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Numerical simulations were carried out to illustrate analytical results.
Inspired by previous attempts, this paper aims to establish the clustering approach as a practical guideline to explore student categories and characteristics, with the working example on a real dataset to illustrate analytical procedures and results.
To illustrate analytical results, let us consider the following example: { x n + 1 = a x n + α tanh ( x n ) + β tanh ( y n − 2 ), y n + 1 = a y n + α tanh ( y n ) + β tanh ( z n − 2 ), z n + 1 = a z n + α tanh ( z n ) + β tanh ( x n − 2 ).
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Figure 18 illustrates analytical values according to Equation 16 depending on the distance between sender and receiver.
Figure 16a illustrates analytical results of temperature distributions through the wall thickness predicted from the wall models with and without considering moisture clog.
The duplicate experiments are included in Table 1 to illustrate the analytical sensitivity to sample selection (particle size) and analytical reproducibility with samples of uniform composition (aliquots).
Figures 15 and 16 illustrate the analytical WNRs and the comparison of the experimental BERs with the analytical ones, respectively.
Two examples illustrate the analytical results.
We illustrate our analytical considerations with empirical analysis.
Numerical examples are provided to illustrate the analytical findings.
Finally, we provide an analysis of an actual experiment to illustrate our analytical results.
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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