Howrigan et al. [ 11] found that the numbers and sizes of ROH that are identified in genotyping data can strongly depend on certain parameters and thresholds imposed during sequence analysis.
Type and magnitude of such effects depend on certain parameters, e.g. choice and order of exercise, intensity, number and length of sets, time under tension and rest length period [ 20, 21].
On an industrial production line, distinct tasks can be assigned to be processed by different machines depending on certain conditions and production parameters.
By using a sub-supersolution approach and a mountain pass theorem, Giacomoni et al. [13] proved, among other things, that when (h(x equivlambda), (k(x equiv1), (0depending on certain value of the parameter λ).
The problem is modeled in the framework of optimal control under stochastic uncertainty, where the process differential equation depends on certain random parameters having a given probability distribution.
With digitized text material, where OCR quality or human readability depends on certain image parameters like contrast and sharpness, the use of quality metadata will provide good automated optimization results without overprocessing the digitized text (like halos around letters that occur due to oversharpening) [57].
The magnitude of the splicing-induced enhancement appears to vary from gene to gene [10], and may depend on certain genomic parameters, such as the length and position of introns in the unprocessed transcript.
The paper shows that the separated structure of parameter dependencies within the Polytopic Tensor-Product (TP) model can be exploited during the controller design by applying controller candidates that depend only on certain parameter sets.
Since our method is based on Richardson's method for solving systems of linear equations (Bertsekas & Tsitsiklis, 1997), its convergence rate depends on certain scaling parameter and a preconditioning matrix.
