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"Its boundless compass, including as it does, every state and non-state institution, as well as relevant institutional contexts, coupled with the absence of any built-in time parameters, does not fit comfortably or practically within the single inquiry model in which it currently resides.
The proposed parameter, unlike many other parameters, does not use an empirical fitting factor.
We have also observed that the changes in the parameters does not affect this inference.
The results demonstrated also that the precision of the calculated rheological parameters does not depend on the initial parameter values.
This fixation of parameters does not considerably change the coefficient of determination (( R^{2} )) of the regression analysis.
The computational results show that a change in the type of probability distribution of the stochastic parameters does not significantly affect the value of the stochastic solutions.
Therefore, a theoretical analysis that holds for all possible channel parameters does not allow to capture the particular structure of different practical settings.
Moreover, we conclude that the parameterization of the functional model with constant unknown bias parameters does not thoroughly remove systematic errors in the data.
Differentiating (14) with respect to the parameters does not lead to well-formed formulae, so we try to find a lower bound for (14) using Jensen's inequality (15).
In CNN, the number of free parameters does not grow proportionally with the input dimensions and therefore performs better in terms of many benchmarks.
However, altering the control points at the same time as the shape parameters does not affect the smoothness of the curve.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com