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Figure 4 shows the average percent difference between the estimated indices and the true indices for several different combination of filters.
For the historical problems tested, the average percent difference between CPGEA solutions and the lower bound is 0.67%.
For the WLAB studies, the average percent difference between the Monte Carlo- and Acuros-generated scattered photon fluences at the face of the detector was -0.7%.
It was found that, although there was a percent difference of about 14% in the average segmentation quality between methods, this was translated into an average percent difference of only 4% in the classification performance.
It is shown that the modified Kunii Levenspiel model accurately predicts the no catalyst addition and copper catalyst addition experiments of the hydrochlorination fluidized bed with an average percent difference of less than 6%.
For the left side, Scenario 2 on average performed with the greatest amount of accuracy with an average absolute difference of 2.29 mm, an average percent difference of 0.16%, and a standard deviation of 1.90 mm.
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After including the detector response, the average percent differences between the Monte Carlo- and Acuros-generated scatter fractions (SF) were -0.1% without the grid and 0.6% with the grid.
The average percent differences across all four days were 20.9% and 19.7% for the first 5 min and middle 5 min, respectively.> -wrap-foot> (Mean ± standard error).
The average percent differences in residue identity (and SDs) between native and full consensus sequences were: 65 (±14) for MR-full, 54 (±16) for MF-full and 51 (±17) for MET-full consensus sequences.
Mean percent difference is −3.2%%.
The average percent of difference to GS for all overestimated values for each group was calculated and expressed as the mean ± SD.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com