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For the latter, a comparison is given between the developed method and previously published results.
The calculation times are assessed and comparison between the developed method and the classical block-form LU decomposition method is also performed.
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This robustness is in the fact of including smoothness and sparseness constraints into the factorization process because the main difference between the develop method and HPSS and MFS is the use of sparseness constraints to achieve time-frequency energy distributions as can be found in real-world percussive or harmonic sounds.
The detection limits of the developed methods were between 2.9 and 9.3 pg/mg (ppb) for hair samples and in the 40 – 70 pg/g (ppt) range for the urine or meat samples.
Finally, a comparison of the computational efficiency of the developed methods is made between a variety of problems of different sizes.
The developed methods take the interactions between control and diagnosis into account.
A comparison between the newly developed method and other existing methods (the modified BISE algorithm and a fast Fourier transform algorithm) indicates that the newly developed method is an effective tool for reconstructing high-quality time series of PAL NDVI time series.
Measurement results showed comparable predictions between the two developed methods with an average deviation of 30 °C over the 500 800 °C range.
We compared the diagnostic performances between this newly developed method and our trimmed mean method in identifying women with low BMD at the lumbar spine and the femoral neck in 100 postmenopausal women ([greater than or equal to]50 years), of whom 60 to the training and 40 to its testing with no previous record of osteoporosis.
We controlled for differences in size between the models using a recently developed method for comparing FE models [16].
The second (and newly developed) method returns components produced by differences between age- and cause-specific mortality rates.
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