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After a long campaign of simulations and comparisons, two short binary LDPC codes have emerged as the most attractive candidates.
For comparisons, two objective measures, peak signal-to-noise ratio (PSNR) and structural similarity index measurement (SSIM) are used to evaluate the performances of the super-resolution algorithms.
Three pipeline biofilm samples were chosen for these comparisons; two contained crude oil and corrosion products and the third transported seawater.
The classifier complexity on this stage is usually very low (only one or two features are considered; the decision is made of one to comparisons, two multiplications, and one addition).
Based on our numerical tests and comparisons, two practical adaptive thinning algorithms are proposed for thinning large data sets, one which is more accurate and another which is faster.
The relative weights are given by right eigenvector (w) corresponding to the largest eigenvalue ((lambda _mathrm{max})), as: begin{aligned} Pw=lambda _mathrm{max}w end{aligned} (1)To ensure the consistency of subjective perception in pairwise comparisons, two indices, consistency index (CI) and consistency ratio (CR) are suggested.
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In these comparisons, two thousand permutations were used with FDR set to <10% for all comparisons except when comparing the 24hrLS to the 48hrLS for which FDR was set at <14%.
Four electrodes were used for target comparisons, four were used for distractor comparisons, and eleven were used for control comparisons.
Among nine comparisons, five were eligible for the trend estimation.
Bonferroni correction was applied for multiple comparisons (seven tests).
Starch (four comparisons), glucose (two comparisons), galactose (two comparisons) and sucrose (one comparison) were the comparators.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com