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In our derivations, we have found that the post-processing noise in the DDST case behaves asymptotically as a Gaussian mixture process, while in most of the existing works, the noise is assumed to be asymptotically Gaussian distributed.
The present paper introduces the mixture process and a series of mechanical tests on UHDCC with 3 different mixtures.
Those of the side-stripper DWC for the aliphatic compound mixture process are 10.2% and 10.8% less, respectively.
A more structural view of how fluctuations around trend-growth are determined is to suppose that the data are generated by a mixture process.
The mixture process can be modeled by the FHMM [36] that comprises two underlying HMMs evolving independently over time, each corresponding to a single speaker.
This information is necessary to avoid the artifacts and/or noise caused by the mixture process which tends to appear before and after active notes.
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Two example processes, the BTX and aliphatic compound mixture processes, are utilized for the evaluation.
We present a methodology to estimate the maximum recovery of each component in an azeotropic multicomponent mixture processed at a batch distillation column.
In this paper, we examine flexible, optimal designs for realistic mixture-process variable experiments.
A limited number of designs for mixture-process variable experiments are available in the literature.
A mixture-process design was constructed and 99 hearth bread batches were made.
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