• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.615-625
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• 2009

In this paper we describe Wilcoxon test and T-test that are well-known in two-sample location problem for detecting edges under different window configurations. The choice of window configurations is an important factor in determining the performance and the expense of edge detectors. Our edge detectors are based on testing the mean values of local neighborhoods obtained under the edge model using an edge-height parameter. We compare three window configurations based on statistical tests in terms of qualitative measures with the edge maps and objective, quantitative measures as well as CPU time for detecting edge.

• Transactions on Electrical and Electronic Materials
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• v.17 no.1
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• pp.1-6
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• 2016

Ensuring the secure operation of power systems has become an important and critical matter during the present time, along with the development of large, complex and load-increasing systems. Security constraints such as the thermal limits of transmission lines and bus-voltage limits must be satisfied under all of a system’s operational conditions. An alternative solution to improve the security of a power system is the employment of Flexible Alternating-Current Transmission Systems (FACTS). FACTS devices can reduce the flows of heavily loaded lines, maintain the bus voltages at desired levels, and improve the stability of a power network. The Unified Power Flow Controller (UPFC) is a versatile FACTS device that can independently or simultaneously control the active power, the reactive power and the bus voltage; however, to achieve such functionality, it is very important to determine the optimal location of the UPFC device, with the appropriate parameter setting, in the power system. In this paper, a genetic algorithm (GA) method is applied to determine the optimal location of the UPFC device in a network for the enhancement of the power-system loadability and the minimization of the active power loss in the transmission line. To verify our approach, simulations were performed on the IEEE 14 Bus, 30 Bus, and 57 Bus test systems. The proposed work was implemented in the MATLAB platform.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.195-202
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• 2011

The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.6
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• pp.56-62
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• 2005

The fatigue analysis and lifetime evaluation are very important in design procedure to assure the safety and reliability of the rubber components. Fatigue lifetime prediction methodology of the rubber component was proposed by incorporating the finite element analysis and fatigue damage parameter from fatigue test. Finite element analysis of 3D dumbbell specimen and rubber component were performed based on a hyper-elastic material model determined from material test. The Green-Lagrange strain at the critical location determined from the FEM was used for evaluating the fatigue damaged parameter of the natural rubber. Fatigue life of the rubber component are predicted by using the fatigue damage parameter at the critical location. Predicted fatigue lifes of the rubber component agreed fairly well the experimental fatigue lives.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.9
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• pp.999-1004
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• 2014

In the present paper, the effects of initial crack location on spatial randomness of fatigue crack growth resistance (FCGR) in friction stir welded (FSWed) AA7075-T651 plates were studied. The objective of this study is to characterize the statistical properties of FCGR for three different types of initial crack location (ICL) specimens. In this work, the FCGR coefficients were treated as a spatial random process. It was found that the FCGR coefficients for all initial crack location specimens closely followed a two parameter Weibull distribution. The shape parameter of the Weibull distribution for BM-ICL specimens showed the largest value of 7.50, and that for the WM-ICL specimens showed the smallest value of 2.61. In addition, the autocorrelation functions for all the ICL specimens followed the exponential function.

• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.649-661
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• 2001

While the conventional edge detection can be considered as the problem of determining the existence of edges at certain locations, the fuzzy edge modeling can be considered as the problem of determining the membership values of edges. Thus, if the location of an edge is unclear, or if the intensity function is different from the ideal edge model, the degree of edgeness at the location is represented as a fuzzy membership value. Using the concept of fuzzy edgeness, an automatic smoothing parameter evaluation and selection method for a conventional edge detector is proposed. This evaluation method uses the fuzzy edge modeling, and can analyze the effect of smoothing parameter to determine an optimal parameter for a given image. By using the selected parameter we can detect least ambiguous edges of a detection method for an image. The effectiveness of the parameter evaluation method is analyzed and demonstrated using a set of synthetic and real images.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.116-122
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• 2016

Recently, the production cycle in manufacturing process has been getting shorter and different types of product have been produced in the same process line. In this case, the control chart using coefficient of variation would be applicable to the process. The theory that random variables are located in the three times distance of the deviation from mean value is applicable to the control chart that monitor the process in the manufacturing line, when the data of process are changed by the type of normal distribution. It is possible to apply to the control chart of coefficient of variation too. ${\bar{x}}$, s estimates that taken in the coefficient of variation have just used all of the data, but the upper control limit, center line and lower control limit have been settled by the effect of abnormal values, so this control chart could be in trouble of detection ability of the assignable value. The purpose of this study was to present the robust control chart than coefficient of variation control chart in the normal process. To perform this research, the location parameter, ${\bar{x_{\alpha}}}$, $s_{\alpha}$ were used. The robust control chart was named Tim-CV control chart. The result of simulation were summarized as follows; First, P values, the probability to get away from control limit, in Trim-CV control chart were larger than CV control chart in the normal process. Second, ARL values, average run length, in Trim-CV control chart were smaller than CV control chart in the normal process. Particularly, the difference of performance of two control charts was so sure when the change of the process was getting to bigger. Therefore, the Trim-CV control chart proposed in this paper would be more efficient tool than CV control chart in small quantity batch production.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.329-331
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• 2005

This paper proposes a line-to-ground cable fault location method for underground distribution system. The researched cable is composed of core and sheath. And underground cabke system has been analyzed using Distributed Parameter Circuit. The effectiveness of proposed algorithm has been verified through EMTDC simulations.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.59-70
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• 1997

We introduce several estimators of the location and the scale parameters of the two-parameter exponential distribution, and then compare these estimators by the mean square error (MSE). Using the parametric bootstrap estimators and the delete-d jackknife, we obtain the bootstrap and the delete-d jackknife confidence intervals for the location and the scale parameters and compare the bootstrap confidence intervals with the delete-d jackknife confidence intervals by length and coverage probability through Monte Carlo method.

• Journal of Korean Society for Quality Management
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• v.19 no.1
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• pp.51-64
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• 1991

This paper deals with a robust subset selection procedure based on Hodges-Lehmann estimators of location parameters. An improved formula for the estimated standard error of Hodges-Lehmann estimators is considered. Also, the degrees of freedom of the studentized Hodges-Lehmann estimators are investigated and it is suggested to use 0.8n instead of n-1. The proposed procedure is compared with the other subset selection procedures and it is shown to have good effciency for heavy-tailed distributions.