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The performance pattern of OMP is very similar to SBL (Fig. 13): both methods are good at handling materials with an insignificant specular component (e.g. #10, red-specular-plastic).
Because both methods are good choices, i.e., projection is the second choice and parent medium is suggested in [13], hence each method is assigned a probability 0.5 to be chosen for execution.
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Vilkman et al. conducted a test-retest analysis of 11C-FLB 457 PET scanning with 7 healthy volunteers (mean age ± SD = 29.0±6.9) and suggested that coefficient of variation (COV) of each extrastriatal region in BPND_Logan and BPND_SRTM methods was about 20% and the reproducibility of both methods was good [51].
The level of agreement of both methods was good for anti-CL IgG, moderate for anti-CL IgM, very good for anti-β2 GPI IgG, and moderate for anti-β2 GPI IgM (kappa = 0.641, 0.507, 0.803 and 0.506, respectively).
Within the same session, reliability of both methods was good to very good (ICCs from 0.73 to 0.96 with 95%CI from 0.50 to 0.99 and SEM from 0.9° to 2.4° with 95%CI from 0.7° to 3.2°).
The test-target methods are good tools for camera characterization.
Finite element methods are good compromises with high flexibility.
"I think his methods are good and he knows what he wants.
Research shows that fuzzy classification methods are good choice to cope with the above-mentioned issues.
The similarity-based big data reduction methods are good choice for network extraction and reduction.
Tree-based ensemble methods are good candidates for that purpose.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com