Sentence examples for performance of the method with from inspiring English sources

We illustrate the performance of the method with several numerical examples.

First we demonstrate theoretically how this approach works, test the performance of the method with a range of computer simulated image series with varying flow dynamics.

We apply our method to trimmed and untrimmed NURBS structures and illustrate a good performance of the method with benchmark test models and a shell model from engineering practice.

The performance of the method with respect to speed and accuracy is compared to a general-purpose Bulirsch-Stoer scheme for a variety of non-linear equations, and the results indicate that the method is a viable and attractive alternative to standard numerical integration.

Nevertheless, our proposed usage of textural features, particularly the BSIF-TOP, still surpasses the performance of the method with deep object features when iDT is the base feature.

The final bar depicts the performance of the method with all filters applied.

Further tests have been performed to assess the performance of the methods with different measurement types and configurations.

Based on NetRank, NetScore, and F_Flow, the performances with different swapping percentages were inferior compared with the performances of the method with RWR. Figure 3A illustrates the performances of the DDA score based on different prioritization methods with different thresholds of edge swapping.

We illustrate the performance of the methods with examples of four different data sets.

However, the stronger performance of the methods with learned parameter(s) suggests a small performance gain can be realized from the added effort of tuning a query to each data set.

First we use the original formulation of the problem by Dasika and Maranas [ 17] with a maximum of two promoter-transcript pairs, and compare the performance of the methods with the published results.