No abstract

We have developed a method to analyze in detail, translocation events providing a novel and flexible tool for data analysis of nanopore experiments. Our program, called OpenNanopore, is based on the cumulative sums algorithm (CUSUM algorithm). This algorithm is an abrupt change detection algorithm that provides fitting of current blockages, allowing the user to easily identify the different levels in each event. Our method detects events using adaptive thresholds that adapt to low-frequency variations in the baseline. After event identification, our method uses the CUSUM algorithm to fit the levels inside every event and automatically extracts their time and amplitude information. This facilitates the statistical analysis of an event population with a given number of levels. The obtained information improves the interpretation of interactions between the molecule and nanopore. Since our program does not require any prior information about the analyzed molecules, novel moleculenanopore interactions can be characterized. In addition our program is very fast and stable. With the progress in fabrication and control of the translocation speed, in the near future, our program could be useful in identification of the different bases of DNA.

Abstract-A new method for voltage dips and swells analysis is presented in this paper. This method is based on the space vector representation in the complex plane and the zero-sequence voltage. Indeed, in the case of nonfaulted system voltages, the space vector follows a circle in the complex plane with a radius equal to the nominal voltage. It follows the same shape for balanced dips, but with a smaller radius. For unbalanced dips, this shape becomes an ellipse with parameters depending on the phase(s) in drop, dip magnitude and phase angle shift. For swells the space vector shape is not modified, though the zero-sequence voltage presents significant changes in its phase and magnitude and can be used for swells analysis. The changes in the space vector and the zero-sequence voltage are used to determine the dip/swell time occurrence, to classify and finally characterize the measured power-quality disturbance. Algorithms are developed for each step of this automatic voltage dips and swells analysis (segmentation, classification, and characterization) and are validated on real measurement data.