This publication contains three new datasets for scene-level sketch semantic segmentation task, namely SKY-Scene, TUB-Scene, and Freehand-Scene. SKY-Scene and TUB-Scene are synthetic datasets, where the scene layout templates were extracted from dataset SketchyScene, and the object components were adopted from dataset Sketchy. They are composed to include more sketch-specific characteristics, e.g., sparsity, abstractness, and diversity, to truly evaluate segmentation performance. Freehand-Scene are fifty real human-drawn scene sketches for practical test.

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Recently, surface electromyogram (EMG) has been proposed as a novel biometric trait for addressing some key limitations of current biometrics, such as spoofing and liveness. The EMG signals possess a unique characteristic: they are inherently different for individuals (biometrics), and they can be customized to realize multi-length codes or passwords (for example, by performing different gestures).

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This dataset is based on the ACFR Five Roundabouts Dataset. The original tracking data of over 23,000 traffic vehicles have been processed with an optimization-based filtering method to combat measurement noise and errors. Smooth velocity and acceleration signals are reconstructed. The processed recordings have then undergone a selection process using DBSCAN to remove the erroneous samples. The remaining samples contained in this dataset are considered representative of how average human drivers approach a roundabout scenario in daily driving.

Instructions: 

We sincerely hope that sharing this dataset would help researchers in the relevant fields. Explanations on the dataset structure can be found in the README in the zip file. In case of any questions, please contact the authors via: y.zheng-2@tudelft.nl. Thank you!

 

The details of the processing method are presented in:

Y. Zheng, B. Shyrokau and T. Keviczky, "Comfort and Time Efficiency: A Roundabout Case Study," 2021 IEEE International Conference on Intelligent Transportation Systems (ITSC), 2021

(To be available online in Oct. 2021. Citation information will be updated.)

 

When using this dataset, please kindly cite our work above as well as the following:

A. Zyner, S. Worrall and E. M. Nebot, "ACFR Five Roundabouts Dataset: Naturalistic Driving at Unsignalized Intersections," in IEEE Intelligent Transportation Systems Magazine, vol. 11, no. 4, pp. 8-18, winter 2019, DOI: 10.1109/MITS.2019.2907676.

 

The original ACFR Five Roundabouts Dataset can be found via:

https://ieee-dataport.org/open-access/acfr-five-roundabouts-dataset

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This is a dataset is an example of a distribution of 20 correlated Bernoulli random variables.

Instructions: 

Q_joint ... is 5 cells each consists of the joint distributions of 4,8,12,16,20 bits, respectively. The dimension of each cell is 2^n X 1, .e., a vertical column and n=4,8,12,16,20.

Q_conditional... is 5 cells each consists of the conditional distributions of 4 bits given 0, 4, 8,12,16 bits, respectively. In other words, 1:4 bits, 5:8 bits given 1:4 bits, 9:12 bits given 1:8 bits, 13:16 bits given 1:12 bits, 17:20 given 1:16 bits. The dimension of each cell is 2^4=16 X 2^n, i.e., a vertical column and n=4,8,12,16.

Q_ marginal... is 5 cells each consists of the marginal distributions of each 4 consecutive bits, i.e., 1:4 - 5:8 - 9:12 - 13:16 - 17:20, respectively.  The dimension of each cell is 16 X 1, i.e., q vertical column.

Also, a MATLAB code is uploaded to extract conditional and marginal distributions from any given discrete distribution.

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This work provides the measurement data of sixteen high frequency (HF) radio frequency identification (RFID) transponder (tag) chips. In particular, the chip input impedance was characterized versus chip input voltage at 13.56 MHz. The measurement is based on the radio frequency current-voltage impedance measurement method and achieves, compared to previous work, higher measurement accuracy of lower than 1.5 %. The accompanying publication provides additional details.

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The objective of this dataset is the fault diagnosis in diesel engines to assist the predictive maintenance, through the analysis of the variation of the pressure curves inside the cylinders and the torsional vibration response of the crankshaft. Hence a fault simulation model based on a zero-dimensional thermodynamic model was developed. The adopted feature vectors were chosen from the thermodynamic model and obtained from processing signals as pressure and temperature inside the cylinder, as well as, torsional vibration of the engine’s flywheel.

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The presented data contain recordings of underwater acoustic transmissions collected from a field experiment whose goal was to characterize self-interference for in-band full-duplex underwater acoustic communications. The experiment was conducted in the Lake of Tuscaloosa in July 2019. A single transmission-receiving line was deployed off a boat that was moored in the center of the lake. The transmission-receiving line had one acoustic transmitter and eight hydrophone receivers.

Instructions: 

1) User Guide for In-Band Full-Duplex Underwater Acoustic Communication Measurements Self-interference.pdf

2) readme_BPSK.txt

3) readme_OFDM.txt

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This dataset contains solar radiation data from Coto Laurel Puerto From May 20,2019 to May 19, 2020. Additional power ramp rate data is provided for seven different methods: Ramp saturation, first order low-pass filter, second order low-pass filter, moving average, exponential moving average, enhanced linear exponential smoothing, and predictive dynamics smoothing.

Instructions: 

The data is in .mat format. Please use MATLAB to access to it. Ramp rate data results are in the out.mat file. Daily data is available under the name of each PRRC method.

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This Matlab model and the included results are submitted as reference for the paper ''. 

Presenting a comparative study of the Sequential Unscented Kalman Filter (SUKF), Least-squares (LS) Multilateration and standard Unscented Kalman Filter (UKF) for localisation that relies on sequentially received datasets. 

The KEWLS and KKF approach presents a novel solution using Linear Kalman Filters (LKF) to extrapolate individual sensor measurements to a synchronous point in time for use in LS Multilateration. 

 

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The data provided here correspond to the TPWRS paper presenting a novel  filter design procedure to optimally split the Frequency Regulation (FR) signal between conventional and fast regulating Energy Storage System (ESS) assets, considering typical Communication Delays (CDs).  The filter is then integrated into a previously validated FR model of the Ontario Power System (OPS) including Battery and Flywheel ESSs, which is used to analyze the impact of these ESSs, CDs, and limited regulation capacity in the FR process in a real system.  The proposed methodology to split the

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