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In this paper, we present a heuristic method to select a near-optimal subset of measurement locations starting from a particular set of measurements, by minimizing the sensitivity of the parameter estimates with respect to observed response.
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By minimizing the energy function, composed of the sensitivity, color, coherence, and smoothness terms, the proposed algorithm obtains accurate segmentation results.
The best statistical cut-offs were calculated by minimizing the distance between the point with sensitivity = 1 and specificity = 1 and the intercept on the ROC curve.
A sensitivity-based model updating approach is applied to identify the local damages by minimizing the difference between the measured response and the reconstructed response.
They travel efficiently, by minimizing the distance they travel.
Friction Minimize friction on the axle by minimizing the contact surface area.
Its application minimizes the sensitivity of similarity to dipping reflectors with no apparent link to faulting by aligning adjacent trace segments with lag time.
We expect that many of the SNPs that affect computational gene structure reflect a biologically unrealistic sensitivity of the gene prediction algorithm to sequence changes, and we propose that genome annotation algorithms could be improved by minimizing their sensitivity to natural polymorphisms.
In particular, these biomarkers typically each depend on a number of physiological factors that when altered by tumor therapy may lead to opposing effects on the biomarker response, thereby minimizing the biomarker sensitivity to therapy.
A two-stage masking procedure was used to maximize sensitivity while minimizing the multiple comparisons problem.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com