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The design has been optimized using a two-dimensional numerical device simulation program (TCAD-Silvaco).
The proposed methods have been optimized using a Box Behnken design of experiments.
The experimental parameters affecting the microextraction process have been optimized using a multifactor experimental design strategy.
Three LC parameters have been optimized using a multifactorial design comprising 29 experiments that includes 2 center point replicates.
The work has been carried out in two steps; firstly the parameters of hybrid dual channel semitransparent photovoltaic thermal module has been optimized using a fuzzyfied genetic algorithm.
These variables have been optimized using a central composite design obtaining response surfaces that describe this preparation method of nano-emulsions.
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The model enables the automated generation of inclusive and flexible ORC cascades and is optimized using a global optimization algorithm.
Based on this approach operation decisions are optimized using a multi-objective optimization model with a compound system's objective.
The model Equation 4 is optimized using a multistage Monte-Carlo optimization technique[43].
During the optimization step, the most relevant parameters of the screening were optimized using a central composite design meanwhile other factors were kept constant.
To this end, an extraction procedure was optimized using a Plackett Burman experimental design to determine the key conditions for optimal extraction of glucocorticoids from urine.
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