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where is large enough such that (32).
Let be nonnegative on, where is large enough.
Define, where is large enough so in and (3.34).
Therefore, the current part around time is not similar to segment, where is large.
Performance of the covariance diagnostic is demonstrated further in Table 1, which shows close correspondence between the proportion of simulations where the diagnostic is negative and the proportion where is large.
Similar(55)
This scheme samples sparsely in relatively uniform areas and more intensively where variation is large.
A drawback of the method is over-sharpening image regions where there is large illumination variation.
end{aligned} where (q>0) is large enough and (lambda>0) is small enough.
To offset the additional complexity, we focus on the case where n is large.
To offset the added complexity, we again focus on the case where n is large.
However, in those areas where (theta _s) is large, the predicted values diverged from the measured values.
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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