. can be used for students learning machine learning subjects. articles that have used this data can be seen at the link: https://doi.org/10.1109/CENIM.2018.8711397
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1109 Views
In order to increase the diversity in signal datasets, we create a new dataset called HisarMod, which includes 26 classes and 5 different modulation families passing through 5 different wireless communication channel. During the generation of the dataset, MATLAB 2017a is employed for creating random bit sequences, symbols, and wireless fading channels.
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8535 Views
Complex networks have been successfully applied to sleep stage analysis and classification. However, whether the electroencephalogram (EEG) montage reference will affect the network properties is still unclear.
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875 Views