Sentence examples for degree of data and from inspiring English sources

The results have proven that techniques of porosity permeability crossplot and FZI have severe scattering degree of data and poor capability for identification of flow units of shaly sandstone reservoirs.

"We bring a high degree of data and underlying prediction intelligence to bear, to know which users to go after in their native environment – be it phone or tablet, iOS or Android," says Ellis. "Customers pay us on more of a cost-per-action rather than a cost-per-install basis".

Several important milestones have been reached recently towards the goal of a higher degree of data and information exchange among providers and consumers.

Although the maximum degrees of data and model are not strictly correlated, tests showed that higher L generate small-scale artefacts in the inversion results, but do not increase the resolution of the anomalous structures.

It is thus apparent that no method of dealing with missing data is appropriate under all conditions, and the best approach will depend on the degree of data missingness and the structure of the underlying missing data – correlations of missing covariate and outcome data.

Comprehensive experiments on several real datasets are used for performance assessment, including quantitative evaluations to measure the degree of data reduction and the distortion of reconstructed images.

This is in conformity with [7], stating that a certain degree of data quantity and accuracy are to be fulfilled for SMAA application.

The RQI is calculated using data of Table 1 and plotted versus ratio of pore volume to grain volume (φz) on a log log figure, as shown in Fig. 3. Figure 3 describes a severe scattering degree of data points and unsuitability to define flow units.

This RQI log log plot is based on obtaining a straight line characterizing single flow unit, but the final result still shows high scattering degree of data points and incapability to delineate flow units for shaly sandstone reservoir under investigation, Fig. 3.

This strategy turns out to introduce a hidden bias towards sick patients because sicker patient have records with a higher degree of data sufficiency and are more likely to be included in EHR-based studies; therefore, this selection process biases the study populations towards those comprised of sicker patients.

Providing reliable, efficient individualized patient support requires a degree of mastery of data and coordination with increased use of ICTs.