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The prediction of the cooling parameters is based on the numerical solution of the critical heat flux (CHF) model.
The identification of the input parameters is based on both classical engineering equations and statistical analysis of collected data.
An approach for optimizing the biosensor parameters is based on the availability of mathematical model of a catalytic biosensor (bioelectrode).
The proposed algorithm of identification of the six ship model parameters is based on the combination of two sub-algorithms: the backstepping procedure and the tuning design method.
The estimation of the parameters is based on real bispectral index scale surgical data and it is performed by using genetic algorithms.
The design of the matrix of stabilization parameters is based on the identification of the stability deficiencies of the standard Galerkin method applied to these two problems.
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We considered variable mutation rates amongst loci, and the Mij and θi starting parameters were based on FST and Ne calculations, respectively.
This model is also free of empirical fitting parameters, being based on pure flow physics scaling.
The model parameters are based upon the member sizes, properties and connection designs.
The statistical parameters are based on the available literature, test data and load surveys.
The model parameters are based on local conditions in the Leipzig area.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com