• 품질경영학회지
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• 제35권4호
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• pp.159-165
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• 2007

Using statistical methods a change-point analysis of oil supply disruption is conducted. The statistical distribution of oil supply disruption is a weibull distribution. The detection of the change-point is applied to Bayesian method and weibull parameters are estimated through Markov chain monte carlo and parameter approach. The statistical approaches to the estimation for the change-point and weibull parameters is implemented with the sets of simulated and real data with small sizes of samples.

• 한국환경과학회지
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• 제17권4호
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• pp.405-412
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• 2008

Statistical analysis technique was applied to operating parameters and removal efficiency data sets obtained from advanced wastewater treatment plant during 1 year. Through factor analysis three factors derived varimax rotation were selected each plant. Three components explained 96%, 87% of the total variance of the process, respectively. The components on $A_2O$ Plant were identified in the following order : 1) Shortening the SRT during high-flow period, 2) Keeping biomass high on winter 3) factor was related to DO. On DNR plant, we defined them as follows: factor 1, Prolonged the SRT during high-flow period; factor 2 was related to sludge return; factor 3, Influent BOD during low-DO period. This technique was believed to assist operators in identifying priorities to improve operation efficiency.

• KSTLE International Journal
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• 제2권1호
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• pp.35-39
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• 2001

In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

• 대한의용생체공학회:의공학회지
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• 제10권3호
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• pp.289-292
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• 1989

In this study we propose an approach based on statistical method which use the whole of saccades instead of using a few points of saccades in the quantitative analyse saccades. We computed statistical parameters such as mean velocity, quadratic mean velocity, standard duration, skewness of saccades velocity, flattness factor of saccades velocity, and mean delay by considering eye velocity as a probability density function. The results abtained are the following as ; This parameters showed the same trend like that of the main sequence. They were not biased by the systematic errors due to the arbitrary threshold. They were also less sensitive to noise, which was tested through the model simulation. So they are expected to provide a more comprehensive quantitative description of the dynamic properties of saccade in the diagnostic field.

• 한국시뮬레이션학회논문지
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• 제3권1호
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• pp.17-28
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• 1994

A statistical procedure is developed to estimate the relative difference between two parameters each obtained from either true model or approximate model. Double sample procedure is applied to find the additional number of simulation runs satisfying the preassigned absolute precision of the confidence interval. Two types of parameters, mean and standard deviation, are considered as the performance measures and tried to show the validity of the model by examining both queues and inventory systems. In each system it is assumed that there are three distinct means and their own standard deviations and they form the simultaneous confidence intervals but with control in the sense that the absolute precision for each confidence interval is bounded on the limits with preassigned confidence level. The results of this study may contribute to some situations, for instance, first, we need a statistical method to compare the effectiveness between two alternatives, second, we find the adquate number of replications with any level of absolute precision to avoid the unrealistic cost of running simulation models, third, we are interested in analyzing the standard deviation of the output measure, ..., etc.

• 대한전자공학회논문지
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• 제19권2호
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• pp.1-6
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• 1982

본 논문에서는 런덤파라미터를 포함하는 선형 시스템의 실제 해석에 perturbation 이론의 응용을 보이고 있다. 시스템의 출력의 통계치가 시스템의 파라미터와 입력의 통계치들에 의해 (perturb된 선형 연산자 방정식에 의해) 구해졌고, perturb된 state 변환 매트릭스도 유도되었다. 간단한 일차, 이차 선형 시스템 모델을 가지고, 정확한 해와 perturbation 결과사이의 정확도가 비교되어 졌고 perturbation series의 수렴도도 조사되어 졌다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.2
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• pp.1163-1167
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• 2003

As a PD classification method, statistical distribution parameters have been used during several ten years. And this parameters are recently finger print method, NN(Neural Network) and etc. So in this paper we studied finger print method and NN with BP(Back propagation) learning algorithm using the statistical distribution parameter, and compared with two method as classification method. As a result of comparison, classification of NN is more good result than Finger print method in respect to calculation speed, visible effect and simplicity. So, NN has more advantage as a tool for PD classification.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.181-186
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• 2005

Many data sets obtained from surveys or medical trials often include missing observations. When these data sets are analyzed, it is general to use only complete cases. However, it is possible to have big biases or involve inefficiency. In this paper, we consider a method for estimating parameters in logistic linear models involving non-ignorable missing data mechanism. A binomial response and normal exploratory model for the missing data are used. We fit the model using the EM algorithm. The E-step is derived by Metropolis-hastings algorithm to generate a sample for missing data and Monte-carlo technique, and the M-step is by Newton-Raphson to maximize likelihood function. Asymptotic variances of the MLE's are derived and the standard error and estimates of parameters are compared.

• 한국농공학회지
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• 제43권3호
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• pp.56-65
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• 2001

In interpreting stream water quality data, scientific or statistical mehtods should be employed. Classical parametric statistical methods may not be adopted in analyzing water quality data, due to the violation of normality. In this study, nonparametric statistical methods, such as Kruskal-Wallis test and Mann-Whitney test, were used in comparing water quality data from several monitoring stations. Water quality data used are those collected Bokha watershed, located in Ichon-city, Kyonggi province. Based on the test results, domestic sewage is the major pollution source. A couple of sub-watersheds with a large number of livestock do not show significant differences in water quality parameters. It should be noted that comparison of mean values of water quality parameters is difficult to relate water quality with watershed characteristics. The results also indicate that livestock farming does not significantly affect the water quality.

• 천문학회보
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• 제39권1호
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• pp.34-34
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• 2014

We investigate the constraints on the matter density ${\Omega}m$ and the cosmological constant ${\Omega}{\Lambda}$ using the gravitational lensed QSO (Quasi Stellar Object) systems from the Sloan Digital Sky Survey (SDSS) by analyzing the distribution of image separation. The main sample consists of 16 QSO lens systems with measured source and lens redshifts. We use a lensing probability that is simply defined by the gaussian distribution. We perform the curvature test and the constraints on the cosmological parameters as the statistical tests. The statistical tests have considered well-defined selection effects and adopt parameter of velocity dispersion function. We also applied the same analysis to Monte-Carlo generated mock gravitational lens samples to assess the accuracy and limit of our approach. As the results of these statistical tests, we find that only the excessively positively curved universe (${\Omega}m+{\Omega}{\Lambda}$ > 1) are rejected at 95% confidence level. However, if the informations of the galaxy as play a lens are measured accurately, we confirm that the gravitational lensing statistics would be the most powerful tool.