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We model this situation as a generalization of the covering tour problem, introduce the idea of split delivery, and propose an efficient heuristic approach to solve it.
However, we consider our attempt to model this situation to represent an informative thought as an experiment addressing the question of what forces the wing would be expected to produce if it could be held fixed with particular amounts of twisting at a range of β angle.
We model this situation by altering the net utilities of the players with a term which we identify with altruism.
Therefore, to model this situation correctly, the DFT with LDA and a double-ζ-polarized basis set were applied [22].
A typical way to model this situation is the linear logistic model: Pr ( y = 1 | x ) = 1 1 + exp ( - β ′ x ), (3).
Though we sometimes find that the reconstruction error on the right class in the JSR model is slightly smaller than the reconstruction error on the right class in the IJSR model, this situation tends to happen when the reconstruction errors on the right class are both remarkably smaller than the reconstruction errors on the wrong class.
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We propose modeling this situation as a scheduling problem, and then present specific heuristics for its solution.
As indicated by the Guideline on Air Quality Models, this situation may call for the use of two different modeling approaches for the same Class I area and source, depending upon the State's chosen method for modeling sources less than 50 km.
In conjunction with appropriate AI architectures and optimized machine "learning" models, this situation may eventually lead to an accurate imitation of the human brain on a much bigger scale.
In modeling this situation, we re-ran our method on the curated data set, using as filter vocabulary a subset of the publications in each individual's manually curated publication list.
Modelling this situation showed a reduction of stimuli in femoral condyles corresponding to sites of reduced proliferation and shape change and the replacement of a complex dynamic pattern of stimuli by a simplified, static environment.
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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