In particular, in Figure 5(a), the estimation error of the ML-based method is lower than the CRLB because the data length exceeds that,, used in the CRLB. Figure 5 Root mean square estimation error versus SNR with K = 120.
However, the gel based method is likely less accurate for the lower abundance proteins, as the signal/noise ratio for spot intensity was low – see [14].
However, the recall and precision of this method is lower, and it cannot effectively support users doing service discovery based on functional semantic.
The total optimized annual cost of plant operation determined by structural method is lower by 8.1% (conventional method) and 7.0% (modified method) as compared to base value.
The simulation results prove that compared with the conventional design method based RTC, the global signal optimization design method based RTC is lower in hardware cost, faster in circuit evolution, higher in convergent precision, and higher in circuit evolution success rate.
The figures also suggest that the likelihood-based method is superior, as it consistently outperforms the method based on TIGER rates, achieving lower AICc and BIC scores.
Figure 2 shows that the false discovery rate (FDR) curve based on our method is clearly lower than these two FDR curves based on GSA (one for Boston data and the other for Michigan data).
Figure 3 shows that the FDR curve based on our method is still clearly lower than these three FDR curves based on GSA (one curve for each data set).
Distance optimality, neighbor-joining and parsimony based methods had lower support for most clades, but were compatible with the maximum likelihood phylogeny (data not shown).
It can be readily seen that all of the solutions generated in the first generation, and thus the best solution of this generation too, are worse than the baseline solution of the repeated random draws based method (as witnessed by their relative fitness being lower than unity).
