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In this case, the final FVs were formed by combining the composite features synthesized by each individual sub-population.
In this way, the composite features of concrete are appropriately taken into account.
Channel-fill, channel-flank and lobe strata represent the building blocks that form composite features documented at four scales.
Using the selected composite features discussed above, Figure 5 shows that the 1-NN, with 95.20% sensitivity (SEN) & 88.60% specificity (SPE), achieved the best overall performance.
Low-coherence interferometry is exploited for the high-speed 3D inspection of microelectronics products comprised of composite features of different surface characteristics.
Furthermore, the composite features a high energy density of 31.5 Wh kg−1 at a power density of 100 W kg−1.
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The composite featured a honeycomb structure.
The composite feature vector was then fed to a number of statistical classifiers.
The ternary composite featured high stability, with an increase of 5% in capacitance after a thousand cycles.
The resulting feature vectors F ¯ HRV and F ¯ EEG were concatenated to form a single composite feature vector, F ¯, given by F ¯ = F ¯ EEG F ¯ HRV (3).
The resultant composite, featuring three-dimensional reinforcement architecture, possesses triple toughening mechanisms at three different scales, thus yielding a synergistic effect.
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