Sentence examples for mean features of from inspiring English sources

Morphological analysis and fracture surface analysis were performed by means of Optical Microscopy and Scanning Electron Microscopy to evaluate the material flow produced under different processing conditions as well as the mean features of the joints.

The mean features of co-composting products are presented in Table 1; the final products presented a C/N ratio of around 10, NH4 +/NO3 − ≤1, which provides information on the importance of organic matter oxidation and a significant degree of stability of substrate.

This was due to the fact that all simulated series were generated by the same set of parameters, in order to reproduce the mean features of experimental series.

We propose that the feature of a particular class if brought similar/closer to the mean feature of that class can help in learning class-specific representations.

The mean feature of PHT is sub-gluteal pain occurring during sport activity, stretching or in a prolonged sitting position, which can radiate down to the posterior thigh till the popliteal fossa.

A high prediction accuracy is achieved in an extensive comparison with classical experimental data, covering not only the mean feature of the flow and transient bubble dispersion patterns, but also the second-order statistics of the liquid which is vital in assessing a closure model and has not been enough addressed in the past RANS-based studies.

*Focal; **Big, but focal - = absent; + = barely present; ++ = moderate; +++ = severe Semiquantitative analysis of renal damage representative of mean features, obtained for each group of rats.

Comparing the quantile features to the mean features, the performance of the quantile features is better and more stable than that of the mean features no matter which classifier is used.

where is the number of clusters, is the mean feature vector of th cluster, is the number of the features that belong to cluster, and is the covariance matrix of cluster.

where μ is the overall mean feature vector of the pixels in R c ⋃ R s.

In particular, all features in the dataset and the (mean) feature value of the currently selected element are presented.