• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.2
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• pp.436-444
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• 1991

A computational method has been developed to analyze the bone-remodeling induced by external fixator. The method was based on the Finite Element Method (FEM) in combination with numerical formulation of adaptive bone-remodeling theories. As a feed-back control variable, compressive strain and effective stress were used to determine the surface remodeling and internal (density) remodeling respectively. Surface remodeling and internal remodeling were combined at each time step to predict the rel situation. A noticeable shape and density change were detected at the region between two pins and density change was decreased with time increment. At final time step, the shape and density distribution were converged closely to its original intact bone model. Similar change was detected in stress distribution. The altered stress distribution due to the pin and external fixator converged to the intact stress distribution with time.

• Applied Microscopy
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• v.44 no.2
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• pp.74-78
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• 2014

Dislocation density and distribution in epitaxial GaAs layer on Si are evaluated quantitatively and effectively using image processing of transmission electron microscopy image. In order to evaluate dislocation density and distribution, three methods are introduced based on line-intercept, line-length measurement and our coding with line-scanning method. Our coding method based on line-scanning is used to detect the dislocations line-by-line effectively by sweeping a thin line with the width of one pixel. The proposed method has advances in the evaluation of dislocation density and distribution. Dislocations can be detected automatically and continuously by a sweeping line in the code. Variation of dislocation density in epitaxial GaAs films can be precisely analyzed along the growth direction on the film.

• The Mathematical Education
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• v.39 no.2
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• pp.167-177
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• 2000

In this thesis we concerned with the degree of similarity in pairs of scores having a common mean and variance could express similarity in terms of the absolute difference between the standardized scores. We particulary discussed the distribution of absolute differences between pairs of T scores among many standardized scores and demonstrated the procedures for calculating the lower limit of Med(│d│) values i. e. the maximum possible similarity with medians and correlation coefficients of the equivalent form tests by using the folded normal distribution, although other researchers expressed the degree of similarity using only the standard normal distribution. We also described many cases how to use those techniques and to apply effectively them in real evaluation fields.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.134-140
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• 2003

The film sensor is used for measuring pressure distribution at planar area, especially at a small space or gap. The present paper deals with the development of film type sensors and system for pressure distribution measuring. The developed system is consist of (1)film sensor with 40/sup */40 array, (2)PCI interface card with maximum sampling rate of 100㎐, and (3)software for data processing and real-time display. The contact pressure test of wiper blade and front glass of vehicle was performed with wiper blade by 40cm. Generally spring force of wiper arm is designed at 0.7∼1kN. Test results of total force was 9.4N and 7.1N in each driver and passenger toward. The paper suggested possibility for base definition in wiper design. A windshield wiper blade experiment revealed that the system successfully measured the contact force distribution during static state, showing the usefulness of the developed system.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.729-742
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• 2005

In this paper, we discuss the propriety of the various noninformative priors for the Pareto distribution. The reference prior, Jeffreys prior and ad hoc noninformative prior which is used in several literatures will be introduced and showed that which prior gives the proper posterior distribution. The reference prior and Jeffreys prior give a proper posterior distribution, but ad hoc noninformative prior which is proportional to reciprocal of the parameters does not give a proper posterior. To compute survival function, we use the well-known approximation method proposed by Lindley (1980) and Tireney and Kadane (1986). And two methods are compared by simulation. A real data example is given to illustrate our methodology.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.423-432
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• 2016

In this paper, we stochastically analyze the continuous time surplus process in a risk model which involves a continuous type investment. It is assumed that the investment of the surplus to other business is continuously made at a constant rate, while the surplus process stays over a given sufficient level. We obtain the stationary distribution of the surplus level and/or its moment generating function by forming martingales from the surplus process and applying the optional sampling theorem to the martingales and/or by establishing and solving an integro-differential equation for the distribution function of the surplus level.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.507-518
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• 2017

Volatility plays a crucial role in theory and applications of asset pricing, optimal portfolio allocation, and risk management. This paper proposes a combined model of autoregressive moving average (ARFIMA), generalized autoregressive conditional heteroscedasticity (GRACH), and skewed-t error distribution to accommodate important features of volatility data; long memory, heteroscedasticity, and asymmetric error distribution. A fully Bayesian approach is proposed to estimate the parameters of the model simultaneously, which yields parameter estimates satisfying necessary constraints in the model. The approach can be easily implemented using a free and user-friendly software JAGS to generate Markov chain Monte Carlo samples from the joint posterior distribution of the parameters. The method is illustrated by using a daily volatility index from Chicago Board Options Exchange (CBOE). JAGS codes for model specification is provided in the Appendix.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.97-108
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• 2020

This paper compares several methods for estimating parameters of normal inverse Gaussian distribution. Ordinary maximum likelihood estimation and the method of moment estimation often do not work properly due to restrictions on parameters. We examine the performance of adjusted estimation methods along with the ordinary maximum likelihood estimation and the method of moment estimation by simulation and real data application. We also see the effect of the initial value in estimation methods. The simulation results show that the ordinary maximum likelihood estimator is significantly affected by the initial value; in addition, the adjusted estimators have smaller root mean square error than ordinary estimators as well as less impact on the initial value. With real datasets, we obtain similar results to what we see in simulation studies. Based on the results of simulation and real data application, we suggest using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values to estimate the parameters of normal inverse Gaussian distribution.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.47-64
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• 2020

In this paper, we derive some estimators of the scale parameter of the exponentiated half-logistic distribution based on the multiply Type-I hybrid censoring scheme. We assume that the shape parameter λ is known. We obtain the maximum likelihood estimator of the scale parameter σ. The scale parameter is estimated by approximating the given likelihood function using two different Taylor series expansions since the likelihood equation is not explicitly solved. We also obtain Bayes estimators using prior distribution. To obtain the Bayes estimators, we use the squared error loss function and general entropy loss function (shape parameter q = -0.5, 1.0). We also derive interval estimation such as the asymptotic confidence interval, the credible interval, and the highest posterior density interval. Finally, we compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation. The average length of 95% intervals and the corresponding coverage probability are also obtained.

• Water for future
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• v.26 no.4
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• pp.73-83
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• 1993

This study focuses on the separation effect analysis of rainfall data for 2-parameter log-normal, 3-parameter log-normal, type-extreme value, 2-parameter gamma, 3-parameter gamma, log-Pearson type-III, and general extreme value distribution functions. Difference in the relationship between the mean and standard deviation of skewness for historical data and relations derived from 7 distribution functions are analyzed suing the Monte Carlo experiment. The results show that rainfall data has the separation effect for 6 distribution functions except 3-parameter gamma distribution function.