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For this reason, in this study, the values of variables obtained by polynomial model were transformed to images then an image processing method was performed to represent the relevant values of the variables as a single colour shade.
The coefficients from the logistic regression model were transformed into the components of a risk score.
All continuous variables entered in the model were transformed to be normally distributed and range from zero to one for the fifth and ninety-fifth percentiles of the healthy population.
The dependent variable and all continuous explanatory variables explored in this model were transformed into natural logarithms, as this specification resulted in a residual plot that best approximated a normal distribution – a requirement of OLS regressions.
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Step 2: The ODE model is transformed using the proposed linear transformation pattern.
This paper demonstrates a transformation practice where a Simulink model is transformed into a Function Block model in FBDK.
The rational model is transformed to a time domain model using inverse Laplace transformation.
The longitudinal model is transformed into the strict feedback formation.
The identified model is transformed into modal realization.
Then the block density model is transformed into a residual node density model.
Later, this dynamical model was transformed into controllable canonical form for position tracking control purposes.
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