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In order to enhance the defect in relation to background noise of large grained materials different algorithms have been developed.
However, most existing methods for pulsed thermographic data processing aim to enhance the defect signals in each single thermal image, whereas automatic defect detection is not achieved.
Since pinholes are the major failure mechanisms of artificial interfaces, a novel double-layer design was proposed to enhance the defect tolerance, enabling uniform ion flux and mechanical properties as confirmed by both simulation and experiments.
Theoretically, subtracting this image from the original undiffused background would enhance the defect by removing some of the background components.
The effect of over-expression of CG5009 was to enhance the defect, an effect that was also seen with the Hsp70 co-chaperone DnaJ-1.
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The proposed system designs a novel image acquisition system to enhance the defects appearances and get controlled image acquisition environment.
Consequently, in a low contrast image, the PMAD model can smooth the background but it cannot clearly enhance the defects.
If the gland and a particular gene act in parallel, redundant pathways, then removal of both would enhance the defects, although there would be no change if they acted together.
Accordingly, logarithmic transformation would be helpful to apply the signal processing method in enhancing the defect frequencies for the bearing defect diagnosis.
Evidence is presented to suggest that high intensity illumination does not significantly increase the rate of passivation, but rather greatly enhances the defect formation rate.
However, loss of BRM function in adult plants (aMIR BRM) significantly enhanced the defect in the flower primordium initiation of mp-S319.
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