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An optimal control problem for the implementation of three different restoration techniques and their combinations has been formulated within a control vector parameterization approach.
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The parameter estimation model is a constrained dynamic optimization problem that has been formulated within an equation oriented control vector parameterization environment.
This is done by modeling them as MRFs with Gibbs energies, and a solution is formulated within a Bayesian solution.
The complete model is formulated within a thermodynamic framework at large strains and is proved to be thermodynamic consistent.
With this optimization method, a favorable droplet size of a nanoemulsion with reasonable polydispersity index was able to be formulated within a short sonication time.
The model is formulated within a thermodynamic framework, giving a physically sound format where the thermodynamic mechanical and chemical forces that drive the phase transformation are conveniently identifiable.
The theory is formulated within a proper continuum mechanics framework and it treats uniaxial and multiaxial stress states in a unified manner for arbitrary load histories.
The problem is formulated within a thermo-diffusive single-reaction model and leads for large values of the Zeldovich number β to a free boundary problem.
The bulk model is formulated within a thermodynamic framework at large strains, and it will be specialized and applied to cutting processes in steel production.
More recent concerns have focused on how the various theories of persistence can be formulated within a relativistic framework: can we sustain a distinction between temporal and spatial parts, or should we think in terms of spatiotemporal parts?
Notice that the identification result has been established thanks to the fact that the identification problem is formulated within a GPSM, taking advantage of this technique in its applications to control theory.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com