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肝疾患의 Immunoglobulin量 變動에 관한 臨床的 硏究
金宗克,高侊道 고려대학교 의과대학 1975 고려대 의대 잡지 Vol.12 No.1
Author has studied 62 subjects who had been admitted to the Department of Gastroenterology, Medical College of Korea University and diagnosed by liver biopsy and 10 healthy Koreans from July, 1972 to Sept., 1973. Blood collected from the patients had been stored in freezing at -20 degree centigrade. The results of this study are as follows. 1. Blood level of immunoglobulins (Mean±Standard Deviation) in healthy Koreans are: IgG 1,387±254, IgA 171±78, IgM 94±33. The unit is ㎎/dl. 2. In acute hepatitis including icteric and nonicteric cases IgG is 1,616±314 and increased above normal range in 50 per cent of cases by mild degree with statistical significance. IgA is 313±86 and increased in 63 per cent by high degree with statistical significance and IgM is 133±66 and increased in 44 per cent by moderate degree with statistical significance. 3. In chronic hepatitis IgG is 1,788±302 and increased above normal range in 64 per cent of cases by mild degree with statistical significance. IgA is 347±127 and increased in 73 per cent by high degree with statistical significance. IgM is 143±80 and increased in 45 per cent by moderate degree without statistical significance. 4. In liver cirrhosis IgG is 1,958±449 and increased above normal range in 78 per cent by moderate degree with statistical significance. IgA is 390±129 and increased in 83 per cent by high degree with statistical significance. IgM is 160±69 and increased in 72 per cent by high degree with statistical significance. 5. In primary hepatoma IgG is 1,649±402 and increased above normal range in 71 per cent by mild degree without statistical significance. IgA is 376±171 and increased in 71 per cent by high degree with statistical significance. IgM is 149±66 and increased in 57 per cent by mild degree without statistical significance. 6. In reactive hepatitis IgG is 1,571±383 and increased above normal range in 40 per cent by mild degree without statistical significance. IgA is 333±130 and increased in 80 per cent by high degree with statistical significance. IgM is 123±62 and increased in 40 per cent by mild degree without statistical significance.
Bootstrap Prediction Interval estimator of SVM
김대학 한국자료분석학회 2004 Journal of the Korean Data Analysis Society Vol.6 No.3
Prediction interval estimation based on bootstrap method is presented for the support vector machine regressions, which allow us to perform even nonlinear regression by constructing a linear regression function in a high dimensional feature space. The bootstrap is applied to generate the bootstrap samples for the estimation of the covariance of the regression parameters consisting of the optimal bias and Lagrange multipliers. Experimental results are given which indicate the performance of proposed algorithm.
A comparison on the differential Entropy
김대학 한국데이터정보과학회 2005 한국데이터정보과학회지 Vol.16 No.3
Entropy is the basic concept of information theory. It is well defined for random varibles with known probability density function(pdf). For given data with unknown pdf, entropy should be estimated. Usually, estimation of entropy is based on the approximations. In this paper, we consider a kernel based approximation and compare it to the cumulant approximation method for several distributions. Monte carlo simulation for various sample size is conducted.
Comparison of EKF and UKF on training the artificial neural network
김대학 한국데이터정보과학회 2004 한국데이터정보과학회지 Vol.15 No.2
The Unscented Kalman Filter is known to outperform the Extended Kalman Filter for the nonlinear state estimation with a significance advantage that it does not require the computation of Jacobian but EKF has a competitive advantage to the UKF on the performance time. We compare both algorithms on training the artificial neural network. The validation data set is used to estimate parameters which are supposed to result in better fitting for the test data set. Experimental results are presented which indicate the performance of both algorithms.
Application of bootstrap method for change point test based on kernel density estimator
김대학 한국데이터정보과학회 2004 한국데이터정보과학회지 Vol.15 No.1
Change point testing problem is considered. Kernel density estimators are used for constructing proposed change point test statistics. The proposed method can be used to the hypothesis testing of not only parameter change but also distributional change. Bootstrap method is applied to get the sampling distribution of proposed test statistic. Small sample Monte Carlo Simulation were also conducted in order to show the performance of proposed method.
On-Line Pruning Regression Method by LS-SVM
김대학 한국자료분석학회 2005 Journal of the Korean Data Analysis Society Vol.7 No.2
Least squares support vector machine(LS-SVM) is a well known and useful machine learning ways for statistical classification and regression analysis. LS-SVM can be a good substitute for traditional statistical method but computational difficulties are still remained to operate the inversion of matrix of huge data set. In modern information society, we can easily obtain a large data sets by on-line or batch mode. For the analysis of these kind of huge data sets, we suggest an on-line pruning regression method based on LS-SVM. With relatively small number of pruned support vectors, we can have almost same performance as regression with full data set.
김대학,이기락 한국데이터정보과학회 2005 한국데이터정보과학회지 Vol.16 No.4
We often extract a new feature from the original features for the purpose of reducing the dimensions of feature space and better classification. In this paper, we show feature extraction method based on independent component analysis can be used for classification. Entropy and mutual information are used for the selection of ordered features. Performance of classification based on independent component analysis is compared with principal component analysis for three real data sets.
이항모수의 신뢰구간추정량에 대한 실제포함확률에 관한 연구
김대학,Kim, Dae-Hak 한국데이터정보과학회 2010 한국데이터정보과학회지 Vol.21 No.4
본 연구는 이항분포의 성공의 확률에 대한 신뢰구간추정량들을 비교분석하고자 한다. 일반적으로 대표본의 경우에 적용되는 잘 알려진 신뢰구간추정량과 소표본의 경우에도 적용될 수 있는 정확신뢰구간, 그리고 포아송 분포를 이용하여 구한 신뢰구간추정량과 연속성의 수정을 고려한 추정량들을 소 표본의 모의실험을 통하여 실제포함확률의 측면에서 비교하였다. In this paper, various methods for finding confidence intervals for the p of binomial parameter are reviewed. We compare the performance of several confidence interval estimates in terms of actual coverage probability by small sample Monte Carlo simulation.