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Although these combinations of the blocking and blur metrics show good results, the NR image quality metric using the proposed NR blur and blocking metrics showed the best performance.
Research teams or players in different sports to try to find the worst, by seasonal record, points scored, individual statistics or some other metric, using the Internet, libraries and resources like The New York Times's archives.
We designed the NDGB metric using the city of Bari, Southern Italy, as a case example by involving four groups of stakeholders (n = 202) to assess ten urban green spaces.
(1) An overall co-expression metric using the average correlation, (2) an extreme expression metric by looking at the top 5% average z-scores for every gene in the module, and (3) the root mean-squared deviation within the expression values of each module.
In addition, we evaluated the relative change associated with effort for each BOLD metric, using the non-parametric Kolmogorov-Smirnov (K-S) test to determine if there was a significant change in the distribution of median voxel values for run-1 vs. run-2 (task novelty) and old vs. young groups (aging).
Tables 4 shows the performance of the evaluated overall metric using the CSIQ and the LIVE databases.
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The proposed metric uses the same parameters as used with the LIVE database without any training.
Our standard metric uses the l 2-norm as defined in Equation 13.
The KNN metric uses the Euclidian distance to determine the similarity of a sample to its k nearest sample neighbors.
One exposure metric used the matched exposure period between birth and death but averaged all PM2.5 measurements in the mother's county.
We describe the database and the metric used in the evaluation in the next subsections.
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