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Linear learning methods have low variance because most randomly drawn training sets produce similar decision hyperplanes.
For all drugs except penicillin and methicillin, all methods have low false-positive rates, below the FDA threshold of 3%.
Second, the methods have low computational cost, thus suitable for embedded battery management systems (BMSs) with constrained computing capabilities.
Among the various means to evaluate the quality of video streams, light-weight No-Reference (NR) methods have low computation and may be executed on thin clients.
Molecular methods have proved to be a reliable alternative to field observation, but most current methods have low sensitivity and/or low identification success (i.e. hosts are only identified to taxonomic levels higher than species).
Usually, the spatial deinterlacing methods have low computational power.
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With a small sample size of n = 20 all of the principal component methods had low power.
Remaining methods had low use and helpfulness.
The HKLOD method also worked reasonably well, but the EE(Residual), SLOD and MLOD methods had low power.
The authors found that biopsy-based methods had low sensitivity and high specificity; UBT had high accuracy; stool antigen tests were less accurate; and serology, though not influenced by UGI bleeding, was not recommended as the first test.
Serum samples were collected in a standardized way and stored at −80°C, laboratory methods had low CVs, and there were a relatively large number of subjects, i.e., good statistical power.
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