• International Journal of Highway Engineering
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• v.14 no.3
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• pp.77-85
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• 2012

Most of Automatic Accident Detection Algorithm has a problem of detecting an accident as traffic congestion. Actually, center's managers deal with accidents depend on watching CCTV or accident report by drivers even though they run the Automatic Accident Detection system. It is because of the system's detecting errors such as detecting non-accidents as accidents, and it makes decreasing in the system's overall reliability. It means that Automatic Accident Detection Algorithm should not only have high detection probability but also have low false alarm probability, and it has to detect accurate accident spot. The study tries to verify and evaluate the effectiveness of using Gaussian Mixture Model and individual vehicle tracking to adapt Accident Detection Algorithm to Center Management System by measuring accident detection probability and false alarm probability's frequency in the real accident.

• Journal of the Korea Concrete Institute
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• v.27 no.4
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• pp.427-434
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• 2015

The objective of this study is to establish an rational mixture-proportioning procedure for low-$CO_2$ concrete using supplementary cementitious materials (SCMs) achieving the targeted $CO_2$ reduction ratio as well as the conventional requirements such as initial slump, air content, and 28-day compressive strength of concrete. To evaluate the effect of SCM level on the $CO_2$ emission and compressive strength of concrete, a total of 12537 data sets were compiled from the available literature and ready-mixed concrete plants. The amount of $CO_2$ emission of concrete was assessed under the system boundary from cradle to concrete production stage at a ready-mixed concrete plant. Based on regression analysis using the established database, simple equations were proposed to determine the mixture proportions of concrete such as the type and level of SCMs, water-to-binder ratio, and fine aggregate-to-total aggregate ratio. Furthermore, the $CO_2$ emissions for a given concrete mixture can be straightforwardly calculated using the proposed equations. Overall, the developed mixture-proportioning procedure is practically useful for determining the initial mixture proportions of low-$CO_2$ concrete in the ready-mixed concrete field.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1047-1054
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• 2015

This paper presents an acoustic model transform method using untranscribed speech database for improved speech recognition. In the presented model transform method, an adapted GMM is obtained by employing the conventional adaptation method, and the most similar Gaussian component is selected from the adapted GMM. The bias vector between the mean vectors of the clean GMM and the adapted GMM is used for updating the mean vector of HMM. The presented GAMT combined with MAP or MLLR brings improved speech recognition performance in car noise and speech babble conditions, compared to singly-used MAP or MLLR respectively. The experimental results show that the presented model transform method effectively utilizes untranscribed speech database for acoustic model adaptation in order to increase speech recognition accuracy.

• Korean Journal of Food Science and Technology
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• v.45 no.4
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• pp.473-477
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• 2013

The aim of this study was to identify the optimal ingredient-mixing ratio of Job's-tear and wheat flour subjected to extrusion. A modified distance-based mixture design analysis was chosen for the experimental design. The results showed that the bending failure force, the a-value, and the water absorbtion index (WAI) value had no correlation with the mixture ratio of Job's-tear and wheat flour. However, the diameter of the extrudates, the L- and b-values, and the water solubility index (WSI) value were all found to be correlated to the mixture ratio. While the first three values were determined using a linear model, the WSI value was determined using a quadratic model. The diameter and color had an inverse correlation to the mixture ratio: the higher the ratio of Job's-tear to wheat flour, the lower the diameter and darker the color. The L- and b-values were found to change in accordance with the mixture ratio of Job's-tear to wheat flour. The lowest WSI value was obtained at a 40:60 ratio of Job's-tear to wheat.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.335-338
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• 2004

본 논문에서는 기존의 정보량(Entropy) 기반 클러스터링 기법을 향상시키기 위한 방법으로서 퍼지 정보량을 이용하였다 가우시안 혼합 모델을 이용하면, 프로토타입의 목적 함수를 이용하는 클러스터링 기법보다 향상된 결과를 얻을 수 있고, Parameter의 조정이 요구되지 않는다. 그러나, 가우시안 혼합 모델의 사용은 주어진 패턴 집합을 클러스터링하는데 계산량의 증가를 초래하게 된다. 본 논문에서는 가우시안 혼합 모델의 정형화에 요구되는 계산량을 감소시키는 방법을 제시한다 또한 퍼지정보량(Fuzzy Entropy)을 적용하여 기존의 정보량 기반의 클러스터링 결과와 비교 분석하였다.

• International Journal of Highway Engineering
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• v.3 no.1 s.7
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• pp.185-197
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• 2001

This paper dealt with modification of effective crack length model (ECM) by adding Poisson's ratio term to evaluate fracture toughness of asphalt concrete which varies its material property by temperature. The original ECM model was developed for solid materials, such as cement concrete, and Poisson's ratio of materials was not considered. However, since asphalt concrete is sensitive to temperature variation and changes its Poisson's ratio by temperature, it should be taken into consideration to know exact fracture property under various temperatures. Four binders, including 3 polymer-modified asphalt (PMA) binders, were used to make a dense-grade asphalt mixture and 3-point bending test was peformed on notched beam at low temperatures, from -5oC to 35oC. Elastic modulus, flexural strength and fracture toughness were obtained from the test. The results showed that, since Poisson's ratio was considered, the more accurate test values could be obtained using modified ECM equation than original ECM. PMA mixture showed higher stiffness and fracture toughness than normal asphalt mixture under very low temperatures.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.20-24
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• 2011

In this paper, numerical simulation of cavitation flow for modified NACA66 hydrofoil was made by using the multi-phase RANS equation based on pseudo-compressibility. The Homogeneous mixture model comprised of the mixture continuity, mixture momentum and liquid volume fraction equations was utilized. A vertex-centered finite-volume method was used in conjunction 2nd-order Roe's FDS to discretize the inviscid fluxes. The viscous fluxes were computed based on central differencing The Spalart-Allmaras one equation model was employed for the closure of turbulence. Reasonable agreements were obtained between the calculation results and the experiment for pressure coefficients on the hydrofoil surface.

• The Journal of the Acoustical Society of Korea
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• v.25 no.7
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• pp.319-324
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• 2006

We Propose two new methods for non-keyword modeling to improve the performance of speaker- and vocabulary-independent keyword spotting system. The first method is decision tree clustering of monophone at the state level instead of monophone clustering method based on K-means algorithm. The second method is multi-state multiple mixture modeling at the syllable level rather than single state multiple mixture model for the non-keyword. To evaluate our method, we used the ETRI speech DB for training and keyword spotting test (closed test) . We also conduct an open test to spot 100 keywords with 400 sentences uttered by 4 speakers in an of fce environment. The experimental results showed that the decision tree-based state clustering method improve 28%/29% (closed/open test) than the monophone clustering method based K-means algorithm in keyword spotting. And multi-state non-keyword modeling at the syllable level improve 22%/2% (closed/open test) than single state model for the non-keyword. These results show that two proposed methods achieve the improvement of keyword spotting performance.

• Korean Journal of Human Ecology
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• v.16 no.5
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• pp.899-908
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• 2007

Clusters of parental and peer variables associated with adolescent risk behaviors are explored using the mixture model. Questionnaires were completed by 917 high school freshmen in the Daegu Kyungpook area and included measures of risk behaviors, parental attachment, autonomy, parental monitoring, and peers' risk behaviors and desirable behaviors. As a result of the mixture model, five clusters were produced. Two of the subgroups were consistent with the literature of showing linear relationships among adolescent risk behaviors and above variables; a group of higher parental attachment and autonomy as well as parental monitoring, lower friends' risk behaviors, and lower adolescent risk behaviors, and a group of lower parental attachment and autonomy as well as parental monitoring, higher friends' risk behaviors, and higher adolescent risk behaviors. Two other subgroups were similar in parental attachment and autonomy, but differed in parental monitoring, friends' risk behaviors, and adolescent risk behaviors. The last subgroup was characterized by scoring the lowest parental attachment and autonomy, parental monitoring, friends' risk behaviors, and lower adolescent risk behaviors compared to other subgroups. The utility of the mixture model in research on adolescent risk behaviors is discussed in the conclusion.

• Applied Chemistry for Engineering
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• v.32 no.5
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• pp.574-580
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• 2021

The main goal of this study was to find an optimal surfactant mixture composition for the development of the best performing cleansing products. Three different surfactants including sodium cocoyl alaninate (SCoA), cocamidopropyl betaine (CPB), and decyl glucoside (DG) were selected, which showed excellent properties in detergency, foaming height, and contamination rate through preliminary experiments. The experiments by simplex centroid design matrix for surfactant mixtures were performed, and the regression analysis was conducted with the experimental data. Surface response model equations, which is statistically significant (p < 0.05), were obtained. The optimal composition of the surfactant mixture was also determined as SCoA (0.22), CPB (0.78), and DG(0.00) from simultaneous optimization of three response variables.