Sentence examples for representations perform from inspiring English sources

Second, there are regulatory requirements that are much more complex than the ones used in the experiment in this research; how the different types of representations perform on these significantly complex requirements still need to be investigated.

This work is a comparative study of the chosen image representations, and it is beyond the scope of this article to explain why certain representations perform better than others in certain situations.

To what extent are these representations performing the past, turning it into a new experience that transforms our original records?

The same calculations and graphical representations performed for the Nouna CBHI (Tables 4– 5, Figure 2) could be computed for subgroups of the sample by important covariates such as place of residence (dummy variable coded 0 for Nouna villages and 1 for Nouna town) or education (dummy variable coded 0 for no education and 1 for some education).

These DOA estimation methods based on the sparse signal representation perform higher resolution than the conventional methods without requiring the number of sources.

A.F. collected the orthologue groups across 36 species with sufficient structural representation, performed the structural analysis and determined the interaction propensities across orthologues.

The graph representation performs better than standard graph representations for those cases when the rules of geometric locality and uniform element distribution around nodes are violated.

Table 4 shows that attribute-based representation performs better for predicting length and draught; nevertheless, it performs slightly worse for gross tonnage and summer deadweight.

Though generic vessel representation performs reasonably well, trained deep models which focus on specific attributes are significantly better in attribute categorization.

A 109-dimensional output-based generic representation performs the best in this experiment, since it is specifically designed for learning vessel types.

LDA-based representation performs better in identifying close homologs (SAS threshold of 2 Å) than the remote ones (SAS threshold of 5 Å) for a given query protein.