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Using a "moving window" procedure, we delimited smaller 5 km × 5 km grids in 16 possible positions within the larger grid.
To calculate the CC features, the Hanning window procedure was applied to each analysis window of the EMG signals.
The sliding window procedure divides a sequence in a number of overlapping subsequences.
As Tilemap is based on a statistical model that incorporates the replicate data, it is a more solid approach than a simple sliding window procedure.
We used a sliding window procedure to extract the core haplotype associated with the trait, starting with six polymorphisms haplotype analysis and reducing the window on selected and significant haplotypes only.
Here we present a new machine learning approach to identify potential T3SS effectors by their N-terminal amino acid sequence using a sliding window procedure in combination with artificial neural networks (ANN, feedforward type) [16] and support vector machine (SVM) classifiers [17], together with a comprehensive prediction of potential T3SS effectors for 918 bacterial genomes.
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Many techniques are based on sliding window procedures that compare the topology of one segment against neighboring segments or the whole alignment.
The optimization model is solved using Genetic Algorithm and implemented using a moving-window procedure.
In order to mitigate the spectral leakage effects as well as to improve the accuracy of damping ratio estimation the windowing procedure was adopted with a selected number of samples LN, determining the duration of a window function.
Based on these results, the quality of the analytic signal obtained via HT can be improved by implementing a windowing procedure (Fig. 3): Open image in new window Fig. 3 Windowing procedure, the gray portions will form the analytic signal or instantaneous parameter time history for the whole dataset 1. Divide the signal x t) into M segments of equal length N. 2.
Parameters of the windowing procedure: the window size to estimate the background baseline DC: the grouping spatial window size to convert sub-pixel target velocity to the pixel target velocity in the frame (as an input to the DPA). the size of the short-term variance windows for each sample and for each grouping.
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