This dataset is in support of my 2 research papers ' '.


  • Part I :  
  • Part II : 

Related Claim : Novel ß Non-Linear Theory,  Novel ß Solar Boost Converter and Novel ß Power Boost DC-DC Converter  in Patent 'Novel ß 10-Axis Grid Compatible Multi-Controller' 


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.


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


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.


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.


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.


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.


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. 



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


In order to obtain the constants of our PID temperature controller, it was necessary to identify the system. The identification of the system allows us, through experimentation, to find the representation of the plant to be able to control it.

The first data with name "data_2.mat" represent the open loop test, where the sampling frequency is 100 [Hz], this data was useful to find the period of the pulse train generator, which is twice the slowest sampling time analyzed between the high pulse and low pulse of the input.