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As we know, QP-free (also called SSLE) method is a kind of efficient methods for standard nonlinear programs (see [16]-[13] [16]-[13]
After an introduction to main ideas of semi-infinite optimization, this article surveys recent developments in theory and numerical methods for standard and generalized semi-infinite optimization problems.
In the next three subsections we present comparison of methods for standard deviation estimation.
As for the labeling protocols, methods for standard gene-expression analysis are generally based on labeling from the 3' end, followed by detection with 3'-end probes.
Although there are multiple methods for standard setting, they can be broadly classified as relative (norm-referenced) or absolute (criterion-referenced) [ 27].
Table 1 shows results obtained using several other methods for standard error and confidence interval estimation, for three randomly selected subsample data sets and three 2-sample data sets.
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Forgy method is preferable as initialization method for standard k-means.
In this paper, motivated from QP-free method for standard nonlinear programs, based on techniques of perturbation and penalty function, we propose a globally convergent QP-free algorithm for NLSDP (1.1).
Several numerical experiments are carried out on fine computational meshes to demonstrate the accuracy and efficiency of the proposed method for standard benchmark problems as well as for unsteady, pulsatile flow through a curved, pipe bend.
It will be interesting to test the general applicability of this method for standard avidity assays by comparison with single-point and end-point avidity determinations.
Homogeneity should be assessed within the two trial sets that contribute to the indirect comparison using the same methods as for standard meta-analysis [4].
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