Sentence examples for distance in the database from inspiring English sources

If there was a mismatch, the current segment classification was changed to the appropriate segment to follow the previous one, provided that the measured distance was within the threshold of the new identity's reference distance in the database, otherwise the classification identity of the current segment was discarded.

This implies that the prediction effect of sequence homology approaches depends on the distance in the database, and is instable.

Likewise, empty coaching stock (ECS) movements between the depot and nearby stations in the network may also coincidentally match up with some of the reference distances in the database and have identities incorrectly assigned to them.

Applying a converse logic, Sippl reasoned that the frequencies of occurrence of structural features such as interatomic distances in the database of known protein structures could be used to assign a free energy (potential of mean force) for a given protein conformation.

The size of the group aims to remove the possibility of the existence of several plausible matches for cumulative group distance in the reference database.

In fact, given that the distance between SNPs with a polymorphic indel between them is on average shorter than the distance given in the databases (an indel in the Seattle SNPs and NIEHS databases is always represented by the long indel variant regardless of whether it is an insertion or a deletion), we underestimate the recombination rate.

This is the value of the minimum phylogenetic distance between the organisms in the database and the investigated strains measured by CVTree [ 31, 32].

When we retrieve top- k nearest neighbors, using indexing techniques alone, we were able to make the search speed 77% faster compared to the prevoius version of 3D-Surfer that uses linear Euclidian distance scan between the 3DZDs in the database.

This is likely to happen when a few visual words of SVT origin from the cluttered background, and the local SIFT descriptors of the query image may have high occurrences over these visual words, resulting in high Hausdorff distances to the database images which have the same foreground objects but different backgrounds.

The BFMatcher uses a descriptor in one data set (sample) and compares it to all the other features in the second data set (in the database) with a distance calculation (Hamming distance), and the closest match is returned.

The respective power function for the distance relationship expressed in Equation 3 is highly significant within the distance range of the database.