• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.1074-1079
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• 2007

We will introduce speech/speaker recognition algorithm for the isolated word. In general case of speaker verification, Gaussian Mixture Model (GMM) is used to model the feature vectors of reference speech signals. On the other hand, Dynamic Time Warping (DTW) based template matching technique was proposed for the isolated word recognition in several years ago. We combine these two different concepts in a single method and then implement in a real time speaker/speech recognition system. Using our proposed method, it is guaranteed that a small number of reference speeches (5 or 6 times training) are enough to make reference model to satisfy 90% of recognition performance.

• Journal of Microbiology and Biotechnology
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• v.2 no.2
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• pp.85-91
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• 1992

The intestinal microflora of humans is an extraordinarily complex mixture of microorganisms, the majority of which are anaerobic microorganisms. The distribution of amylolytic microorganisms in the human large intestinal tract was investigated in various individuals of differing ages using anaerobic culture techniques. A large percentage of the amylolytic microorganisms present belonged to the Genus Bifidobacteria. The number of Bifidobacteria increased significantly at two years of age. Adults and children above 2 years old carried about $0.8{\times}10^9-2.0{\times}10^{10}$ colony forming units (CFU/gram) of amylolytic Bifidobacteria. Among these amylolytic Bifidobacteria, Int-57 was chosen for further studies. Between 65% and 85% of the amylase produced was secreted and the remaining amylase was bound to the cell wall facing the outside. Amylase production could be induced by starch in a stable form. When cells were grown on maltose or glucose, amylase production was much lower than on starch and amylase activity disappeared after 24 hours growth on these media. Partially purified enzymes showed optimum activity at a temperature of $50^{\circ}C$ and at an optimum pH of 5.5, respectively. Heat treatment at $70^{\circ}C$ for 30 minutes almost completely inactivated amylase. The hydrolysis products of starch were mainly maltose and maltotriose. Soluble starch, amylose, amylopectin, and $\gamma$-cyclodextrin($\gamma$-CD) were easily hydrolyzed. The rate of hydrolysis of $\alpha$-CD and $\beta$-CD was slower than that of $\gamma$-CD. Carboxymethyl cellulose, $\beta$-1, 3-glucan and inulin were not hydrolyzed.

• Nuclear Engineering and Technology
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• v.47 no.6
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• pp.738-745
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• 2015

The catalytic exchange of hydrogen isotopes between hydrogen and water has been known to be a very useful process for the separation of tritium from tritiated water. For the process, a highly active hydrophobic catalyst is needed. This study provides an effective fabrication method of size-controlled platinum/poly[styrene-divinylbenzene-tri(propylene glycol) diacrylate] [Pt/poly(SDB-TPGDA)] hydrophobic catalyst beads with a narrow size distribution. Platinum nanoparticles were prepared by ${\gamma}$-ray-induced reduction in the aqueous phase first, and then uniformly dispersed in SDB-TPGDA comonomer after the hydrophobization of platinum nanoparticles with alkylamine stabilizers. The porous Pt/poly(SDB-TPGDA) hydrophobic catalyst beads were synthesized by the UV-initiated polymerization of the mixture droplets prepared in a capillary-based microfluidic system. The size of as-prepared catalyst beads can be controlled in the range of $200-1,000{\mu}m$ by adjusting the flow rate of dispersed and continuous phases, as well as the viscosity of the continuous phase. Sorbitan monooleate and cyclohexanol were used as coporogens to control the porosities of the catalyst beads.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.4
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• pp.285-297
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• 2017

This study proposed a new approach to develop an Intelligent control algorithm for cooperative working of human and robot based on voice recognition. In general case of speaker verification, Gaussian Mixture Model is used to model the feature vectors of reference speech signals. On the other hand, Dynamic Time Warping based template matching techniques were presented for the voice recognition about several years ago. We converge these two different concepts in a single method and then implement in a real time voice recognition enough to make reference model to satisfy 95% of recognition performance. In this paper it was illustrated the reliability of voice recognition by simulation and experiments for humanoid robot with 18 joints.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5585-5593
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• 2014

This study tested the hypothesis that the significance of the heterogeneous dispersion parameter in safety performance function (SPF) used to estimate the expected crashes is affected by the endogenous heterogeneous prior distributions, and analyzed the impacts of the mis-specified dispersion parameter on the evaluation results for traffic safety countermeasures. In particular, this study simulated the Poisson means based on the heterogeneous dispersion parameters and estimated the SPFs using both the negative binomial (NB) model and the heterogeneous negative binomial (HNB) model for analyzing the impacts of the model mis-specification on the mean and dispersion functions in SPF. In addition, this study analyzed the characteristics of errors in the crash reduction factors (CRFs) obtained when the two models are used to estimate the posterior means and variances, which are essentially estimated through the estimated hyper-parameters in the heterogeneous prior distributions. The simulation study results showed that a mis-estimation on the heterogeneous dispersion parameters through the NB model does not affect the coefficient of the mean functions, but the variances of the prior distribution are seriously mis-estimated when the NB model is used to develop SPFs without considering the heterogeneity in dispersion. Consequently, when the NB model is used erroneously to estimate the prior distributions with heterogeneous dispersion parameters, the mis-estimated posterior mean can produce large errors in CRFs up to 120%.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.453-459
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• 2010

In the study of traffic safety, it is utmost important to obtain more reliable estimates of the expected crashes for a site (or a segment). The observed crashes have been mainly used as the estimate of the expected crashes in Korea, while the empirical Bayes (EB) estimates based on the Poisson-gamma mixture model have been used in the USA and several European countries. Although numerous studies have used the EB method for estimating the expected crashes and/or the effectiveness of the safety countermeasures, no past studies examine the difference in the estimation errors between the two estimates. Thus, this study compares the estimation errors of the two estimates using a Monte Carlo simulation study. By analyzing the crash dataset at 3,000,000 simulated sites, this study reveals that the estimation errors of the EB estimates are always less than those of the observed crashes. Hence, it is imperative to incorporate the EB method into the traffic safety research guideline in Korea. However, the results show that the differences in the estimation errors between the two estimates decrease as the uncertainty of the prior distribution increases. Consequently, it is recommended that the EB method be used with reliable hyper-parameter estimates after conducting a comprehensive examination on the estimated negative binomial model.