• Journal of the Korean Institute of Gas
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• v.5 no.4 s.16
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• pp.70-78
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• 2001

In order to find out which equipment failures were mostly contributed to the rupture of a continuous stirred tank reactor, the sensitivity analysis was carried out. The uncertainty of likelihood of the rupture of reactor was studied by the uncertainty analysis. And the cost effectiveness analysis resulted in the recommendation of the exchange with a better reliable unit if you want to maintain the process efficiently from the view point of cost. The uncertainty analysis showed that the likelihood of catastrophic rupture of the reactor was distributed from $8.09{\times}10^{-04}$ to $5.50{\times}10^{-02}/year$. As a result of cost-effectiveness analysis, it was proposed to exchange the voting logic unit for a better safer system.

• Journal of the Korean Geotechnical Society
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• v.33 no.7
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• pp.29-41
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• 2017

There are uncertainties about the seismic load caused by seismic waves, which cannot be predicted due to the characteristics of the earthquake occurrence. Therefore, it is necessary to consider these uncertainties by probabilistic analysis. In this paper, procedures to develop a fragility curve that is a representative method to evaluate the safety of a structure by stochastic analysis were proposed for cut slopes. Fragility curve that considers uncertainties of soil shear strength parameters was prepared by Monte Carlo Simulation using pseudo static analysis. The fragility curve considering the uncertainty of the input ground motion was developed by performing time-history seismic analysis using selected 30 real ground input motions and the Newmark type displacement evaluation analysis. Fragility curves are represented as the cumulative probability distribution function with lognormal distribution by using the maximum likelihood estimation method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.161-174
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• 1996

Addressed in this paper is performance analysis of the maximum-likelihood code acquisition technique for slotted-mode preamble search in the CDMA reverse link. The probabilities of detection, miss, and false alarm are derived analytically for a multiple $H_{1}$ cell case in a frequency-selective Rayleigh fading channel, based on the statics of the CDMA noncoherent demodulator output. the probability density function of the decision variable consisting of successive demodulator outputs is also derived by considering the fading characteristics of the received signal for both single and dual antenna cases. The performance of the code acquisition technique is evaluated numerically with an emphasis on investigating the effects of post-detection integration, fading rate, and antenna diversity on the detection performance.

• The Korean Journal of Applied Statistics
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• v.9 no.2
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• pp.119-134
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• 1996

Accelerated life testing (ALT) of a system is commonly used to reduce time and cost. ALT is achieved by subjecting the test systems to more severe conditions than the normal ones to obtain estimates of life distribution under normal condition. The major interest of this research is to use a model of incorporating the common environmental effect on the components serially linked into a system-so called frailty model for the system life time distribution under each stress and to discuss the related data analysis and comparison of the model with the generally used one. The profile likelihood is used to get an initial values required to compute maximum likelihood estimates and simulation is carried for comparison.

• Journal of the Korean Society for Nondestructive Testing
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• v.13 no.2
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• pp.11-19
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• 1993

It is very essential to get the accurate classification of defects in primary pressure vessel weld for the safety of nuclear power plant. The signal analysis using the digital signal processing and pattern recognition is performed to classify UT defects extracting feature vector from ultrasonic signals. The minimum distance classifier and the maximum likelihood classifier based on statistics were applied in this experiment to discriminate ultrasonics data obtained form both the training specimens (slit, hole) and the testing specimens(crack, slag). The classification rate was measured using pattern classifier. Results of this study show the promise in solving the many flaw classification problems that exist today.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.587-598
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• 2006

The number of variables exceeds the number of samples in microarray data. We propose a nonparametric local linear logistic classification procedure using orthogonal components for classifying high-dimensional microarray data. The proposed method is based on the local likelihood and can be applied to multi-class classification. We applied the local linear logistic classification method using PCA, PLS, and factor analysis components as new features to Leukemia data and colon data, and compare the performance of the proposed method with the conventional statistical classification procedures. The proposed method outperforms the conventional ones for each component, and PLS has shown best performance when it is embedded in the proposed method among the three orthogonal components.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.33-40
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• 2005

The aim of remotely sensed data classification is to produce the best accuracy map of the earth surface assigning each pixel to its appropriate category of the real-world. The classification of satellite multi-spectral image data has become tool for generating ground cover map. Many classification methods exist. In this study, MLC(Maximum Likelihood Classification), ANN(Artificial neural network), SVM(Support Vector Machine), Naive Bayes classifier algorithms are compared using IKONOS image of the part of Dalsung Gun, Daegu area. Two preprocessing methods are performed-PCA(Principal component analysis), ICA(Independent Component Analysis). Boosting algorithms also performed. By the combination of appropriate feature selection pre-processing and classifier, the best results were obtained.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.986-994
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• 2005

This Paper proposes the likelihood-based nonlinear dimension reduction method of the speech feature parameters in order to construct the voice activity detecter adaptable in noisy environment. The proposed method uses the nonlinear values of the Gaussian probability density function with the new parameters for the speec/nonspeech class. We adapted Likelihood Ratio Test to find speech part and compared its performance with that of Linear Discriminant Analysis technique. In experiments we found that the proposed method has the similar results to that of Gaussian Mixture Models.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.835-847
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• 2016

To analyze lattice or areal data, a conditionally autoregressive (CAR) model has been widely used in the eld of spatial analysis. The spatial neighborhoods within CAR model are generally formed using only inter-distance or boundaries between regions. Kyung and Ghosh (2010) proposed a new class of models to accommodate spatial variations that may depend on directions. The proposed model, a directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Properties of maximum likelihood estimators of a Gaussian DCAR are discussed. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.4
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• pp.609-628
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• 1995

This paper presents a reliability model and a data-analytic procedure for a repairable unit subject to failures due to multiple non-identifiable causes. We regard a failure cause as a state and assume the life distribution for each cause to be exponential. Then we represent the dependency among the causes by a Markov switching model(MSM) and estimate the transition probabilities and failure rates by maximum likelihood(ML) method. The failure data are incomplete due to masked causes of failures. We propose a specific version of EM(expectation and maximization) algorithm for finding maximum likelihood estimator(MLE) under this situation. We also develop statistical procedures for determining the number of significant states and for testing independency between state transitions. Our model requires only the successive failure times of a unit to perform the statistical analysis. It works well even when the causes of failures are fully masked, which overcomes the major deficiency of competing risk models. It does not require the assumption of stationarity or independency which is essential in mixture models. The stationary probabilities of states can be easily calculated from the transition probabilities estimated in our model, so it covers mixture models in general. The results of simulations show the consistency of estimation and accuracy gradually increasing according to the difference of failure rates and the frequency of transitions among the states.