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The three methods shared a total of 1,352 spectral identifications in the EC HCD data set and 607 spectral identifications in the EC ETD data set.
When the disequilibrium was absent in either of the populations (populations 1 6), all three methods shared a low probability of making false positive inference using case and control samples from these populations separately (Table 4).
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But all these methods share a problem.
All of the DTN routing methods share a similar characteristic, the 'store-carry-forward' fashion.
These methods share a common feature that high growth temperatures (>500°C) and costly equipments are usually necessary.
Most FR bottom-up quality assessment methods share a similar framework known as the error-visibility paradigm [1].
Although these methods share a common transform domain workbench, they differ to the type of the orthogonal polynomial basis used as kernels in constructing the moment coefficients.
As representatives of the background subtraction approach, these four methods share a common overall structure: they keep a background model that is built when the scene does not contain objects of interest.
All of these methods share a considerable percentage of recurrence.
All methods share a bias problem which makes the confidence intervals based on asymptotic normal theory not fully accurate.
All of these methods share a family resemblance: a norm is established for a sequence characteristic, and genes or genomic regions are sought that deviate from the norm.
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