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Results show that the kinematic, diffusive and dynamic flow approximation provide least to highest accuracy, respectively, in recreating measured discharge.
Here we extend this existing picture using a refined approximation, provide a more general analytical formula, and show that in principle up to N(N + 1) / 2 segments can show up experimentally.
It is clearly shown that our sparse CCA based on rank-1 matrix approximation provide the best results for all SNR range and all observation length.
In addition, simulation-based evidence suggests that the TMDD model and its MM approximation provide similar results for both BW-based or fixed i.v. dosing and, thus, serve as an adequate model to guide dosing.
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Finally, Sullivan-type health expectancies use the observed prevalence of disability/health to approximate the true period conditions, a reasonable approximation provided that disability or self-rated health is stable over time or evolves regularly (Mathers and Robine 1997).
The reasons for providing only the right-tail large deviation approximation are (i) all of the above mentioned approximations fail to approximate the extreme right-tail probabilities and (ii) the FMCI approximation provides an accurate approximation for left-tail probabilities.
The numerical analysis of the approximation provides criteria for stability and convergence.
The approximation provides a detailed understanding of the modeled fire regime.
Boundary layer approximation provides the dependence of the statistical moments of the RTD on Péclet number.
The spline approximation provides continuity of displacement and stress components within each yarn and matrix subregion.
The studies indicate the proposed approximation provides a very accurate solution for systems with a good voltage profile.
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CEO of Professional Science Editing for Scientists @ prosciediting.com