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In that regard our method resembles the work of McGuire et al. [25].
This management method resembles the practical design flow and is therefore intuitive to the designer in the decision-making process.
It is shown how the proposed design method resembles the solution of a competing H∞ design and offers the ability to interpret H∞ centralized control solutions, and understand the tradeoffs inherent in such a design.
It is shown how the proposed design method resembles the solution of a competing H∞ design and offers the ability to interpret H∞ centralized control solutions understanding the inherent tradeoffs of multivariable feedback control.
(Noorman et al. 2017) With this focus, the Lean method resembles the experimental approach to innovation, described as continuous testing and learning by means of gradual scaling-up, while a technology is introduced in society (e.g. Asveld, 2016; Robaey & Simons, 2015; van de Poel, 2011).
Summarised, the GM method resembles the idea of the BG algorithm (see Section 2.3.2), although no building of new logical integrities from previously found correspondences takes place here, and consequently no M N, M > 1 correspondences, i.e. no matches for complete routes are constructed.
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In addition, our results showed that the gene expression dynamics of specific PGC markers, such as T, Fgf8 and Sox17 in the EB method, resembled the expression of in vivo markers more closely than the markers observed using the attachment culture technique (Fig. 3A).
The average values of the estimated parameters by the bootstrap method resembled the final estimates of the population PK parameters (Table 4).
In this the introduction of these renormalization group methods resembles the way in which the need to an atomistic account of macroscopic thermodynamic behavior itself required the new methods of statistical mechanics to be added to the older repertoire of typical dynamical explanations.
It is worth pointing out that although the adaptive Algorithm 1 for multi-moment-matching PMOR methods resembles the greedy algorithm that is often used in the reduced basis method [6], the size of the training sets we used in numerical tests, which is 20 in all three examples, is much smaller than that typically used in reduced basis methods, which can easily reach 1,000 or even 10,000.
The method resembles that of the good butcher who knows how to cut at the articulations or the good tailor who knows how to sew pieces of cloth together into clothes that fit.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com