• Journal of Technologic Dentistry
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• v.15 no.1
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• pp.89-94
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• 1993

The tooth size and shape of the permanent incisor teeth have been studied and analyzed about the mean size, S.D, S.E, etcs and percentage from stone model of 100 Korean male and 74 Korean female. The results were as follows. 1. The crown length of permanent incisor teeth were longer in males than in females statistical differences of males and female were not found. 2. the mesio-distal diameters of permanent incisor teeth were larger in males than in females and statistical differences of males and females were found in mandibular lateral incisor and the bigest were max. central incisor, 2nd max. lateral incisor, 3rd man. lateral incisor and the smallest were man. central incisor. 3. The square form in max. central incisor was the greatest percentage and the tapering form in max. lateral incisor and man, incisor was the greatest percentage but tapering form and ovoid form and other shape were found in max. lateral at the same ratio. 4. Concerning the labial developmental groove "midium" was the greatest percentage in the max. central incisor and "low" was the greatest percentage in the man incisor. Concerning the incisal line, straight line was the greatest percentage in the max, incisor and man, incisor and concerning the lingual tubercle "none" was the greatest percentage in the max. incisor. 5. In comparison between left side and right side of incisor, the ratio of same shape ware 22.4%-36.2% but similar or dissimilar cases were more frequently found.

• Communications for Statistical Applications and Methods
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• v.25 no.4
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• pp.373-383
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• 2018

The spatial scan statistic is a widely used method to detect spatial clusters. The method imposes a large number of scanning windows with pre-defined shapes and varying sizes on the entire study region. The likelihood ratio test statistic comparing inside versus outside each window is then calculated and the window with the maximum value of test statistic becomes the most likely cluster. The results of cluster detection respond sensitively to the shape and the maximum size of scanning windows. The shape of scanning window has been extensively studied; however, there has been relatively little attention on the maximum scanning window size (MSWS) or maximum reported cluster size (MRCS). The Gini coefficient has recently been proposed by Han et al. (International Journal of Health Geographics, 15, 27, 2016) as a powerful tool to determine the optimal value of MRCS for the Poisson-based spatial scan statistic. In this paper, we apply the Gini coefficient to normal-based spatial scan statistics. Through a simulation study, we evaluate the performance of the proposed method. We illustrate the method using a real data example of female colorectal cancer incidence rates in South Korea for the year 2009.

• Transactions of Materials Processing
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• v.10 no.2
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• pp.130-136
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• 2001

The mathematical set-up model was developed to reduce the mechanical property deviation in annealed and slightly rolled steel strip. The mechanical peculiarities of skin pass rolling process, such as high friction value and non-circular contact arc, low reduction and non-negligible entry and exit elastic zones as well as central restricted deformation zone are all taken into account. The deformation of work rolls is calculated with the influence function method and arbitrary contact arc shape is permitted. The strip deformation is modeled by slab method and the entry and exit elastic deformation zones are included. The strip restricted deformation zone near the neutral point is also considered. It was revealed that the new model has better accuracy than present regression model by statistical analysis with actual mill rolling data.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.317-317
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• 2000

The mathematical set-up model was developed to reduce the mechanical property deviation in annealed and slightly rolled steel strip. The mechanical peculiarities of temper rolling process, such as high friction value and non-circular contact arc, Low reduction and non-negligible entry and exit elastic zones as well as central restricted deformation zone are all taken into account. The deformation of work rolls is calculated with the influence function method and arbitrary contact arc shape is permitted. The strip deformation is modeled by slab method and the entry and exit elastic deformation zones are included. The restricted deformation Bone near the neutral point is also considered. It was revealed that the new model has better accuracy than present regression model by statistical analysis with actual mill rolling data.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.522-524
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• 2012

For exact classification of the defect, good feature selection and classifier is necessary. In this paper, various features such as brightness features, shape features and statistical features are stated and Bayes classifier using Gaussian mixture model is used as classifier. Also feature extraction method based on spectral graph theory is presented. Experimental result shows that feature extraction method using graph Laplacian result in better performance than the result using PCA.

• Journal of Ocean Engineering and Technology
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• v.21 no.5
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• pp.55-60
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• 2007

Bellows are mechanical components which prevent the damage of system by absorption of the vibration and the displacement of axle and radial direction. Thermal piping system is expanded by the fluid of the high temperature from the heat engine inside. At this time, bellows prevent the damage of the piping due to the thermal expansion. Recently, design of bellows is required to fit some other operational environments which are not suggested in the E.J.M.A code book. And it is difficult to produce and to maintain bellows of high temperature and high pressure bemuse of its complicated shape and this causes the manufacturing cost to rise. The objective of this study is to determine optimum shape of bellows which can endure in the high temperature and high pressure. The maximum stress has an effect on the fatigue life of bellows, therefore it needs to be minimized. This study attempts to find a shape which minimizes the stress occurring in the bellows by the design of experiment. The model used in this study is not presented in the E.J.M.A code book, therefore, from the result of design of experiment we find the factors which give effects on the characteristic value and we presents the recession model using the RSM, which can predict the characteristic values depending on the change of factor values.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.289-298
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• 1998

We investigate the distribution of likelihood ratio test(LRT) of null hypothesis a sample is from single gamma with unknown shape and scale against the alternative hypothesis a sample is from a mixture of two gammas, each with unknown scale and unknown (but equal) scale. To obtain stable maximum likelihood estimates(MLE) of a mixture of two gamma distributions, the EM(Dempster, Laird, and Robin(1977))and Modified Newton(Jensen and Johansen(1991)) algorithms were implemented. Based on EM, we made a simple structure likelihood equation for each parameter and could obtain stable solution by Modified Newton Algorithms. Simulation study was conducted to investigate the distribution of LRT for sample size n = 25, 50, 75, 100, 50, 200, 300, 400, 500 with 2500 replications. To determine the small sample distribution of LRT, I considered the model of a gamma distribution with shape parameter equal to 1 + f(n) and scale parameter equal to 2. The simulation results indicate that the null distribution is essentially invariant to the value of the shape parameter. Modeling of the null distribution indicates that it is well approximated by a gamma distribution with shape parameter equal to the quantity $0.927+1.18/\sqrt{n}$ and scale parameter equal to 2.16.

• Structural Engineering and Mechanics
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• v.38 no.6
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• pp.715-732
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• 2011

A novel structural damage detection method with a new damage index has been recently proposed by the authors based on the statistical moments of dynamic responses of shear building structures subject to white noise ground motion. The statistical moment-based damage detection (SMBDD) method is theoretically extended in this paper with general application. The generalized SMBDD method is more versatile and can identify damage locations and damage severities of many types of building structures under various external excitations. In particular, the incomplete measurements can be considered by the proposed method without mode shape expansion or model reduction. Various damage scenarios of two general forms of building structures with incomplete measurements are investigated in consideration of different excitations. The effects of measurement noise are also investigated. The damage locations and damage severities are correctly identified even when a high noise level of 15% and incomplete measurements are considered. The effectiveness and versatility of the generalized SMBDD method are demonstrated.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.08a
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• pp.438-446
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• 1999

Crop minimization of the top and bottom ends of hot rolled plate, in a plate, in a plate mill, has been investigated. The existing model to determine the edging pattern at the finishing rolling pass was not reasonable to get high width accuracy and rolling yields. New models including width prediction have been formulated by using neural network model of back propagation learning algorithm and statistical analysis based on the actual production rolling data to give the optimal pattern for minimizing trimming loss. Using these models, at a given rolling condition of broadside pass and finishing pass and the permissible condition of width variation, it was possible to minimize crip at the top and bottom ends according to optimum procedure in plate mill. An application to improve the plan view pattern reduced width variation by 23% and crop length by 30% on average with an effective fishtail crop shape.

• Journal of KIISE
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• v.41 no.11
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• pp.921-926
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• 2014

Face detection refers to the process extracting facial regions in an input image, which can improve speed and accuracy of recognition or authorization system, and has diverse applicability. Since conventional works have tried to detect faces based on the whole shape of faces, its detection performance can be degraded by occlusion made with accessories or parts of body. In this paper we propose a method combining local feature descriptors and probability modeling in order to detect partially occluded face effectively. In training stage, we represent an image as a set of local feature descriptors and estimate a statistical model for normal faces. When the test image is given, we find a region that is most similar to face using our face model constructed in training stage. According to experimental results with benchmark data set, we confirmed the effect of proposed method on detecting partially occluded face.