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Covariates in the final model were selected by step-wise backward selection procedure.

Resolutions within the model were selected by convergence testing for maximum accuracy of results whilst conserving computing load.

The variables that were considered to be significant based on the univariate regression model were selected and analyzed by the multivariate Cox regression model.

Data for the model were selected according to a criteria function defined as the ideal process condition.

The input variables and parameters of the SVR model were selected and optimized by using a genetic algorithm.

Parameters and control variables in the parametric model were selected according to the design rules and the extended parametric map.

Independent variables for the multiple prediction model were selected as quartz content, packing density and concavo convex type grain contact.

The geometric parameters of the plate girder section model were selected to give the maximum VIV response.

Dimensions of the idealized model were selected based on analytical prediction of deposition in scaled versions of existing adult airway geometries.

Hydrogels tested in vivo with a subcutaneous implantation model were selected based on the results from in vitro degradation and growth factor release kinetics.

These two separation methods, in conjunction with the NAM model, were selected to form an integrated approach to assessing BFI in catchments.