• Journal of Radiation Protection and Research
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• v.41 no.1
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• pp.41-47
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• 2016

Background: For the accurate dose assessment in radiation therapy, energy spectrum of the photon beam generated from the linac head is essential. The aim of this study is to develop the technique to accurately unfolding the energy spectrum with the transmission analysis method. Materials and Methods: Clinical linear accelerator and Monet Carlo method was employed to evaluate the transmission signals according to the thickness of the observer material, and then the response function of the ion chamber response was determined with the mono energy beam. Finally the energy spectrum was unfolded with HEPROW program. Elekta Synergy Flatform and Geant4 tool kits was used in this study. Results and Discussion: In the comparison between calculated and measured transmission signals using aluminum alloy as an attenuator, root mean squared error was 0.43%. In the comparison between unfolded spectrum using HEPROW program and calculated spectrum using Geant4, the difference of peak and mean energy were 0.066 and 0.03 MeV, respectively. However, for the accurate prediction of the energy spectrum, additional experiment with various type of material and improvement of the unfolding program is required. Conclusion: In this research, it is demonstrated that unfolding spectra technique could be used in megavoltage photon beam with aluminum alloy and HEPROW program.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.9
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• pp.4049-4054
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• 2014

Background: Race and ethnicity are significant factors in predicting survival time of breast cancer patients. In this study, we applied advanced statistical methods to predict the survival of White non-Hispanic female breast cancer patients, who were diagnosed between the years 1973 and 2009 in the United States (U.S.). Materials and Methods: Demographic data from the Surveillance Epidemiology and End Results (SEER) database were used for the purpose of this study. Nine states were randomly selected from 12 U.S. cancer registries. A stratified random sampling method was used to select 2,000 female breast cancer patients from these nine states. We compared four types of advanced statistical probability models to identify the best-fit model for the White non-Hispanic female breast cancer survival data. Three model building criterion were used to measure and compare goodness of fit of the models. These include Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC). In addition, we used a novel Bayesian method and the Markov Chain Monte Carlo technique to determine the posterior density function of the parameters. After evaluating the model parameters, we selected the model having the lowest DIC value. Using this Bayesian method, we derived the predictive survival density for future survival time and its related inferences. Results: The analytical sample of White non-Hispanic women included 2,000 breast cancer cases from the SEER database (1973-2009). The majority of cases were married (55.2%), the mean age of diagnosis was 63.61 years (SD = 14.24) and the mean survival time was 84 months (SD = 35.01). After comparing the four statistical models, results suggested that the exponentiated Weibull model (DIC= 19818.220) was a better fit for White non-Hispanic females' breast cancer survival data. This model predicted the survival times (in months) for White non-Hispanic women after implementation of precise estimates of the model parameters. Conclusions: By using modern model building criteria, we determined that the data best fit the exponentiated Weibull model. We incorporated precise estimates of the parameter into the predictive model and evaluated the survival inference for the White non-Hispanic female population. This method of analysis will assist researchers in making scientific and clinical conclusions when assessing survival time of breast cancer patients.

• Journal of Astronomy and Space Sciences
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• v.17 no.1
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• pp.77-86
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• 2000

There have been a few attempts to measure diffuse line emission between 900 $\AA$ and 1200 $\AA$, and only in a limited number of sight lines has it been detected. The main contributions to the equilibrium radiative cooling curve between $10^{4.5}K\;to\;10^6K$ are from the doublet of Ovi ${lambda}{lambda}1032;and;{lambda}{lambda}1038$ in the FUV spectral region. There are several bright airglow lines which could interfere with attempts to observe the OVI lines. The nearest lines HI 1025 $\AA$, OI 1027 $\AA$ have a combined intensity of about $10^{5.5}$ photons/s/$cm^2$/sr. In the present study, the detectability simulation of OVI doublet is performed using a Monte-Carlo technique and chi-square statistics. The analysis results are compared with the previous observations and with the predictions of several interstellar medium models, and are used to limit manufacturing and alignment errors of FIMS optical system.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.355-362
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• 2012

Remaining useful life(RUL) prediction of a system is important in the prognostics field since it is directly linked with safety and maintenance scheduling. In the physics-based prognostics, accurately estimated model parameters can predict the remaining useful life exactly. It, however, is not a simple task to estimate the model parameters because most real system have multivariate model parameters, also they are correlated each other. This paper presents representative methods to estimate model parameters in the physics-based prognostics and discusses the difference between three methods; the particle filter method(PF), the overall Bayesian method(OBM), and the sequential Bayesian method(SBM). The three methods are based on the same theoretical background, the Bayesian estimation technique, but the methods are distinguished from each other in the sampling methods or uncertainty analysis process. Therefore, a simple physical model as an easy task and the Paris model for crack growth problem are used to discuss the difference between the three methods, and the performance of each method evaluated by using established prognostics metrics is compared.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.217-224
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• 2024

This paper proposes an efficient dimension reduction method (DRM) that considers the nonlinearity of the performance functions in reliability-based design optimization (RBDO). The dimension reduction method evaluates the reliability more accurately than the first-order reliability method (FORM) using integration quadrature points and weights. However, its efficiency is hindered as the number of quadrature points increases owing to the need for an additional evaluation of the performance function. In this study, we assessed the nonlinearity of the performance function in RBDO and proposed criteria for determining the number of quadrature points based on the degree of nonlinearity. This approach suggests adjusting the number of quadrature points during each iteration of the RBDO process while maintaining the accuracy of theDRM while improving the computational efficiency. The nonlinearity of the performance function was evaluated using the angle between the vectors used in the maximum probable target point (MPTP) search. Numerical tests were conducted to determine the appropriate number of quadrature points according to the degree of nonlinearity. Through a 2D numerical example, it is confirmed that the proposed method improves the efficiency while maintaining the accuracy of the dimension reduction method or Monte Carlo Simulation (MCS).

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.80-81
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• 2012

Recently, one of the critical issues in the etching processes of the nanoscale devices is to achieve ultra-high aspect ratio contact (UHARC) profile without anomalous behaviors such as sidewall bowing, and twisting profile. To achieve this goal, the fluorocarbon plasmas with major advantage of the sidewall passivation have been used commonly with numerous additives to obtain the ideal etch profiles. However, they still suffer from formidable challenges such as tight limits of sidewall bowing and controlling the randomly distorted features in nanoscale etching profile. Furthermore, the absence of the available plasma simulation tools has made it difficult to develop revolutionary technologies to overcome these process limitations, including novel plasma chemistries, and plasma sources. As an effort to address these issues, we performed a fluorocarbon surface kinetic modeling based on the experimental plasma diagnostic data for silicon dioxide etching process under inductively coupled C4F6/Ar/O2 plasmas. For this work, the SiO2 etch rates were investigated with bulk plasma diagnostics tools such as Langmuir probe, cutoff probe and Quadruple Mass Spectrometer (QMS). The surface chemistries of the etched samples were measured by X-ray Photoelectron Spectrometer. To measure plasma parameters, the self-cleaned RF Langmuir probe was used for polymer deposition environment on the probe tip and double-checked by the cutoff probe which was known to be a precise plasma diagnostic tool for the electron density measurement. In addition, neutral and ion fluxes from bulk plasma were monitored with appearance methods using QMS signal. Based on these experimental data, we proposed a phenomenological, and realistic two-layer surface reaction model of SiO2 etch process under the overlying polymer passivation layer, considering material balance of deposition and etching through steady-state fluorocarbon layer. The predicted surface reaction modeling results showed good agreement with the experimental data. With the above studies of plasma surface reaction, we have developed a 3D topography simulator using the multi-layer level set algorithm and new memory saving technique, which is suitable in 3D UHARC etch simulation. Ballistic transports of neutral and ion species inside feature profile was considered by deterministic and Monte Carlo methods, respectively. In case of ultra-high aspect ratio contact hole etching, it is already well-known that the huge computational burden is required for realistic consideration of these ballistic transports. To address this issue, the related computational codes were efficiently parallelized for GPU (Graphic Processing Unit) computing, so that the total computation time could be improved more than few hundred times compared to the serial version. Finally, the 3D topography simulator was integrated with ballistic transport module and etch reaction model. Realistic etch-profile simulations with consideration of the sidewall polymer passivation layer were demonstrated.