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Both at consecutive sample ratio 0.15.
The consecutive sample ratio β is a trade-off parameter.
The used pink noises have 22.05-kHz 22.05-kHz and 44.1-kHz sample ratio.
A ray-tracing sampling method was further used to obtain the cap-to-band sample ratio.
Preliminary screening experiments were performed to select choice of solvent, extraction time, microwave power and solvent: sample ratio.
The samples were divided into two groups: a calibration group and a test group, with approx. 2 1 sample ratio.
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The solvent, solvent-to-sample ratio, extraction time and extraction temperature were optimized.
This indicated the solvent-to-sample ratio was the most important factor among the four parameters.
The most significant (p < 0.0001) effect is the solvent-to-sample ratio while quadratic effects caused by temperature and solvent-to-sample ratio were of moderate importance (p < 0.05).
The solvent-to-sample ratio was the most important factor comparing with solvent, extraction time and temperature.
This leads to a computational challenge of high feature-to-sample ratio from the machine learning viewpoint [12].
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