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In addition, two different mixture methods are tested; the first is to add SSPCM to the concrete mixture, and the second is to replace the fine aggregate with the same amount of SSPCM.
We applied both the CLR and Dirichlet mixture methods described above to 8 different hierarchical mixing models.
In this situation, mixture methods are redundant since the distinction between infected and uninfected children is easily made and there are few children with intermediate results.
By comparison, there are no informative results for any of the CPI or CLR qualitative mixture methods, as indicated by the absence of red and purple cases.
The mixture methods of analysis are designed to provide a better estimate of prevalence of infection in such situations than a simple cut-off based approach.
Within such "mixture methods", it is then assumed that one population reflects infection, while one (or more) populations reflect non-specific reactions to BCG, environmental mycobacteria or background noise in the test's operating characteristics.
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From top to bottom: MC, Kernel, and Gaussian mixture method.
Figure 5 BER estimated by Gaussian mixture method with different iteration.
The formulations were based on the composition designed by D-optimal mixture method.
Gaussian Mixture method seems to be the worst one in the MISE criterion.
Figure 6 BER estimated by Gaussian mixture method for very high SNR values and only using samples with 50 iterations.
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