• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1060-1070
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• 1992

In this paper, characteristics of Acoustic Emission in Low Density Polyethylene were studied from tree initiation to breakdown under long-term inhomogeneous alternative electrical field. The voltage levels used were 9, 11 and 14[kV]. Especially, a newly developed automatic measuring system was used to measure time variations of AE average amplitude, AE pulse number, AE pulse distribution patterns due to polarities. The patterns wer specially the variated patterns, when tree propagated. Also, parameters for dielectric breakdown prediction, which were suggested by Okamoto, were calculated. The result was analysed by tree shapes and partial discharge activities in tree due to tree initiation and propagation.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.539-557
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• 1998

This article is concerned with the problem of estimating the mean of a one-parameter exponential family through sequential sampling in three stages under quadratic error loss. This more general framework differs from those considered by Hall (1981) and others. The differences are : (i) the estimator and the final stage sample size are dependent; and (ii) second order approximation of a continuously differentiable function of the final stage sample size permits evaluation of the asymptotic regret through higher order moments. In particular, the asymptotic regret can be expressed as a function of both the skewness $\rho$ and the kurtosis $\beta$ of the underlying distribution. The conditions on $\rho$ and $\beta$ for which negative regret is expected are discussed. Further results concerning the stopping variable N are also presented. We also supplement our theoretical findings wish simulation results to provide a feel for the triple sampling procedure presented in this study.

• Journal of Korean Society for Quality Management
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• v.31 no.1
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• pp.109-122
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• 2003

This paper presents a robust process capability index(PCI) based on the expected loss derived from the empirical distribution function(EDF). We propose the EDF expected loss in order to develop a PCI that does not depends on the underlying process distribution. The EDF expected loss depends only on the sample data, so the PCI based on it is robust and it does nor require complex calculations. The inverted normal loss function(INLF) is employed in order to overcome the drawback of the quadratic loss which may Increase unboundedly outside the specification limits. A comprehensive simulation study was performed under various process distributions, in order to compare the accuracy and the precision of the proposed PCI with those of the PCI based on the expected loss derived from the normal distribution. The proposed PCI turned out to be more accurate than the normal PCI in most cases, especially when the process distribution has high kurtosis or skewness. It is expected that the proposed PCI can be utilized In real processes where the true distribution family may not be known.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.305-309
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• 2000

In this paper, we presents a new methodology for face recognition after analysing conventional ICA(Independent Component Analysis) based approach. In the literature we found that ICA based methods have followed the same procedure without any exception, first PCA(Principal Component Analysis) has been used for feature extraction, next ICA learning method has been applied for feature enhancement in the reduced dimension. However, it is contradiction that features are extracted using higher order moments depend on variance, the second order statistics. It is not considered that a necessary component can be located in the discarded feature space. In the new methodology, features are extracted using the magnitude of kurtosis(4-th order central moment or cumulant). This corresponds to the PCA based feature extraction using eigenvalue(2nd order central moment or variance). The synergy effect of PCA and ICA can be achieved if PCA is used for noise reduction filter. ICA methodology is analysed using SVD(Singular Value Decomposition). PCA does whitening and noise reduction. ICA performs the feature extraction. Simulation results show the effectiveness of the methodology compared to the conventional ICA approach.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.749-756
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• 2000

Chemical application, one of the most important crop management processes happened to cause spray drift, that would threaten farmers in field as well as dwellers in rural region. Spray drift was affected by micro-meteorological parameters. In Korea, a boom sprayer was introduced but good effects of a boom sprayer was not evaluated. A study to evaluate short distance drift characteristics of a boom sprayer in paddy fields has been undergoing and determining wind characteristics in paddy field was the main purpose of this paper. Micro-meteorological information has been pre-requisite information for evaluating drift in both long and short distances or in both theoretical and experimental ways. Wind velocity, Reynolds stresses, turbulence intensity, skewness, kurtosis etc. were evaluated with height from the ground using a 2-dimensional probe and a hot wire anemometer system.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.1
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• pp.56-62
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• 2011

Terrain recognition ability is crucial to the performance of legged robots in an outdoor environment. For instance, a robot will not easily walk and it will tumble or deviate from its path if there is no information on whether the walking surface is flat, rugged, tough, and slippery. In this study, the ground surface recognition ability of robots is discussed, and to enable walking robots to recognize the surface state and changes, a central moment method was used. The values of the sensor signals (load cell) of robots while walking were detected in the supported section and were analyzed according to signal variance, skewness, and kurtosis. Based on the results of such analysis, the surface state was detected and classified.

• Journal of KSNVE
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• v.4 no.3
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• pp.307-318
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• 1994

Existence of any nonlinearity in responses of a nonlinear system is tested using a kurtosis or a fourth moment which has been widely used to characterize signal patterns. By inputting a harmonic signal to a system and investigating the distortions of an output signal from a harmonic pattern, which are due to violations of proportionality between the input and the output, it is judged whether the output is generated from a nonlinear system or not. Through applying the method presented in this work to simulation studies on detections of nonlinearities of a single degree of freedom system, in which three kinds of nonlinearities are treated as restoring force terms, feasibilities of the method are shown and the range of both frequency and input amplitude, in which the system generates nonlinear responses, is determined.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.770-773
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• 2007

As higher reliability and accuracy on production facilities are required to detect incipient faults, a diagnostic system for predictive maintenance of the facility is highly recommended. In this paper, it presents a study on the application of vibration signals to diagnose faults for a Rotating Machinery using the Mahalanobis Distance-Taguchi System. RMS, Crest Factor and Kurtosis that is known as the Statistical Methods and the spectrum analysis are used to diagnose faults as parameters of Mahalanobis distance.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.318-324
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• 1998

This study was conducted to derive optimal design floods by Generalized Extreme-value(GEV) distribution for the annual maximum series at ten watersheds along Han, Nagdong, Geum, Yeongsan and Seomjin river systems. Adequacy for the analysis of flood data used in this study was established by the tests of Independence, Homogeneity, detection of Outliers. L-coefficient of variation, L-skewness and L-kurtosis were calculated by L-moment ratio respectively. Parameters were estimated by the Methods of Moments and L-Moments. Design floods obtained by Methods of Moments and L-Moments using different methods for plotting positions in GEV distribution were compared by the relative mean and relative absolute error. It was found that design floods derived by the method of L-moments using weibull plotting position formula in GEV distribution are much closer to those of the observed data in comparison with those obtained by method of moments using different formulas for plotting positions in view of relative mean and relative absolute error.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.307-309
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• 2003

생체인증에서 가장 많이 활용되고 있는 지문은 다른 생체 인증에 비해 시스템 구축 및 유지비용이 적게들며 사용자에게 거부감을 적게 주는 장점을 가지고 있다. 하지만, 입력되는 지문 영상의 상태가 가변성이 크다는 른 단점이 있다. 즉, 획득 장치의 성능과 획득되는 과정에서의 물기, 땀, 불순물, 압력의 차이 등으로 인해 입력될 때마다 영상의 품질이 달라질 수 있다는 의미이다. 이것은 인식의 성능을 떨어뜨리는 요인으로 작용하게 되는데, 이러한 약점은 인식 과정 전에 지문 영상의 품질 판정을 삽입함으로써 해결할 수 있다 본 논문은 지문의 품질 판정 방법으로 통계적 측정치인 표준편차(standard deviation), 왜도(skewness), 그리고 첨도(kurtosis) 등을 이용하였으며 , 판정된 품질에 따른 적응성 알고리즘을 적용시켜 지문 인식의 성능을 극대화시킬 수 있도록 제안하였다.