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Results show that all experimental Sherwood numbers occur between the two models, which gives credence to the measurements.
Even the scale of impacts may vary, the list of significant factors and their signs are matching in two models, which gives a confidence in the original dataset.
To this end, we first define a suitable sequence of microscopic models, which gives the connection between the defining objects of the Wilson Cowan equation (1.3) and the microscopic models discussed in Sect.
A review of the literature shows that the Hidden Markov Model (HMM) adopting the sliding window approach are the mainly used models, which gives good results when a relevant feature-extraction process is performed.
An analysis of graded amplitude is also provided based on Fourier envelope equations of beam/foundation models, which gives an insightful understanding of these fading wrinkles that differ from the ones usually observed in rectangular geometric cases.
It is a pseudo-scientific set of theories and models which gives primacy to the abstruse at the expense of the known.
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Thus, it is important to obtain process models which give a satisfactory description of gain directionality.
Their relationships are modeled by graphical models which give explicit factorization of a high-dimensional joint probability distribution.
The prediction of CCD experiment was verified by neural network models which gave almost similar results to those determined by response surface models.
This is a shortcoming in many contemporary SA models, which give less priority to intentionality as a driver of human-dominant situations [2, 5, 7].
When the actuators are perturbed simultaneously this approach yields models which give a satisfactory description of the high-and low-gain directions.
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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