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Existing design approaches to consider this system are either too simplistic resulting in loss of accuracy or significantly complicated Finite Element Analysis demanding expensive highly skilled manpower.
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Stand-off analysis demands the most stringent requirements on instrumentation.
Rather than composing knowledge from various independent components, this analysis demands instead that the epistemic states are related to one another in substantive ways.
The growing interest in contextual analysis demands standardization of the definitions as they apply to adolescents, followed by correct usage of the terms.
While the analysis demands good preparation to meet the purpose of each specific Foresight (e.g. adjust the focus of the data analysis, defining the appropriate hashtags etc)., the analysis itself can be done within a couple of days, or, depending on the goals of the analysis, even hours, due to its semi-automated nature.
Global gene expression analysis demands microarray platforms with a high genome coverage.
The result of this analysis demands for further investigation to validate and to justify.
This analysis demands the most statistical power and therefore, we calculated the sample size based on this analysis.
It needs to be emphasized that including multiple exacerbations in the analysis demands accounting for dependency on the patient level and the inherent correlation of paired data.
Furthermore, users need extensive training in operating the programs and interpreting the results, and Bayesian analysis demands for rather extensive data entry which may not be feasible in daily clinical practice.
Similarly to the finite element method, isogeometric solution of complex engineering problems may lead to computationally very demanding analysis, demands of which can be alleviated by performing it in a parallel computing environment.
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CEO of Professional Science Editing for Scientists @ prosciediting.com