• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.714-720
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• 2004

In detecting human faces in color images, additional geometric computation is often necessary for validating the face-candidate regions having various forms. In this paper, we propose a method that detects the facial features using chrominance components of color which do not affected by face occlusion and orientation. The proposed algorithm uses the property that the Cb and Cr components have consistent differences around the facial features, especially eye-area. We designed the Mean-Gray Morphology operator to emphasize the feature areas in the eye-map image which generated by basic chrominance differences. Experimental results show that this method can detect the facial features under various face candidate regions effectively.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1579-1580
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• 2015

본 논문에서는 3차원 메쉬 모델의 중요 영역을 표현하는 메쉬 돌출맵(mesh saliency map)을 생성하기 위하여 다중 스케일 평균 곡률 (multi-scale mean curvature)을 기반으로 정의된 전역 희소치(global rarity)를 이용하는 방법을 제안한다. 제안 방법에서는 우선, 메쉬 모델의 지역 영역 특성을 정의하기 위하여 기존 관련 연구들에서 많이 사용하고 있는 가우시안 가중치 평균곡률(Gaussian-weighted mean curvature)을 5단계 서로 다른 스케일에서 정의하고, 메쉬의 각 정점(vertex)에 대하여 중심주변 연산자(center-surround operator)를 적용하여 5단계 지역 돌출특성(local saliency)을 정의한다. 주어진 메쉬 모델의 전역 희소치를 구하기 위하여 메쉬의 모든 정점쌍 (vertex pair)에 대하여 5단계 지역 돌출 특성 공간에서의 거리를 계산하고, 각 정점별로 5단계 지역 돌출 특성 공간에서의 다른 정점과의 거리의 합으로 전역 희소치를 정의한다. 이러한 전역 희소치를 각 정점의 메쉬 돌출치로 정의한다. 서로 다른 형태의 3차원 모델에 대하여 제안방법에 의한 메쉬 돌출맵과 지역 특성만을 고려한 기존 메쉬 돌출맵을 생성하여 중요 영역 표현 결과를 비교 분석한다.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.411-425
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• 2021

Accelerated failure time (AFT) model represents a linear relationship between the log-survival time and covariates. We are interested in the inference of covariate's effect affecting the variation of survival times in the AFT model. Thus, we need to model the variance as well as the mean of survival times. We call the resulting model mean and variance AFT (MV-AFT) model. In this paper, we propose a variable selection procedure of regression parameters of mean and variance in MV-AFT model using penalized likelihood function. For the variable selection, we study four penalty functions, i.e. least absolute shrinkage and selection operator (LASSO), adaptive lasso (ALASSO), smoothly clipped absolute deviation (SCAD) and hierarchical likelihood (HL). With this procedure we can select important covariates and estimate the regression parameters at the same time. The performance of the proposed method is evaluated using simulation studies. The proposed method is illustrated with a clinical example dataset.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.53-62
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• 1995

In recent years, the rapid development of the machine tool and tough insert has made metal removal rates increase, and automatic system without human supervision requires a higher degree reliability of machining process. Therefore the control of chips is one of the important topics which deserves much attention. The chip classification was made based upon standard deviation of the mean cutting force measured by a tool dynamometer. STS304was chosen as the workpiece which is known as the difficult-to-cut material and mainly saw-toothed chip produced, and the chip type according to the standard deviation of mean cutting force was classified into five categories in this experiment. Long continuous type chip which interrupts the normal cutting process, and damages the operator, tool and workpiece has low standard deviation value, while short broken type chip, which is favourable chip for disposal, has relatively large standard deviation value. In addition, we investigated the possibility that the chip type can be predicted analyzing the relationship between chip type and cutting condition by the trained neural network, and obtained favourable results by which the chip type can be predicted with cutting conditon before cutting process.

• Genomics & Informatics
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• v.14 no.4
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• pp.149-159
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• 2016

With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE) value on data from the Korea Association Resource (KARE) with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.227-234
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• 2000

The human sensibility caused by the motion of an object grasped by a human operator is defined as kinesthetic sense of arm. Due to nonlinearity and ambiguity of human sense, there is no absolute standard for quantification of kinesthetic sense. In this research, a so-called 2-dimensional arm motion generator is developed to present various mechanical impedance (i.e., stiffness or damping) characteristics to a human arm. The kinesthetic words representing arm kinesthetic sense are selected and then the subject's satisfaction levels on these words for given impedance values are measured and processed by the SD method and factor analysis. In addition, the quantification method using neural network is proposed to take into account the individual difference between the mean sensibility and each subject's sensibility. Through this proposed algorithm, the sensibility of human motion described qualitatively can be converted into engineering data ensuring objectivity, reproducibility, and universality.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.11-21
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• 1990

With a general trend toward larger and more complex systems with centralized control, an operator's role of supervisory decision making in the control room becomes more important. Identification of potential man-machine interface (MMI) problems with CRT-based process control systems was attempted using a structured questionnaire survey. Based on the survey results, a laboratory experiment was carried out to investigate the performance of alarm detection on a process control CRT display. The user performance was measured in terms of reaction time from the onset of an alarm sound until the completion of predefined response procedures. The results revealed that for a highly complex tasks, mean reaction time ($\bar{RT}$) with a color consistent display was 10.5% faster than that with the original display, and $\bar{RT}$ with a grouped display was reduced by 8.2% in comparison with the color consistent display.

• Bulletin of the Korean Mathematical Society
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• v.34 no.2
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• pp.155-171
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• 1997

Let $M^n$ be a connected subminifold of a Euclidean space $E^m$, equipped with the induced metric. Denoty by $\Delta$ the Laplacian operator of $M^n$ and by x the position vector. A well-known T. Takahashi's theorem [13] says that $\delta x = \lambda x$ for some constant $\lambda$ if and only if $M^n$ is either minimal subminifold of $E^m$ or minimal submanifold in a hypersphere of $E^m$. In [9], O. Garay studied the hypersurfaces $M^n$ in $E^{n+1}$ satisfying $\delta x = Dx$, where D is a diagonal matrix, and he classified such hypersurfaces. Garay's condition can be seen as a generalization of T.

• Bulletin of the Korean Mathematical Society
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• v.53 no.3
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• pp.885-902
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• 2016

In this paper we begin the study of $L_k$-2-type hypersurfaces of a hypersphere ${\mathbb{S}}^{n+1}{\subset}{\mathbb{R}}^{n+2}$ for $k{\geq}1$ Let ${\psi}:M^3{\rightarrow}{\mathbb{S}}^4$ be an orientable $H_k$-hypersurface, which is not an open portion of a hypersphere. Then $M^3$ is of $L_k$-2-type if and only if $M^3$ is a Clifford tori ${\mathbb{S}}^1(r_1){\times}{\mathbb{S}}^2(r_2)$, $r^2_1+r^2_2=1$, for appropriate radii, or a tube $T^r(V^2)$ of appropriate constant radius r around the Veronese embedding of the real projective plane ${\mathbb{R}}P^2({\sqrt{3}})$.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.98-101
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• 1992

A new algorithm using entropy operater with variable threshold for edge detection from 2D short axis echocardiogram is proposed. This algorithm is based on brightness, mean value of entropy, and variance value of entropy in local window. This algorithm is effective to process complex echocardiographic images due to the speckle noises, echo dropouts and characteristics of 2D echocardiographic constituents. Results of computer simulation of the proposed algorithm show excellent edge detection performance comparing wi th other edge operators which have been applied to 2D echocardiograms.