Sentence examples for approaches cannot handle from inspiring English sources

However, these approaches cannot handle dynamic backgrounds and are sensitive to threshold values.

Because the cross-validation approaches cannot handle data with missing values, we ran this analysis on only a subset of the full data set that excludes missing values; the results of running our full model on this data set are qualitatively identical to the results from running the full model on the original data set.

But their approach cannot handle the uncovered areas caused by static foreground objects.

However, these mentions were neither counted for javax.swing.text.html.parser.Element class nor for javax.swing.text.Element interface, since our approach cannot handle with name ambiguity.

Although the current approach used by the WLCG employs the same pre-transformation approach, it performs inadequately compared with the new approaches presented in this paper, primarily due to database communication and scalability constraints as the current approach cannot handle the increasing data and workload.

However, such an approach cannot handle long range dependencies because as o increases the search space becomes intractable.

In addition, they basically implement the Lander-Green algorithm (Lander and Green, 1987), which enumerates all inheritance patterns; therefore, their approach cannot handle large pedigrees.

Crucially, these errors occur not because the data lack the spatial resolution to distinguish between the two areas correctly but because the conventional inferential approach cannot handle its complexity.

However, by uniformly partitioning chromosomes into segments with a fixed segment length, their approach cannot handle segments with recombinations.

Usual perturbative approaches usually cannot handle reliably (or at all) systems with initial states that are open shell and/or highly correlated (non-dynamical correlation) for either IPs or EAs.

Since the concept of high utility pattern mining was proposed to solve the drawbacks of traditional frequent pattern mining approach that cannot handle various features of real-world applications, many different techniques and algorithms for high utility pattern mining have been developed.