• Progress in Medical Physics
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• v.14 no.4
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• pp.240-248
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• 2003

The Monte Carlo calculation is the most accurate means of predicting radiation dose, but its accuracy is accompanied by an increase in the amount of time required to produce a statistically meaningful dose distribution. In this study, the effects on calculation time by introducing variance reduction techniques and increasing computing power, respectively, in the Monte Carlo dose calculation for a 6 MV photon beam from the Varian 600 C/D were estimated when maintaining accuracy of the Monte Carlo calculation results. The EGSnrc­based BEAMnrc code was used to simulate the beam and the EGSnrc­based DOSXYZnrc code to calculate dose distributions. Variance reduction techniques in the codes were used to describe reduced­physics, and a computer cluster consisting of ten PCs was built to execute parallel computing. As a result, time was more reduced by the use of variance reduction techniques than that by the increase of computing power. Because the use of the Monte Carlo dose calculation in clinical practice is yet limited by reducing the computational time only through improvements in computing power, introduction of reduced­physics into the Monte Carlo calculation is inevitable at this point. Therefore, a more active investigation of existing or new reduced­physics approaches is required.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.151-161
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• 1997

An easy Monte Carlo Gibbs sampling approach is suggested for Bayesian analysis of cumulative logit models for ordinal polytomous data. Because in the cumulative logit model the posterior conditional distributions of parameters are not given in convenient forms for random sample generation, appropriate latent variables are introduced into the model so that in the new model all the conditional distributions are given in very convenient forms for implementation of the Gibbs sampler.

• Electrical & Electronic Materials
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• v.10 no.8
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• pp.836-842
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• 1997

• Polymer Science and Technology
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• v.9 no.4
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• pp.256-273
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• 1998

• Aerospace Engineering and Technology
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• v.4 no.1
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• pp.95-102
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• 2005

This paper introduces the LAE(Liquid Apogee Engine) and station acquisition fuel budget estimation method for the COMS(Communication, Ocean and Meteorological Satellite) of Korea which is planned to be launched in 2008. And the estimation results are also presented. A statistical approach, more specifically, the Monte-Carlo method was employed to have the estimation include the effect of the launch vehicle GTO injection accuracies. A case study was conducted for several potential launch vehicles to compare the fuel requirements.

• Progress in Medical Physics
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• v.8 no.1
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• pp.47-52
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• 1997

Simulations were performed using a Monte Carlo technique in order to show physical phenomena occurring when a heavy charged particle such as proton or alpha particle traverses the medium. It was confirmed that the sharp Bragg peak occurred deeper in the water with the increasing proton energy. It is found that the use of such a sharp Bragg peak due to heavy charged particles would be far superior to the case of the photon or electron, since the absorbed dose in the target tissues would be better localized, thereby minimizing the damage to the surrounding tissues.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.6
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• pp.253-259
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• 2003

In this paper, the scattered field from a Pierson-Moskowitz sea surface assumed as the PEC by the Finite-Difference Time-Domain(FDTD) method was computed. A one-dimensional surface used to analysis scattering was generated by using the Pierson-Moskowitz model. Back scattering coefficients are calculated with different values of the wind speed(U) which determine configuration of the Pierson-Moskowitz sea surface. The number of surface realization for the computed field, the point number, and the width of surface realization are set to be 50, 8192, and 128k, respectively. In order to verify the computed values these results are compared with those of small perturbation methods, which show good agreement between them.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.12
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• pp.566-574
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• 2002

In this paper, the scattered field from a perfectly conducting fractal surface by the Monte-Carlo moment method was computed. An one-dimensional fractal surface was generated by using the fractional Brownian motion model. Back scattering coefficients are calculated with different values of the spectral parameter(S$\_$0/), and fractal dimension(D) which determine characteristics of the fractal surface. The number of surface realization for the computed field, the point number, and the width of surface realization are set to be 80, 2048, and 64L, respectively. In order to verify the computed results these results are compared with those of small perturbation methods, which show good agreement between them.

• Journal of radiological science and technology
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• v.41 no.3
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• pp.215-221
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• 2018

Cone beam Computed Tomography(CBCT) is an increasing trend in clinical applications due to its ability to increase the accuracy of radiation therapy. However, this leaded to an increase in exposure dose. In this study, the simulation using Monte Carlo method is performed and the absorbed dose of CBCT is analyzed and standardized data is presented. First, after simulating the CBCT, the photon spectrum was analyzed to secure the reliability and the absorbed dose of the tissue in the human body was evaluated using the MIRD phantom. Compared with SRS-78, the photon spectrum of CBCT showed similar tendency, and the average absorbed dose of MIRD phantom was 8.12 ~ 25.88 mGy depending on the body site. This is about 1% of prescription dose, but dose management will be needed to minimize patient side effects and normal tissue damage.

• Journal of Korean Society of Steel Construction
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• v.13 no.5
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• pp.467-476
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• 2001

The construction of highway bridges is almost complete in many countries including the United States. The government and highway agencies change the focus from constructing to maintaining To maintain the bridges effectively there is an urgent need to assess actual bridge loading carrying capacity and to predict their remaining life. The system reliability techniques have to be used for this purpose. Based on lifetime distribution (function) techniques this study illustrates how typical highway bridges can be modeled to predict their remaining life. The parameters of lifetime distribution are generated by Monte. The results can be used for optimization of planning interventions on existing bridges.