• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.3
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• pp.110-121
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• 2021

The importance of tidal flats lost due to industrialization has recently received attention, and attention is being paid to the creation of artificial tidal flats and maintenance of natural tidal flats. However, there is still a lack of understanding about the behavioral characteristics of mud, mud, and sand that form tidal flats. Although research on the movement characteristics of mixed soils such as tidal flats has been conducted through field investigations and hydraulic experiments, interest in developing a numerical model based on these results has not yet reached. In this paper, the purpose of this paper is to establish a mixed soil model that can efficiently manage the low quality of the tidal flats. In constructing a model for reproducing the surface movement of mixed soil, the numerical stability of the reproduction and movement of sand and mud constituting the mixed soil in the numerical model should be considered first, so first, the volume of sand and mud constituting the mixed soil A mixed soil model representing the relationship was proposed based on a topographical diagram representing the geometric structure of the mixed soil. In order to consider the dry bulk density of the mixed soil, it was possible to consider the dry bulk density of the mud by introducing the water content of the mud containing water. In addition, it was confirmed that the mud and sand movement calculation according to the slope collapse of the mixed soil was stably performed through the calculation of the slope collapse of the mixed soil through the numerical analysis model to which the proposed mixed soil model was applied.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.47-54
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• 2005

In general, wavelet coefficients are composed of a few large coefficients and a lot of small coefficients. In this paper, we propose image denoising algorithm using Bernoulli-Gaussian mixture model based on sparse characteristic of wavelet coefficient. The Bernoulli-Gaussian mixture is composed of the multiplication of Bernoulli random variable and Gaussian mixture random variable. The image denoising is performed by using Bayesian estimation. We present an effective denoising method through simplified parameter estimation for Bernoulli random variable using local expected squared error. Simulation results show our method outperforms the states-of-art denoising methods when using orthogonal wavelets.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.4
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• pp.365-373
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• 2010

A chemical reactor model (CRM) was developed for a jet stirred reactor (JSR) to predict the emission of exhaust such as NOx. In this study, a two-PSR model was chosen as the chemical reactor model for the JSR. The predictions of NO formation in lean premixed methane-air combustion in the JSR were carried out by using CHEMKIN and GRI 3.0 methane-air combustion mechanism which include the four NO formation mechanisms. The calculated results were compared with Rutar's experimental data for the validation of the model. The effects of important parameters on NO formation and the contributions of the four NO pathways were investigated. In the flame region, the major pathway is the prompt mechanism, and in the post flame region, the major pathway is the Zelodovich mechanism. Under the lean premixed condition, the N2O mechanism is the important pathway in both flame and postflame regions.

• The Journal of the Acoustical Society of Korea
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• v.24 no.3
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• pp.141-149
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• 2005

Tn general. Gaussian mixture model (GMM) is used to estimate the speaker model from the speech for speaker identification. The parameter estimates of the GMM are obtained by using the Expectation-Maximization (EM) algorithm for the maximum likelihood (ML) estimation. However the EM algorithm has such drawbacks that it depends heavily on the initialization and it needs the number of mixtures to be known. In this paper, to solve the above problems of the EM algorithm. we propose an EM algorithm with the initialization based on incremental ${\cal}k-means$ for GMM. The proposed method dynamically increases the number of mixtures one by one until finding the optimum number of mixtures. Whenever adding one mixture, we calculate the mutual relationship between it and one of other mixtures respectively. Finally. based on these mutual relationships. we can estimate the optimal number of mixtures which are statistically independent. The effectiveness of the proposed method is shown by the experiment for artificial data. Also. we performed the speaker identification by applying the proposed method comparing with other approaches.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.98-101
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• 2006

본 논문에서는 얼굴영상 인식의 전처리 단계인 피부 영역 자동 검출시 적용 가능하며 조명변화에 강건한 피부 영역 검출을 위한 혼합 컬러모델을 제시한다. 또한, 사용자별로 차이를 보이는 다양한 피부색을 자동으로 인식하고 사용자에 적합한 피부색 영역을 결정하기 위하여 제시한 컬러 모델을 기반으로 한 피부색 영역 모델링 전처리 단계를 제시한다. 우선, 사용자 및 사용 카메라에 따라 차이를 보이는 피부색에 대한 영역 모델을 구축하기 위하여 화면상의 가운데에 손이나 얼굴 영역이 위치하도록 하고 일정 프레임의 화면 정보를 취득한다. 취득 화면 정보로서 각 픽셀에 대한 정규화 된 RGB 성분 및 H 성분, V 성분 정보를 추출하고 이에 대한 평균화된 혼합 컬러 모델을 구축한다. H성분으로 피부색과 비슷한 배경을 제거하고 여기에 YUV 성분 중 적색에서 밝기 값을 뺀 성분인 V 값을 한 번 더 사용하여 밝기 값을 제거한 보다 뚜렷한 얼굴영역을 검출한다.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.279-291
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• 2012

When fitting a Cox proportional hazards model with missing covariates, it is inefficient to exclude observations with missing values in the analysis. Furthermore, if the missing-data mechanism is not Missing Completely At Random(MCAR), it may lead to biased parameter estimation. Many approaches have been suggested to handle the Cox proportional hazards model when covariates are sometimes missing, but they are based on the selection model. This paper suggest an approach to handle Cox proportional hazards model with missing covariates by using the pattern-mixture model (Little, 1993). The pattern-mixture model is expressed by the joint distribution of survival time and the missing-data mechanism. In the pattern-mixture model, many models can be considered by setting up various restrictions, and different results under various restrictions indicate the sensitivity of the model due to missing covariates. A simulation study was conducted to show the sensitivity of parameter estimation under different restrictions in a pattern-mixture model. The proposed approach was also applied to mouse leukemia data.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.8
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• pp.1084-1093
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• 2010

Large eddy simulation of turbulent premixed flame stabilized by the bluff body is performed by using sub-grid scale combustion model based on the G-equation describing the flame front propagation. The basic idea of LES modeling is to evaluate the filtered-front speed, which should be enhanced in the grid scale by the scale fluctuations. The dynamic subgrid scale models newly introduced into the G-equation are validated by the premixed combustion flow behind the triangle flame holder. The calculated results can predict the velocity and temperature of the combustion flow in good agreement with the experiment data.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.387-391
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• 2008

For the detection of moving objects, background subtraction methods are widely used. In case the background has variation, we need to update the background in real-time for the reliable detection of foreground objects. Gaussian mixture model (GMM) combined with probabilistic learning is one of the most popular methods for the real-time update of the background. However, it does not work well in the complex and dynamic backgrounds with high traffic regions. In this paper, we propose a new method for modelling and updating more reliably the complex and dynamic backgrounds based on the probabilistic learning and the layered processing.

• Journal of the Korean School Mathematics Society
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• v.9 no.1
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• pp.1-17
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• 2006

This thesis analyzed the effects of cooperative learning blended with TAI(Team Assisted Individualization) and STAD(Student Team Achievement Division) models on the students' ability of problem solving in mathematics in order to discover what kind of effects would give to their ability of that, and would promote their disposition and attitude to learn mathematics. The results of this study were as follows : First, the learning method blended with TAI and STAD models was more effective in the students' ability of problem solving in mathematics than traditional learning method because of the blended model's characteristics; positive interdependence, individual accountability, team recognition, curriculum materials. Second, the learning method blended with TAI and STAD models was more effective in sub-elements - self-confidence, adaptability, will, curiosity and value - of mathematical disposition than traditional learning method. And the learning method blended with TAI and STAD models was more effective in sub-elements - self-consciousness of mathematics and interests - of mathematical attitude than traditional learning method. In conclusion, the learning method blended with TAI and STAD models could affect to not only the students' ability of problem solving in mathematics but also the students' several affective factors.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.05a
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• pp.157-163
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• 2000

이 글은 최근 인지언어학에서 기본적인 핵심이론 중의 하나로 자리잡고 있는 '정신공간 이론'(mental space theory)에 대한 이론적인 소개와 함께 의미구성에 있어서 중요한 개념의 하나인 '사상'(mappings)의 문제를 다루고자 한다. 1994년 이후 Fauconnier와 Fauconnier & Turner 등을 중심으로 진행되어 오고 있는 정신공간 이론에서는, 언어의 의미를 궁극적으로 인지적 공간들 사이의 상호관계가 언어로 '투사'(projection)된 것으로 간주한다. 그리고 기존의 근원영역과 목표영역 사이의 직접적이고 체계적인 사상, 이른바 '두 영역 모델'의 대안으로 '다공간 모델'을 제시하고 있다. 다공간 모델 속에는 '포괄공간'(generic space)과 '혼합공간'(blending space)이 설정되는데, 그 중에서 포괄공간은 근원공간과 목표공간의 모든 개념이나 추상적인 도식 등이 반영되어 있는 반면, 혼합공간은 실제의 다양한 개념적 혼합의 결과로 나타나며, 입력된 공간에서 나타나는 상응되는 부분들 사이의 연결을 활용하고 발전시키기 때문에 그 자체가 또 다른 혼합공간의 입력공간에서 일어나는 개념적 사상의 양상은 매우 다양할 뿐만 아니라 의미구성에 있어서도 중요한 역할을 한다. 이 글에서는 합성어와 같은 어휘적 측면은 물론, 일상의 문장 표현을 통해 나타나는 개념적 사상의 다양한 양상을 고찰하고자 한다.