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In addition, based upon the mean of signal-to-noise (SN) ratio analysis, the sliding speed is the most influencing factor for minimizing coefficient of friction.
Two objective functions are considered: (i) maximizing crystal size subject to a specified maximum coefficient of variation and (ii) minimizing coefficient of variation subject to a specified minimum crystal size.
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However, in the overall sample studied, we aimed to minimize coefficient of variation by repeating all samples in which the coefficient of variation of the T/S ratio in the triplicated telomere length measurement was >10%.
Estimating the optimal s0 for a particular dataset can be based on minimizing the coefficient of variation of the absolute t-statistic values ("SAM") [ 19], minimizing false positive and false negative estimates obtained through permutation ("SAMroc") [ 16], or simply choosing s0 as the 90th percentile of the σM values [ 20].
s0 was chosen by minimizing the coefficient of variation of the denominator of ZE j) across moving windows of data, akin to the strategy of Tusher et al. [ 29] for the moderation of t statistics.
With this procedure, we aimed to discover strong cancer-related signals (features) that exist in the form of pair-wise ratios (or higher order relationship when we extend to N-feature model classifier for N>2) in a given sample, while improving the signal to noise ratio of the dataset by minimizing its coefficient of variation (CV).
The scheduling objective is to minimize the coefficient of variation of slack time (lateness), where the slack time (ST) of a job denotes the difference between its due date and total completion time.
The 'fudge factor' s0 is chosen to minimize the coefficient of variance of d(i).
The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations.
To minimize the coefficient of error, we counted from every fourth section and set the parameters of the optical fractionator so that the sample consisted of at least 250 neurons for each TLCd.
BayesB95 analyses were run exclusively on the best-fit data sets for which the allocation proportions into training and validation sets were determined to minimize the coefficient of variation for the correlation between DGV and phenotypes in the validation set.
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