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In order to be able to incorporate the mutual electromagnetic influence of neighboring elements (e.g., cross talking), one needs refined models based on a sufficiently exact discretization of the full Maxwell equations.
The accuracy, convergence and effectiveness of the designed models are validated through statistical analyses based on a sufficiently large number of independent runs.
Validation of accuracy and convergence of the proposed scheme is made using statistical analysis based on a sufficiently large number of independent runs, this is done in terms of performance measures of mean absolute deviation and root mean squared error.
Although the control charts constructed in this study are based on a sufficiently inclusive cohort, it is desirable to calculate the universal control limits based on a more representative sample.
Given that the relevant non-normative premise must claim that intuitions of the sort at issue are more frequently false than true (or equally likely to be false as to be true) it seems to require an inductive justification based on a sufficiently large number of cases in which we have justification for believing ~p while p is the content of an intuition.
In contrast, our current finding is based on a sufficiently large enough cohort to offer complete confidence in the significance levels reported.
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Although the samples they are based on are limited, they are considered sufficiently reliable to guide an initial aid response.
In this paper the process has been simulated in detail with a one-dimensional pseudo-homogeneous reactor model (PHM) and a reduced model has been developed (computationally enormously much faster and still sufficiently accurate) based on a sharp front approach to simplify further reactor and process design and optimization.
However, it can be recommended that sufficiently large samples (based on a priori power calculation) should be assessed by two or more observers.
Schwarz does not sufficiently emphasize that this measure is based on a temporary, emergency budget for food.
The sufficiently comparable studies were combined into a network analysis based on a common comparator.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com