• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1287-1294
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• 2004

Recently relationships between reliability measures and the coverage have been developed for evaluation of software reliability. Particularly the mean value function of the coverage-based software reliability growth model is important because of its key role in rep-resenting the software reliability growth. In this paper, we first review the problems of the existing mean value functions with respect to the assumptions on which they are based. Then a new mean value function is proposed. The new mean value function is developed for a general testing environment in which imperfect fault detection and repeated construct execution are allowed. Finally performance of the proposed model is empirically evaluated by applying it to a real data set.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.510-513
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• 2002

대부분의 이진화 알고리즘은 임계치를 결정하기 위하여 히스토그램을 사용하여 밝기분포를 분석한다. 배경과 물체의 명도차이가 큰 경우에는 분할을 위해 양봉(bimodal) 히스토그램으로 표현하여 최적의 임계치를 찾기 위해 히스토그램 골짜기(valley)를 선택하는 것만으로도 양호한 임계치 결과를 얻을수 있으나, 배경과 물체의 밝기 차이가 크지 않거나 밝기 분포가 양봉 특성을 보이지 않을 때는 히스토그램 분석만으로 적절한 임계치를 얻기 어렵다. 그리고 한 영상에서는 넓은 영역에 걸쳐 명암도 변화가 일어나고 다양한 유형의 물체가 포함되어 있으므로 스케치 특징점 유무를 판별하는 임계치의 결정에는 애매 모호함이 존재한다. 따라서 본 논문에서는 영상에 대해 삼각형 타입의 소속함수를 적용하여 임계치를 동적으로 설정하고 영상을 이진화하는 방법을 제안한다. 제안된 퍼지 이진화 방법은 평균 밝기 값을 기준으로 가장 어두운 픽셀 값과 가장 밝은 픽셀값의 거리를 계산하여 밝기의 조정률을 구하여 최소 밝기값과 최대 밝기 값을 설정하고 삼각형의 소속 함수에 적용한다. 소속 함수에 적용된 소속도를 a-cut 을 적용하여 영상을 이진화한다. 다양한 영상에 적용한 결과, 기존의 이진화 방법보다 제안된 퍼지 이진화 방법이 효율적인 것을 알 수 있었다.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.131-143
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• 1994

Under the asymmetric losses (entropy loss and Stein loss), we find the classes of Bayes and empiricla Bayes estimates for estimating the Poisson means when the distributin of means are believed a priori. Following the idea of Efron and Morris (1973), we have a computer simulation to compute a relative savings loss of proposed estimates as compared to the classical estimates.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2003.06a
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• pp.21-26
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• 2003

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.5
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• pp.526-534
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• 2014

In this study, single-input transfer function model is applied to forecast monthly mean sea surface temperature(SST) in 2010 at Yeosu in Korean coastal waters. As input series, monthly mean air temperature series for ten years(2000-2009) at Yeosu in Korea is used, and Monthly mean SST at Yeosu station in Korean coastal waters is used as output series(the same period of input). To build transfer function model, first, input time series is prewhitened, and then cross-correlation functions between prewhitened input and output series are determined. The cross-correlation functions have just two significant values at time lag at 0 and 1. The lag between input and output series, the order of denominator and the order of numerator of transfer function, (b, r, s) are identified as (0, 1, 0). The selected transfer function model shows that there does not exist the lag between monthly mean air temperature and monthly mean SST, and that transfer function has a first-order autoregressive component for monthly mean SST, and that noise model was identified as $ARIMA(1,0,1)(2,0,0)_{12}$. The forecasted values by the selected transfer function model are generally $0.3-1.3^{\circ}C$ higher than actual SST in 2010 and have 6.4 % mean absolute percentage error(MAPE). The error is 2 % lower than MAPE by ARIMA model. This implies that transfer function model could be more available than ARIMA model in terms of forecasting performance of SST.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.409-420
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• 2001

Recently a new approach to evaluation of software reliability, one of important attributes of a software system, during testing has been devised. This approach utilizes test coverage information. The coverage-based software reliability growth models recently appeared in the literature are first reviewed and classified into two classes. Inherent problems of each of the two classes are then discussed and their validity is empirically investigated. In addition, a new mean value function in coverage and a heuristic procedure for selecting the best coverage are proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.513-515
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• 2015

본 논문에서는 다양한 영상에서 객체들의 정보 손실을 최소화한 상태에서 영상을 이진화하기 위해 ${\alpha}-cut$을 동적으로 설정하는 개선된 퍼지 이진화 방법을 제안한다. 제안된 퍼지 이진화 방법은 평균 밝기 값을 기준으로 가장 어두운 픽셀 값과 가장 밝은 픽셀 값의 거리를 계산하여 소속 함수의 구간을 설정한다. 그리고 소속 함수에서 소속도를 구한 후, 영상을 이진화 하기 위해 최대 밝기 값에서 중간 밝기 값을 나눈 값을 ${\alpha}-cut$값으로 설정한 후에 구간 임계치를 이용하여 영상을 이진화 한다. 제안된 퍼지 이진화 방법의 효율성을 확인하기 위해 다양한 영상을 대상으로 실험한 결과, 기존의 퍼지 이진화 방법보다 객체와 배경 사이의 명암도가 한쪽에 치우친 분포를 가진 영상과 넓게 분포된 영상에서 모두 객체들의 정보의 손실이 적은 상태에서 이진화되는 것을 확인할 수 있었다.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.527-540
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• 2020

While analyzing data, researching outliers, which are out of the main tendency, is as important as researching data that follow the general tendency. In this study we discuss the influence function for outlier discrimination. We derive sample influence functions of sample mean, sample variance, and sample standard deviation, which were not directly derived in previous research. The results enable us to mathematically examine the relationship between the empirical influence function and sample influence function. We can also consider a method to approximate the sample influence function by the empirical influence function. Also, the validity of the relationship between the approximated sample influence function and the empirical influence function is also verified by the simulation of random sampled data in normal distribution. As the result of a simulation, both the relationship between the two influence functions, sample and empirical, and the method of approximating the sample influence function through the emperical influence function were verified. This research has significance in proposing a method that reduces errors in the approximation of the empirical influence function and in proposing an effective and practical method that proceeds from previous research that approximates the sample influence function directly through empirical influence function by constant revision.

• Journal of the Korean Magnetics Society
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• v.26 no.3
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• pp.81-85
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• 2016

This paper introduces a performance integration method to predict variation characteristic of a performance function of electromagnetic machines or devices due to manufacturing tolerances. A normalized performance function space and a hybrid mean value technique are adapted to effectively predict mean and variance, which can identify probabilistic distribution of the performance function. To verify the effectiveness and accuracy of the proposed method, a mathematical problem and a loudspeaker model are tested, and numerical results are compared with those of existing methods such as Monte Carlo simulation and univariate dimension reduction method.

• The Korean Journal of Nuclear Medicine
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• v.39 no.4
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• pp.257-262
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• 2005

Purpose: Gastric emptying scan (GES) is usually acquired up to 2 hours. Our study investigated whether a fraction of meal-retention in the stomach at 120 minutes (FR120) was predicted from the data measured for 90 minutes by using non-linear curve fitting. We aimed at saving the delayed imaging by utilizing mathematical models. Materials and Methods: Ninety-six patients underwent GES immediately after taking a boiled egg with 74 MBq (2 mCi) Tc-99m DTPA. The patients were divided into Group I ($T_{1/2}\;{\leq}90\;min$) and Group II ($90\;min). Group I (n=51) had 21 men and 30 women, and Group II (n=45) 15 men and 30 women. There was no significant difference in age and sex between the two groups. Simple exponential, power exponential, and modified power exponential curves were acquired from the measured fraction of meal-retention at each time (0, 15, 30, 45, 60, 75, and 90 min) by non-linear curve fitting ($MATLAB^{\circledR}$ 5.3) and another simple exponential fitting was performed on the fractions at late times (60, 75, and 90 min). A predicted FR120 was calculated from the acquired functional formulas. A correlation coefficient between the measured FR120 and the predicted FR120 was computed ($MedCalc^{\circledR}$ 6.0). Results: Correlation coefficients(r) between the measured FR120 and the predicted FR120 of each mathematical functions were as follows: simple exponential function (Group I: 0.8558, Group II: 0.5982, p<0.0001), power exponential function (Group I: 0.8755, Group II: 0.6008, p<0.0001), modified power exponential function (Group I: 0.8892, Group II: 0.5882, p<0.0001), and simple exponential function at the late times(Group I: 0.9085, Group II: 0.6832, p<0.0001). In all the fitting models, the predicted FR120 were significantly correlated with the measured FR120 in Group I but not in Group II. There was no statistically significant difference in correlation among the 4 mathematical models. Conclusion: In the cases with $T_{1/2}\;{\leq}90\;min$, the predicted FR120 is significantly correlated with the measured FR120. Therefore, FR120 can be predicted from the data measured for 90 minutes by using non-linear curve fitting, saving the delayed imaging after 90 minutes when $T_{1/2}\;{\leq}90\;min$ is ascertained.