Sentence examples for dataset can be explained from inspiring English sources

The high errors of both methods for low speeds on the Diepenbeek/Hasselt dataset can be explained by the fact that the low speeds mostly prevail in the busy city center, where the presence of other traffic degrades the results somewhat.

The lack of a significant 2nd chromosome QTL in the F2 BLUP dataset can be explained by the apparent equal and opposite non-additive effects of the two QTL found in the sons dataset.

This may have a direct impact on translation rate and may also induce metabolic responses deleterious for expression yield [38]. PLS modeling suggests that most of the variation in our dataset can be explained by codons for serine (AGC favored and UCU disfavored), threonine (ACG favored), and leucine (UUG favored).

These observations can be motivated by the following remarks: (i) The better verification accuracy for the test PTB dataset can be explained by the shorter temporal interval between the two acquisition times T 1 and T 2, compared to the temporal interval of 5 years in the ECG_ILSA database which is in concord with the observations in [ 14 ].

The better verification accuracy for the test PTB dataset can be explained by the shorter temporal interval between the two acquisition times T1 and T2, compared to the temporal interval of 5 years in the ECG_ILSA database which is in concord with the observations in [ 14].

The differences in model preference and performance seen between the simulated and the animal datasets can be explained by the noiseless character of the generated TACs.

The features observed in Figs. 8 and 9 suggest that, for the torsion versus PGTA and the torsion versus rocking correlations, the differences between these three datasets can be explained by local soil properties.

The ICC for a particular outcome can be described as the amount of variation in the dataset that can be explained by the variation between clusters.

If a-sites fill before h-sites, this implies that the dataset analyzed can be explained without the existence of an h-site.

This suggests that those experiencing IPV have a higher prevalence of HIV in this dataset, but that this association can be explained by precedent, common risk factors.

While we do not have the ground truth for the MS dataset, many of the selected genes can be explained based on current knowledge of disease progression.