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At the end of the study, the Box Jenkins methodology was shown to be the optimal choice to forecast demand.
Overall, the methodology was shown to be highly applicable for the accurate determination of fiber properties from both unidirectional and woven systems.
Overall, the proposed methodology was shown to be efficient for ideal experiments, with a relative average error of <1% in both tests.
Earlier, our methodology was shown to be the most successful one as compared to the popular contemporary techniques for tracing relatively simple and primitive suite of applications contained within SPEC95 benchmark suite [1].
The computational power and efficiency of the methodology was shown by computing the in vivo stress and strain state, and the corresponding unloaded geometry, for two models containing multiple interacting incompressible, anisotropic (fiber-embedded) and hyperelastic material behaviors: a patient-specific abdominal aortic aneurysm and a full 4-chamber heart model.
Our methodology was shown to be especially useful in systematically identifying commonly reported genes and pathways in the heterogeneous disease of AML.
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This methodology is shown in details herein.
The strain-pole methodology is shown to work with similar martensitic transformations in other material systems.
The methodology is shown to yield property estimates that furnish simulations that closely match observed behaviours.
Implementation problems are addressed and the effectiveness of the methodology is shown.
Predictions obtained using the methodology are shown to correlate reasonably well with test data.
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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