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Tables 5 and 6 present the results of the statistical models converted into points to facilitate the assessment of the 1- and 2-year risk of becoming a daily smoker, respectively.
Optimal mathematic model is converted into unconstrained mathematic model using penalty function method.
To calculate FSC between model and map, the model was converted into a density map in Chimera, which was resampled to the grid of the map used for refinement.
The model is converted into a two-stage model keeping the calculation logic.
The uncertain multi-objective optimization model is converted into deterministic multi-objective model including left, center and right interval functions.
Therefore, the neural space model was converted into a mathematical space model.
Essentially, the time domain mathematical model is converted into a space domain model with the curvilinear abscissa s as the new independent variable and the inequality constraints (5) are converted into penalties to be added to the cost function (12).
The proposed model is converted into an equivalent auxiliary crisp model.
Subsequently, this model is converted into a structural and aerodynamic model for analysis purposes.
A mixed integer nonlinear programming (MINLP) model is converted into a nonlinear programming (NLP) model, and solved in combination of enumeration for a few remaining binary variables.
Then, while the NLP optimization reveals local optima, the NLP model is converted into a linear programming (LP) model using linearized AC power flow equations.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com