• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1171-1177
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• 2007

We consider estimation of the right-tail probability in a log-Laplace random variable, As we derive the density of ratio of two independent log-Laplace random variables, the k-th moment of the ratio is represented by a special mathematical function. and hence variance of the ratio can be represented by a psi-function.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.983-986
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• 2002

Support Vector Machine (SVM) is one of the methods of pattern recognition that separate input data using hyperplane. This method has high capability of pattern recognition by using the technique, which says kernel trick, and the Radial basis function (RBF) kernel is usually used as a kernel function in kernel trick. In this paper we propose using the q-normal distribution to the kernel function, instead of conventional RBF, and compare two types of the kernel function.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.411-421
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• 2007

The recent work by the authors (see, Withers, 1999; Withers and McGavin, 2006; Withers and Nadarajah, 2006) provided new expressions for repeated upper tail integrals of the univariate normal density and so also for the general Hermite function. Here we derive new expressions for repeated lower tail integrals of the same. The calculations involve the use of Moran's L-function and the Airy function. In particular, the Hermite functions are expressed in terms of Moran's L-function and vice versa.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.669-678
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• 2007

An algorithm to detect the number of discontinuity points of the variance function in regression model is proposed. The proposed algorithm is based on the left and right one-sided kernel estimators of the second moment function and test statistics of the existence of a discontinuity point coming from the asymptotic distribution of the estimated jump size. The finite sample performance is illustrated by simulated example.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.4
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• pp.251-258
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• 2020

Sewer deterioration models are needed to forecast the remaining life expectancy of sewer networks by assessing their conditions. In this study, the serious defect (or condition state 3) occurrence probability, at which sewer rehabilitation program should be implemented, was evaluated using four probability distribution functions such as normal, lognormal, exponential, and Weibull distribution. A sample of 252 km of CCTV-inspected sewer pipe data in city Z was collected in the first place. Then the effective data (284 sewer sections of 8.15 km) with reliable information were extracted and classified into 3 groups considering the sub-catchment area, sewer material, and sewer pipe size. Anderson-Darling test was conducted to select the most fitted probability distribution of sewer defect occurrence as Weibull distribution. The shape parameters (β) and scale parameters (η) of Weibull distribution were estimated from the data set of 3 classified groups, including standard errors, 95% confidence intervals, and log-likelihood values. The plot of probability density function and cumulative distribution function were obtained using the estimated parameter values, which could be used to indicate the quantitative level of risk on occurrence of CS3. It was estimated that sewer data group 1, group 2, and group 3 has CS3 occurrence probability exceeding 50% at 13th-year, 11th-year, and 16th-year after the installation, respectively. For every data groups, the time exceeding the CS3 occurrence probability of 90% was also predicted to be 27th- to 30th-year after the installation.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.159-168
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• 2008

A special field experiment has been carried out from March 2001 to June 2001 at the Changhowon in Kyunggi to investigate a better methodology for the estimation of dry deposition of pollutions applicable in Korea. In this study, dry deposition plate was used to measure of total and water soluble acidic mass fluxes, and CPRI(Coarse Particle Rotary Impactor), CI(Cascade Impactor) were also used to measure ambient concentrations in various particle size ranges. Sehmel-Hodgson model was used to estimate dry depostion velocity and Weibull probability distribution function was applied to get generalized particle size distribution for the size fractioned concentration data sampled by CPRI and CI. Atmospheric dry deposition fluxes of mass and ionic matters estimated by the various techniques(one-step, multi-step, equi-concentration, subdivision for only the coarse particle range, applying Weibull distribution function, etc.) were compared to flux data sampled by DDP. It was found out that the deposition fluxes estimation methodology calculated by the each particle size range devided by particle size distribution characteristics and the rapidly changed points of deposition velocity using Weibull probability distribution function was the most applicable.

• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.200-204
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• 2012

This study has presented the analysis of breakdown voltage for a double-gate metal-oxide semiconductor field-effect transistor (MOSFET) based on the doping distribution of the Gaussian function. The double-gate MOSFET is a next generation transistor that shrinks the short channel effects of the nano-scaled CMOSFET. The degradation of breakdown voltage is a highly important short channel effect with threshold voltage roll-off and an increase in subthreshold swings. The analytical potential distribution derived from Poisson's equation and the Fulop's avalanche breakdown condition have been used to calculate the breakdown voltage of a double-gate MOSFET for the shape of the Gaussian doping distribution. This analytical potential model is in good agreement with the numerical model. Using this model, the breakdown voltage has been analyzed for channel length and doping concentration with parameters such as projected range and standard projected deviation of Gaussian function. As a result, since the breakdown voltage is greatly changed for the shape of the Gaussian function, the channel doping distribution of a double-gate MOSFET has to be carefully designed.

• Composites Research
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• v.29 no.5
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• pp.299-305
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• 2016

This paper presents a method to detect the fiber property variation of laminated CFRP plates using the bivariate Gaussian distribution function. Five unknown parameters are considered to determine the fiber damage distribution, which is a modified form of the bivariate Gaussian distribution function. To solve the inverse problem using the combined computational method, this study uses several natural frequencies and mode shapes in a structure as the measured data. The numerical examples show that the proposed technique is a feasible and practical method which can prove the location of a damaged region as well as inspect the distribution of deteriorated stiffness of CFRP plates for different fiber angles and layup sequences.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.11
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• pp.75-80
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• 2012

In this paper, the operational characteristics due to the introduction of the superconducting fault current limiter(SFCL) with a peak current limiting function were analyzed in the power distribution system. The parallel structure of the superconducting element can operate the peak current limiting function depending on the transient amplitude of fault current. We studied the operating characteristics of the introduction of the SFCL with a peak current limiting function in the power distribution system. Furthermore, we were analyzed between the SFCL with a peak current limiting function and the protection devices in the power distribution system, through the short circuit experiments.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1573-1582
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• 2015

In lifetime data analysis, it is generally known that the lifetimes of test items may not be recorded exactly. There are also situations wherein the withdrawal of items prior to failure is prearranged in order to decrease the time or cost associated with experience. Moreover, it is generally known that more than one cause or risk factor may be present at the same time. Therefore, analysis of censored competing risks data are needed. In this article, we derive the Bayes estimators for the entropy function under the exponential distribution with an unknown scale parameter based on multiply Type II censored competing risks data. The Bayes estimators of entropy function for the exponential distribution with multiply Type II censored competing risks data under the squared error loss function (SELF), precautionary loss function (PLF) and DeGroot loss function (DLF) are provided. Lindley's approximate method is used to compute these estimators.We compare the proposed Bayes estimators in the sense of the mean squared error (MSE) for various multiply Type II censored competing risks data. Finally, a real data set has been analyzed for illustrative purposes.