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In order to verify the accuracy of the qPCR system, known genotype samples and random samples are employed.
Experiments performed with real-world signature data (composed of genuine samples, and random, simple and skilled forgeries) indicate that the proposed dynamic selection strategy can significantly reduce the overall error rates, with respect to other EoCs formed using well-known dynamic and static selection strategies.
Other techniques based on probability samples, such as network samples, and random digit dialling are also not used as the population registers are available and have many merits in comparison to other techniques.
The layers of beats, samples and random noise layer like a symphony, rather than the one looong crescendo of lesser EDM creators.
Identifying combinations of miRs that putatively are associated to altered mRNAs expression levels we applied the random forest algorithm [40], an ensemble-learning-algorithm that constructs regression trees with bootstrap data samples and random choices of predicting variables.
BP was measured in the sitting position after taking a rest of >5 min. Nonfasting blood samples and random urine samples were obtained from each patient.
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Besides, considering an extreme case, if f s and f θ are co-prime, which will introduce much randomization, whose randomness of sampling is between uniform sampling and random sampling.
Periodic nonuniform sampling introduces enough nonuniform to differentiate the frequency band of the received signals, whose randomness of sampling is between uniform sampling and random sampling.
But sampling and random events affect both earlier and later scores, compounding the inaccuracy.
We compared two sampling techniques (systematic sampling and random sampling) and four intensities for each technique to investigate the driving patterns underlying the changes using multinomial logistic regression.
Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations.
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