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The proposed model formulates a set of displacement and force compatibility conditions between the various subdomains.
Markov Random Field (MRF) model formulates the problem of dense matching as a Bayes decision task.
A mathematical model formulates the feature selection approach and it is solved by binary particle swarm optimization (PSO).
The proposed model formulates the distribution of these random variables as the conditional distribution of route flows given the observed link flows and the SUE principle.
Accounting on standard proportions of gears and transmission characteristics of drives, the proposed model formulates a computational design problem by means of a few linearly independent global variables.
The proposed model formulates the distribution of these random variables as the conditional distribution of route flows and origin destination (O-D) travel demand, given the observed link flows and the SUE principle.
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The dynamic Smagorinsky model formulated by Germano et al. was used to model the subfilter scales.
The model formulated is an error posture model, that depends on current and reference posture.
Secondly, an optimization model, formulated to specifically address the discussion comparing both configuration paradigms.
Dynamics of the cylinder was described using the mathematical model formulated by E.W. Gerc.
The compositional profiles were analyzed with a diffusion model formulated for a polydisperse system.
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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