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DFA minimization is an important problem in algorithm design and is based on the notion of DFA equivalence: Two DFA's are equivalent if and only if they accept the same set of strings.
In this paper, we propose a new notion of DFA equivalence (that we call weak-equivalence): We say that two DFA's are weakly equivalent if they both accept the same number of strings of length k for every k.
Consequently, we first evaluated the sensitivity of the two DFA assays independently against 230 B. anthracis isolates.
The two DFA assay positive/PCR-negative specimens indicassay positive/PCR-negativel available aspecimensspecindicatey maximize diagnosthatsensitivity.
Figure 1C shows that clusters were formed for the two subpopulations along CV1, but the clusters had some overlap and were more spread out than for the first two DFA models.
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We calculated the two DFAs to investigate whether high classification values are due to sex differences or to mere individual differences.
Additionally, we calculated two DFAs with 277 calls of nine individuals excluding males (Table 1) and a second DFA including males with 290 calls of 11 individuals in order to show that call classification based on identity can be calculated with and without differences in acoustic features based on sex.
A third DFA was conducted using all of the predictive traits from the first two DFAs, but it also included the traits AvgPix, CentroidSize, and RelW2 RelW6 and was only conducted in the F2 samples where these additional morphological characters were collected (n = 1882) to test the additional predictive power of the morphological traits.
Each year, cross-validated DFA classified 38.66 ± 0.02% of groans to the correct male (same-year correct classification rate, N = three DFAs).
In it DFA appears to threaten to keep Southeast farmers from selling their milk to three DFA-controlled processing plants if the smaller co-op doesn't pay $3 million annually for that selling privilege, among other demands.
The remaining three discriminant functions together accounted for 22.84 ± 0.03% of the variation (N = three DFAs).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com