• Nuclear Engineering and Technology
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• 제30권4호
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• pp.364-376
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• 1998

The statistical analysis method was applied to the evaluation of fracture toughness in the ductile-brittle transition temperature region. Because cleavage fracture in steel is of a statistical nature, fracture toughness data or values show a similar statistical trend. Using the three-parameter Weibull distribution, a fracture toughness vs. temperature curve (K-curve) was directly generated from a set of fracture toughness data at a selected temperature. Charpy V-notch impact energy was also used to obtain the K-curve by a $K_{IC}$ -CVN (Charpy V-notch energy) correlation. Furthermore, this method was applied to evaluate the neutron irradiation embrittlement of reactor pressure vessel (RPV) steel. Most of the fracture toughness data were within the 95% confidence limits. The prediction of a transition temperature shift by statistical analysis was compared with that from the experimental data.

• 응용통계연구
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• 제25권6호
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• pp.1027-1036
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• 2012

Among various biometrics recognition systems, statistical fingerprint recognition matching methods are considered using minutiae on fingerprints. We define similarity distance measures based on the coordinate and angle of the minutiae, and suggest a fingerprint recognition model following statistical distributions. We could obtain confidence intervals of similarity distance for the same and different persons, and optimal thresholds to minimize two kinds of error rates for distance distributions. It is found that the two confidence intervals of the same and different persons are not overlapped and that the optimal threshold locates between two confidence intervals. Hence an alternative statistical matching method can be suggested by using nonoverlapped confidence intervals and optimal thresholds obtained from the distributions of similarity distances.

• 한국식품과학회지
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• 제51권3호
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• pp.227-236
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• 2019

Antioxidant activity in water and ethanol extracts of dried Lycium chinense fruit, as a result of the total phenolic and tannin content, was measured using a number of chemical and biochemical assays for radical scavenging and inhibition of lipid peroxidation, with the analysis being extended by applying a bootstrapping statistical method. Previous statistical analyses mostly provided linear correlation and regression analyses between antioxidant activity and increasing concentrations of phenolics and tannins in a concentration-dependent mode. The present study showed that multiple component or multivariate analysis by applying multiple regression analysis or regression planes proved more informative than linear regression analysis of the relationship between the concentration of individual components and antioxidant activity. In this paper, we represented the multivariate analysis of antioxidant activities of both phenolic and tannin contents combined in the water and ethanol extracts, which revealed the hidden observations that were not evident from linear statistical analysis.

• Communications for Statistical Applications and Methods
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• 제21권1호
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• pp.105-114
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• 2014

In this paper we suggest an efficient method to estimate the distribution function using the Bezier curve, and compare it with existing methods by simulation studies. In addition, we suggest a robust version of cross-validation criterion to estimate the number of Bezier points, and showed that the proposed method is better than the existing methods based on simulation studies.

• 응용통계연구
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• 제3권1호
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• pp.121-141
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• 1990

컴퓨터의 발전에 따른 통계방법 중에서 붓스트랩(bootstrap)에 대하여 연구하였다. 특히 추축통계량의 표본분포를 붓스트랩분포로 추정하는데 있어서 계산문제와 이론적인 정당성을 고려하였으며, 모분포의 성격을 나타내는 모수의 붓스트랩 신뢰영역을 몇 가지 사례들에 대해 살펴보았고 사례별로 붓스트랩 방법의 의미를 고찰하였다.

• Communications for Statistical Applications and Methods
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• 제7권3호
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• pp.759-766
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• 2000

In order to design fractional factorial experiments which include some debarred combinations, we should select defining contrasts so that those combinations are to be excluded. Choi(1999) presented a method of selectign defining contrasts to construct orthogonal 3-level fractional factorial experiments which exclude some debarred combinations. In this paper, we extend Choi's method to general p-level fractional factorial experiments to select defining contrasts which cold exclude some debarred combinations.

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.793-798
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• 2012

In this paper, we propose regression methods based on the likelihood function. We assume Arnold-Beaver Skew Normal(ABSN) errors in a simple linear regression model. It was shown that the novel method performs better with an asymmetric data set compared to the usual regression model with the Gaussian errors. The utility of a novel method is demonstrated through simulation and real data sets.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -1
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• pp.517-520
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• 2000

This paper deals with the statistical analysis of an autocalibration procedure for the gain and phase imbalances between the in-phase (I) and quadrature (Q) components in quadrature receivers. In real implementation, the imbalances of the gain and phase exist and degrade the performance of the receiver. In this paper we investigate the statistical characteristic of the estimates in an on-line imbalance estimation method for the receiver under the assumption of an additive white Gaussian noise environment.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.831-842
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• 1999

We propose a wavelet decomposition feature extraction method for the hand-written character recognition. Comparing the recognition rates of which methods with original image features and with selected features by the wavelet decomposition we study the characteristics of the proposed method. LDA(Linear Discriminant Analysis) QDA(Quadratic Discriminant Analysis) RDA(Regularized Discriminant Analysis) and NN(Neural network) are used for the calculation of recognition rates. 6000 hand-written numerals from CENPARMI at Concordia University are used for the experiment. We found that the set of significantly selected wavelet decomposed features generates higher recognition rate than the original image features.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.695-706
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• 1999

When fractional factorial experiments contain some infeasible treatment combinations called debarred combinations we should construct experimental designs so that those debarred combinations are to be excluded by selecting defining contrasts appropriately. By applying Franklin(1995)'s procedure for selecting defining contrasts to Cheng and Li(1993)'s method this paper presents a method of selecting defining contrasts to construct orthogonal 3-level fractional factorial experiments which exclude some debarred combinations.