Signal Processing
1.The dataset is the spectrum acquired by using 0.4/0.6-m long SHF.
2.There are 51 different pressure states from 0 MPa to 5 MPa.
3.For each pressure state, more than 130 spectra are collected.
4.In each spectrum, the value of the first row should be deleted.
5.The first col of each spectrum is the wavelength, and the second col is the intensity.
6.The size of each spectrum is (508, 1)
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Here we provide the dataset containing the power measurements obtained with our RIS prototype, which were carried out in the anechoic chamber of TU Darmstadt.
The use of data here contained is intended only for research purposes.
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A video dataset for the paper named "Analysis of ENF Signal Extraction From Videos Acquired by Rolling Shutters" submitted to IEEE Transactions on Information Forensics and Security (T-IFS) and under review.
If you used our dataset, please cite our paper as:
Jisoo Choi, Chau-Wai Wong, Hui Su, and Min Wu, "Analysis of ENF signal extraction from videos acquired by rolling shutters," submitted to IEEE Transactions on Information Forensics and Security (T-IFS), under review.
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video dataset for the paper named "Analysis of ENF Signal Extraction From Videos Acquired by Rolling Shutters"
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Parkinson’s Disease (PD) is the second most common neurodegenerative disorder with resting tremor (RT) being it's most common motor symptom. This study aimed to determine the features of wrist velocity and acceleration that can be used as objective, reliable, and sensitive detectors of RT. Forty-five healthy young adults imitated RT in both hands after observing a video of RT in a person with PD. Inertial measurement units placed on both wrists recorded the linear acceleration and angular velocity, which were used to calculate linear velocity and angular acceleration.
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The dataset includes processed sequences of optical time domain reflectometry (OTDR) traces incorporating different types of fiber faults namely fiber cut, fiber eavesdropping (fiber tapping), dirty connector and bad splice. The dataset can be used for developping ML-based approaches for optical fiber fault detection, localization, idenification, and characterization.
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Oral health problems are closely associated with the analysis of dental tissue changes and the stomatologic treatment that follows. The associated paper explores the use of diffuse reflectance spectroscopy in the detection of dental tissue disorders. The data set includes 78 out of 343 measurements of teeth spectra in the wavelength range from 400 to 1700 nm. The proposed methodology focuses on computational and statistical methods and the use of these methods for the classification of dental tissue into two classes (healthy and unhealthy) by estimating the probability of class membership.
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This dataset contains pathloss and ToA radio maps generated by the ray-tracing software WinProp from Altair. The dataset allows to develop and test the accuracies of pathloss radio map estimation methods and localization algorithms based on RSS or ToA in realistic urban scenarios.
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