• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.294-299
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• 1993

고도로 자동화가 진전된 생산 시스템에서의 가공은 NC 공작기계, 머시닝 센터등에 의해 이루어지고 있으나, 작업 상태에 대한 감시 및 공구교환 시점의 결정은 작업자에 의해 행해지고 있으므로, 무인화에 큰 장애가 되고 있다. 최근 머시닝센터 를 중심으로 가공이 많이 이루어지고 있는 실정에서, 머시닝센터 전체 작업중 대략 40% 정도를 차지하는 드릴 작업에서 공구 상태에 대한 감시는 가공 무인화를 위해서는 필수적이다. 본 연구에서는 드릴가공시 주축 및 Z축 모터전류와 공구마멸과의 정성적 및 정량적 관련성을 조사하기 위해 전류의 진폭영역 정보인 평균, 분산, 왜도(skewness), 첨도(kurtosis)등의 신호처리를 행하여, 이들값이 공구마멸이 진행됨에따라 변화하는 특성을 조사하였다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.28-32
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• 1995

Bacause the chatter vibration is a main factor to damage on the quality and integrity, The cure is required peticurity in cykinderical plunge grinding. The chatter vibration relatied with wheel speed, workpiece and infeed rate. Therefore, we expressed more credible normal signal and chatter signal Pattern in accrdiance with wheel speed and acquired RMS signal of the accelerrometer. In thos study, after finding the chatter pattern, we applied two parameters, standard deviation and Kurtosis, to Neural Network.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11b
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• pp.569-572
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• 2003

본 연구에서는 뉴우턴법에 기초한 고정점 알고리즘의 신경망 기반 독립성분분석에 kurtosis를 추가한 독립성분의 군집화를 제안하였다. 여기서 뉴우턴법의 고정점 알고리즘은 엔트로피에 기초한 목적 함수의 근을 구하는 근사화 방법으로 빠른 성분분석을 위함이고, kurtosis는 독립성분의 추출순서를 고려하지 않는 속성을 개선하기 위함이다. 제안된 기법을 256$\times$256 픽셀의 8개 혼합영상의 분리에 적용한 결과, 제안된 방법은 기존의 독립성분분석에서 분석순서를 고려치 않는 제약을 효과적으로 해결 할 수 있음을 확인하였다.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.121-126
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• 2006

Modern Ocean wave forecasting systems predict the mean sea state, as characterized by the wave spectrum, in a box of size ${\Delta}x{\Delta}y$ surrounding a grid point at location x. It is shown that this approach also allows the determination of deviations from the mean sea state, i.e. the probability distribution function of the surface elevation. Hence, ocean wave forecasting may provide valuable information on extreme sea states.

• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.393-406
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• 1996

We obtain the general moment of non-central Wishart distribu-tion, using the J-th moment of a matrix quadratic form and the 2J-th moment of the matrix normal distribution. As an example, the second moment and kurtosis of non-central Wishart distribution are also investigated.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.679-686
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• 2007

Moment expressions are derived for the internally truncated normal distributions commonly applied to screening and constrained problems. They are obtained from using a recursive relation between the moments of the normal distribution whose distribution is truncated in its internal part. Closed form formulae for the moments can be presented up to $N^{th}$ order under the internally truncated case. Necessary theories and two applications are provided.

• Annual Conference of KIPS
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• 2004.11a
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• pp.851-854
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• 2004

본 논문에서는 독립성분분석(Independent Component Analysis, 이하 ICA)기법과 Kurtosis에서의 제안된 GBD 알고리즘을 이용한 영상 분류 방법을 제안한다. 이 제시된 방법은 기존의 GBD 알고리즘과 비교해서 영상이 급격히 변화하는 부분의 정보를 잃지 않게 개선할 수 있었다. 모의실험 결과로부터 제안된 GBD 알고리즘을 적용하여 영상을 분류할 때 편차가 줄어들어 영상간의 상대적 식별을 용이하게 하여 빨리 수렴이 되는 것을 모의실험을 통하여 확인 할 수 있었다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.12 no.1
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• pp.1-6
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• 1975

The boundary has been one of the most important information in radiographic images and the degrees of difficulty involved varies greatly with the quality of the picture. These Buantifications are the means to diagnoses. The purpose of this paper is to quantify intensity variation and the threshold decision which is based on statistical principles and is developed to detect limits in liver scintigrams the entire picture is devide4 into 64 small regions. The kurtosis and variances for each smal region are used as indications to select the histograms the thresholds are computed according to the method o(maximum likelihood which minimizes the probability o( misclassification. Therefore Ive have demonstrated the applicability of the boundary detection and proved good agreement with human recognition, and we can use it for the diagnosis data of liver disease.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.253-262
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• 2008

The main objective of this paper is to formulate a generalized procedure to extract the first four moments of univariate spatial association measures for statistical testing under the normality assumption and to evaluate the viability of hypothesis testing based on the normal approximation for each of the spatial association measures. The main results are as follows. First, predicated on the previous works, a generalized procedure under the normality assumption was derived for both global and local measures. When necessary matrices are appropriately defined for each of the measures, the generalized procedure effectively yields not only expectation and variance but skewness and kurtosis. Second, the normal approximation based on the first two moments for the global measures fumed out to be acceptable, while the notion did not appear to hold to the same extent for their local counterparts mainly due to the large magnitude of skewness and kurtosis.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.10
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• pp.965-975
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• 2005

In the case of the fault in stator windings of a high voltage motor. it facilitates certain destructive characteristics in insulations. This will result in a decreased reliability in power supplies and will prevent the generation of electricity, which will result in huge economic losses. This study simulates motor windings using normal windings and four faulty windings for an actual fault in stator winding of a high voltage motor. The partial discharge signals produced in each faulty winding were measured using an 80 PF epoxy/mica coupler sensor. In order to quantified signal waves its a way of feature extraction for each faulty signal, the signal wave of winding was quantified to measure the degree of skewness shape and kurtosis, which are both types of statistical parameters, using a discrete wavelet transformation method for each faulty type. Wave types present different types lot each faulty type, and the skewness and kurtosis also present different quantified values. The result of feature extraction was used as a preprocessing stage to identify a certain fault in stater windings. It is evident that the type of faulty signals can be classified from the test results using faulty signals that were randomly selected from the signal, which was not applied in the training after the training and learning period, by applying it to a back-propagation algorithm due to the supervising and learning method in a neural network in order to classify the faulty type. This becomes an important basis for studying diagnosis methods using the classification of faulty signals with a feature extraction algorithm, which can diagnose the fault of stator windings in the future.