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There is, as yet, no universally agreed upon method for the detection of spontaneous otoacoustic emissions (SOAEs). In this paper, we augment extant techniques by presenting a new automated approach. The new procedure reliably labels the spectral peaks as SOAEs, rejects noisy data such as that due to body movements or breathing, provides a subject-specific(More)
The potential influence of spectral analysis factors on estimates of the prevalence of spontaneous otoacoustic emissions (SOAE) was explored. The detection of a SOAE was influenced by two spectral factors: (1) the frequency resolution of the spectrum, and (2) the number of spectral averages. For 15 different combinations of these two factors, the estimate(More)
Conventional methods to create fluid animation primarily resort to physically based simulation via numerical integration, whose performance is dominantly hindered by large amount of numerical calculation and low efficiency. Alternatively, video-based methods could easily reconstruct fluid surfaces from videos, yet they are not able to realize two-way(More)
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