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Methane was decomposed to hydrogen and carbon nanotubes (CNTs)
by microwave plasma, using Fe/Si catalyst activated by biased (—150
V) hydrogen plasma for various treatment times. Upon exposure to biased
hydrogen plasma, the catalyst surface becomes lumpy within 1 min, coheres
between 5 and 10 min and forms particles after 20 min. The methane conversion
increased up to 93% over the treatment time of 5 min. The hydrogen yield showed
as similar tendency as the methane conversion and kept 83% at treatment time of 5
min. The treatment time up to 1 min increased the amount of deposited carbon,
and after treatment time of 5 min it dropped; then again after treatment time
of 20 min, it increased to reach a maximum value of 22 gc/gcat.
Deposited carbon was found to be consisted of carbon nanotubes. It grew
vertically on the catalyst surface and reached a maximum length of 30.7 nm
after treatment time of 10 min. Multiple types of CNTs were present, and the CNT
diameters decreased with increasing plasma treatment time.
introduces a mixed music analysis method using extended specmurt analysis.
Conventional specmurt can only analyze a multi-pitch music signal from a single
instrument and cannot analyze a mixed music signal that has several different types of instruments being played at the
same time. To analyze a mixed music signal, extended specmurt is proposed. We regard the observed spectrum
extracted from the mixed music as the summation of the observed spectra corresponding to each instrument. The mixed music has as many unknown fundamental
frequency distributions as the number of instruments since the observed
spectrum of a single instrument can be expressed as a convolution of the common
harmonic structure and the fundamental frequency distribution. The relation among the observed spectrum, the common
harmonic structure and the fundamental frequency distribution is transformed
into a matrix representation in order to obtain the unknown fundamental
frequency distributions. The equation is called extended specmurt, and the matrix of unknown components can be
obtained by using a pseudo inverse matrix. The experimental result shows the
effectiveness of the proposed method.