• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.297-302
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• 2005

In this paper, an estimating damage on external surface of container using Capsize-Gaussian-Function (be called CGF) is presented. The estimation of the damage size can be get directly from two parameters of CGF, these are the depth and the flexure, also the direction of damage. The performance of the present method has been illustrated using an image of damage container, which had been taken from Hanjin Busan Port, after using image processing techniques to do preprocessing of the image, especially, the main used technique is Canny edge detecting that is widely used in computer vision to locate sharp intensity and to find object boundaries in the image, then correlation between the edge image from the preprocessing step and the CGF with three parameters (direction, depth, flexure), as a result, we get an image that perform damage information, and these parameters is an estimator directly to the damage.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.5
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• pp.563-570
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• 2004

Two-dimensional mesoscopic analysis (meso-analysis) is applied to solids including microdefects such as microcracks or holes. For the problem of effective moduli of microdefrcted solids, various approximate schemes are introduced by using microcrack density and hole density for macro level parameter. Also, microcracks distributed in the parallel direction and random direction are considered. Several numerical studies using meso-analysis are carried out and the results are compared with several approximate schemes in order to show the validity of proposed meso-analysis.

• Communications for Statistical Applications and Methods
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• v.28 no.1
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• pp.21-37
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• 2021

There is a direct connection between linear discriminant analysis (LDA) and linear regression since the direction vector of the LDA can be obtained by the least square estimation. The connection motivates the penalized LDA when the model is high-dimensional where the number of predictive variables is larger than the sample size. In this paper, we study the penalized LDA for a class of penalties, called the moderately clipped LASSO (MCL), which interpolates between the least absolute shrinkage and selection operator (LASSO) and minimax concave penalty. We prove that the MCL penalized LDA correctly identifies the sparsity of the Bayes direction vector with probability tending to one, which is supported by better finite sample performance than LASSO based on concrete numerical studies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.177-179
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• 2021

This paper proposes a method of estimating location of a target point at which an interactive robot gazes in an indoor space. RGB images are extracted from low-cost web-cams, user head pose is obtained from the face detection (Openface) module, and geometric configurations are applied to estimate the user's gaze direction in the 3D space. The coordinates of the target point at which the user stares are finally measured through the correlation between the estimated gaze direction and the plane on the table plane.

• Journal of Korea Water Resources Association
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• v.38 no.8 s.157
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• pp.617-629
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• 2005

In this paper, a hypothesis is tested that division of non-monotonic time series into monotonic parts will improve the estimation of trends through increased homogeneity in direction of time-variation using LOWESS smoothing and seasonal Kendall test. From the trend analysis of generated time series and water temperature, discharge, air temperature and solar radiation of Lake Daechung, it is shown that the hypothesis is supported by improved estimation of trends and slopes. Also, characteristics in homogeneity variation of seasonal changes seems to be more clearly manifested as homogeneity in direction of time-variation is increased. And this will help understand the effects of human intervention on natural processes and seems to warrant more in-depth study on this subject. The proposed method can be used for trend analysis to detect monotonic trends and it is expected to improve understanding of long-term changes in natural environment.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.322-331
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• 2017

In this paper we present a novel robotic palpation method for the lump shape estimation using contact pressure distribution. Many previous researches about the robotic palpation have used a stiffness map, which is not suitable to obtain geometrical information of a lump. As a result, they require a large data set and long palpation time to estimate the lump shape. Instead of using the stiffness map, the proposed palpation method uses the difference between the normal force direction and the surface normal to detect the lump boundary and estimate its normal. The palpation trajectory is generated by the normal of the lump boundary to track the lump boundary in real-time. The proposed approach requires small data set and short palpation time for the lump shape estimation since the shape can be directly estimated from the optimally generated palpation trajectory. An experiment result shows that our method can find the lump shape accurately in real-time with small data and short time.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.543-556
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• 2015

We present a survey of contributions that defined the nature and extent of robust statistics for the last 50 years. From the pioneering work of Tukey, Huber, and Hampel that focused on robust location parameter estimation, we presented various generalizations of these estimation procedures that cover a wide variety of models and data analysis methods. Among these extensions, we present linear models, clustered and dependent observations, times series data, binary and discrete data, models for spatial data, nonparametric methods, and forward search methods for outliers. We also present the current interest in robust statistics and conclude with suggestions on the possible future direction of this area for statistical science.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.1
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• pp.28-36
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• 2009

In this paper, based on the measured data of hull deflection, an approximated hull deflection curve is drawn using reverse analyzed hull deflection data and the estimation method for flexibility analysis of shaft alignment is proposed by use of the approximate hull deflection curve. Generally an offset value of after stern tube bearing is a datum point with an fore stern tube bearing however the shaft alignment has a tendency which is able to get higher flexibility if the shafting system has the deflection value from after stern tube bearing as reference to bottom direction according to results of on this study. By applying this result of study, the shaft alignment for next similar ships will be able to estimate how to follow the hull deflection and how to be influenced by hull deflection at shaft alignment analysis state using the approximated hull deflection curve.

• Journal of the Korean Geographical Society
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• v.36 no.3
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• pp.313-328
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• 2001

The lichen is generally used as a bio-indicator for the estimation of air pollution. The purpose of this research is to diagnose the level of air pollution by means of lichen Chongju region, relative to the direction of the dominant Wind(WNW) and the distance from the air pollution source. As a result it reveals that the industrial estate, its surroundings and inner city are confronting lichen desert phenomenon, According to the I.A.P index the average SO$_2$density in Chongju city in estimated above 0.03 ppm. However, the number of lichen species and its coverage are increased as the distance becomes further from the pollution source.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.64-72
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• 2016

The coverage area of a GNSS regional ionospheric delay model is mainly determined by the distribution of GNSS ground monitoring stations. Extrapolation of the ionospheric model data can extend the coverage area. An extrapolation algorithm, which combines observed ionospheric delay with the environmental parameters, is proposed. Neural network and least square regression algorithms are developed to utilize the combined input data. The bi-harmonic spline method is also tested for comparison. The IGS ionosphere map data is used to simulate the delays and to compute the extrapolation error statistics. The neural network method outperforms the other methods and demonstrates a high extrapolation accuracy. In order to determine the directional characteristics, the estimation error is classified into four direction components. The South extrapolation area yields the largest estimation error followed by North area, which yields the second-largest error.