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Significant factors were selected by using the stepwise selection method.
Variables have been selected by using stepwise backward selection.
Since we wanted information-rich cases, the informants were selected by using strategic sample selection [ 18].
The final model was selected by using the backward selection method in multivariable logistic regression.
Eight process parameters were selected by using a failure modes and effects analysis.
Optimum values of significant variables were selected by using univariate optimisation approaches.
The control parameters are selected by using root locus analysis, which guarantees the system stability.
The co-rotating TE22,6 mode is selected by using the in-house developed code GCOMS.
Lots of reaction routes are selected by using multi-objective programming.
Optimal number of training points are selected by using distribution adaptive sequential experimental design.
The increment value changed in the iteration procedure is selected by using the optimization method.
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