Sentence examples for user defined thresholds from inspiring English sources

A detection algorithm is introduced which isolates the shock-structures in the temporal waveforms based on a pressure rise time and shock strength that satisfy user defined thresholds.

CNVs are defined using numerous one-size-fits-all user defined thresholds (see methods) and may therefore be susceptible to CNV call reliability fluctuations according to data quality.

A predicted insertion/deletion is considered as a match to a true insertion/deletion if the distance of their center points and their length difference are below user defined thresholds.

The SNV caller does not make assumptions regarding the ploidy of the data but rather makes use of the allele information that is generated based on the user defined thresholds.

Additionally, there are only two user defined thresholds (the characteristic length parameter (2 MB default) and Log-Bayes Factor), which serve to reduce the false positive error rate at differing stages of the analysis [ 52].

This constraint tests whether the Katz centrality of a node is greater than the user defined threshold value or not.

The ANN implementation in OpenCV supports two stopping criteria, reaching a predefined maximum number of epochs or a decrease in training set accuracy between two consecutive epochs below a user defined threshold.

The algorithm used for this study (EXTERIORPTS in SOLO + MIA) uses the extremes of the mean-centered one-norm data as initial guesses based on a user defined threshold for the minimum norm value (a low threshold was used in this study to guarantee that contributions for low Z elements and paints used marginally would be extracted).

Now, for this feature we compute feature-feature mutual information with all the features that are already been selected as optimal features and if the feature-feature mutual information of that feature with all other selected features is less than a user defined threshold say, (alpha ) then the feature will be selected.

We perform clustering of optical flow vectors with magnitudes above a user defined threshold.

Those substrings whose score is over a user defined threshold t are then declared as ncRNA candidates.