Sentence examples for domain validation from inspiring English sources

In the safety critical domain, validation of models and testing of code increases the quality of the products altogether.

However, in order to use virtual environments in the thermoception domain, validation of these environments as adequate representations of physical environments (built environments) is imperative.

Easy support for domain validation must be available in Web services development frameworks.

This method is also known as domain validation.

We also confirmed geographical and domain validation of CURB-65 in our patients, which comprised an external validation in a different geographical area and in a population including a different category of patients from CAP. 4 The utility of serum CRP as a prognostic marker has been found to vary.

Each of the test cases includes the following information: component description and parameterization data; modelling hypotheses and simulation results; fundamental equations and correlations, with their validity domains; model validation, and in some cases, experimental validation; and single-phase flow and two-phase flow modelling equations, which cover all water and steam phases.

Correlation measures that evaluate the test or finite element model (FEM) frequency response data directly with the reduced impedance matrix are used in the frequency domain model validation.

In time domain, the validation of the results with the real recordings will be carried out using kurtosis [19].

63 'Good practice statements' have been developed for each domain and validation feedback from government officials has been received.

In the domain of validation or assessing the psychometric properties of pain scales, previous studies have demonstrated that a sample of 150 is acceptable and the type of analysis employed is also acceptable [ 6, 13, 14].

Our reasons are (1) Affymetrix is the common platform used in our three training datasets which ensures the inclusion of the entire set of our 56 genes; (2) the data preprocessing procedure is standardized; (3) existence of many datasets in the public domain for validation and (4) high reproducibility.