Sentence examples for model after adding from inspiring English sources

The elastic foundation is considered as a Pasternak model after adding a shear layer to the Winkler model.

C) Pseudosection plots of apparent resistivity difference between original and PHO-2 model after adding synthetic site in the center of the island.

Let (w^(theta _{max } )) be the vector of priority weights of attributes obtained from the minimax DEA-based GRA model after adding the set of constraints (16).

The incremental value of MSCT-CA was determined by calculating the change in global χ2 with respect to prognosis (Cox model) after adding the MSCT-CA variables to the pre-imaging information (Morise score) and significant calcium score (CACS > 100).

In order to approximate σ e limiter 2, let us first define another symbol vector consisting of all possible data symbol and pilot symbol combinations, defined as s comb, 2 = ( 1 - 1 / N c ) ( 1 - γ ) d l + γ p l, where the power scaling factor 1 - 1 / N c is used to ensure that the total probability over the grid model, after adding Gaussian noise modeling the cyclic mean, equals to unity.

Interaction terms were included in the model if they were statistically significant and remained so in a stable model after adding other covariates.

Patrick et al. reported both effect estimates and a measure of prediction (the c statistic) for the original ("Model 1") model and after adding the "introduced variable" (i.e., glaucoma diagnosis) ("Model 2").

The model is then applied within a Monte-Carlo simulation framework after adding stochasticity to input variables.

To explore to what extent seasonal variation could be a confounder, we also calculated R values of the models after adding seasonal variables (sine and cosine terms) and R values for seasonal terms alone.

In Model 3, after adding medical conditions and hand grip muscle strength to Model 2, the association between two or more falls and MMSE score remained statistically significant (estimate =−0.46, standard error =0.19, P=0.0161): a decline of 0.46 points per year compared with those who did not fall.

The performance of the SVM based models increases after adding a feature of length along with compositional vector.