The task was to detect all the test faces that are the same as the target, with a point for each correct detection.
We used the approach described by Kildare et al. (14) based on Bayes' theorem to estimate the probability for the correct detection of a specific source of pollution under different pollution scenarios (Table 1).
We insist on a constant review of the methodology for the correct detection of sounds of swallowing and subsequent analysis and clinical interpretation.
On the AR face subsets, different disparity errors were considered and for the smallest error, a 100% correct detection was reached in the AR-63 subset and 99.7% was obtained in the AR-564 subset.
Correspondingly, the range of hits varied between 10% and 100% for the correct detection of NF-Ds selected by <1% of the candidates with a mean of 64% (for NF-Ds selected by <5%, range = 20% - 100%, mean = 82%).
For example, in the initial (i=0) detection, for the correct detection case, 96% of γs is smaller than 0.5 whereas for the incorrect detection case, 95% of γs is larger than 0.5.
These instances were rare and the trials discarded, including the results for one of the fatty images for which correct detection was difficult.
In order to check whether or not this measure well reflects the reliability of the detection symbol, we simulated the cumulative distribution function (CDF) of γ for the correct detection case and the incorrect detection case.
Here we describe a modification of the conventional whole-mount in situ hybridization (WISH) procedure that proved to be crucial for the correct detection of transgene transcripts in electroporated embryos.
The above observations show that because of the spatial and temporal correlation of the noise, PDC for the causal pairs has a tendency for higher rate of correct detection and for the noncausal pairs a higher rate for false detections.
