• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.443-450
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• 2018

The Geant 4 simulated the linear accelerator (VARIAN CLINAC) based on the previously implemented BEAMnrC data, using the head structure of the linear accelerator. In the 10 MV photon flux, Geant4 was compared with the measured value of the percentage of the deep dose and the lateral dose of the water phantom. In order to apply the dose calculation to the body part, the actual patient's lung area was scanned at 5 mm intervals. Geant4 dose distributions were obtained by irradiating 10 MV photons at the irradiation field ($5{\times}5cm^2$) and SAD 100 cm of the water phantom. This result is difficult to measure the dose absorbed in the actual lung of the patient so the doses by the treatment planning system were compared. The deep dose curve measured by water phantom and the deep dose curve calculated by Geant4 were well within ${\pm}3%$ of most depths except the build-up area. However, at the 5 cm and 20 cm sites, 2.95% and 2.87% were somewhat higher in the calculation of the dose using Geant4. These two points were confirmed by the geometry file of Genat4, and it was found that the dose was increased because thoracic spine and sternum were located. In cone beam CT, the dose distribution error of the lungs was similar within 3%. Therefore, if the contour map of the dose can be directly expressed in the DICOM file when calculating the dose using Geant4, the clinical application of Geant4 will be used variously.

• Journal of Radiation Protection and Research
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• v.32 no.1
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• pp.21-26
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• 2007

This study is performed to evaluate the dose rate and to analyze the dose distribution of the gamma irradiation facility (IR-221) by using a Monte Calro simulation, which is helpful of upgrading the radiation processing qualification. Monte Cairo simulation is performed by MCNP4B code. Dose rates were measured at total 369 points with alanine dosimeters to compare the calculation results and the measurements data. The results have shown that the MCNP4B code is very useful to determine the dose distribution of the IR-221 gamma irradiation facility, as the calculation dose rate is within about ${\pm}5%$ of the measurement data. Dosimetry about the gamma irradiation facility usually needs enormous manpower and time. However Monte Cairo calculation method can reduce the tedious dosimetry jobs and improve the irradiation processing qualification, which will probably contribute to obtain the reliability of the irradiation products.

• Journal of Biosystems Engineering
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• v.39 no.3
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• pp.205-214
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• 2014

Purpose: Phytosanitary irradiation treatment can effectively control regulated pests while maintaining produce quality. The objective of this study was to establish the best irradiation treatment for mangosteen, a popular tropical fruit, using a Monte Carlo simulation. Methods: Magnetic resonance image (MRI) data were used to generate a 3-D geometry to simulate dose distributions in a mangosteen using a radiation transport code (MCNP5). Microsoft Excel with visual basic application (VBA) was used to divide the image data into seed, flesh, and rind. Radiation energies used for the simulation were 10 MeV (high-energy) and 1.35 MeV (low-energy) for the electron beam, 5 MeV for X-rays, and 1.25 MeV for gamma rays from Co-60. Results: At 5 MeV X-rays and 1.25 MeV gamma rays, all areas (seeds, flesh, and rind) were irradiated ranging from 0.3 ~ 0.7 kGy. The average doses decreased as the number of fruit increased. For a 10 MeV electron beam, the dose distribution was biased: the dose for the rind where the electrons entered was $0.45{\pm}0.03$ kGy and the other side was $0.24 {\pm}0.10$ kGy. Use of an electron kinetic energy absorber improved the dose distribution in mangosteens. For the 1.35 MeV electron beam, the dose was shown only in the rind on the irradiated side; no significant dose was found in the flesh or seeds. One rotation of the fruit while in front of the beam improved the dose distribution around the entire rind. Conclusion: These results are invaluable for determining the ideal irradiation conditions for phytosanitary irradiation treatment of tropical fruit.

• Transactions on Electrical and Electronic Materials
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• v.6 no.1
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• pp.1-5
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• 2005

Continued scaling of MOS devices requires the formation of the ultra shallow and very heavily doped junction. The simulation and experiment results show that the degradation of pMOS performance in logic and SRAM pMOS devices due to the excessive diffusion of the tail and a large amount of dose loss in the extension region. This problem comes from the high-temperature long-time deposition process for forming the spacer and the presence of fluorine which diffuses quickly to the $Si/SiO_{2}$ interface with boron pairing. We have studied the method to improve the pMOS performance that includes the low-energy boron implantation, spike annealing and device structure design using TCAD simulation.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.825-836
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• 2019

One of the most challenging safety precautions for workers in dynamic, radioactive environments is avoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm, DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupational workers in nuclear facilities to avoid unnecessary radiation exposure. The method combines the principle of random tree star ($RRT^*$) and $D^*$ Lite, and uses the expansion strength of grid search strategy from $D^*$ Lite to quickly find a high-quality initial path to accelerate convergence rate in $RRT^*$. The algorithm inherits probabilistic completeness and asymptotic optimality from $RRT^*$ to refine the existing paths continually by sampling the search-graph obtained from the grid search process. It can not only be applied to continuous cost spaces, but also make full use of the last planning information to avoid global re-planning, so as to improve the efficiency of path planning in frequently changing environments. The effectiveness and superiority of the proposed method was verified by simulating radiation field under varying obstacles and radioactive environments, and the results were compared with $RRT^*$ algorithm output.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.693-701
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• 2002

When the lowest dose level compared with zero-dose control has significant difference in effect, it is referred as minimum effective dose (MED). In this paper, we discuss several nonparametric methods for finding MED using updated rank at each sequential test step in small sample size and suggest new nonparametric procedures based on placement. Monte Carlo Simulation is adapted to compare power and Familywise Error Rate(FWE) of the new procedures with those of discussed nonparametric tests for finding MED.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1185-1186
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• 2008

A nuclear explosion emits a transient radiation pulse like gamma rays. Gamma rays have a high energy and cause unexpected effects in semiconductor devices. These effects are mainly referred to dose-rate latcup and dose-rate upset. By transient radiation pulse in CMOS devices, dose-rate latchup is simulated in this paper.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.877-884
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• 2012

Phase I trials determine the maximum tolerated dose(MTD) and the recommended dose(RD) for subsequent Phase II trials. In this paper, a MTD estimation method applied to a biased coin design is proposed for Phase I Clinical Trials. The suggested MTD estimation method is compared to the SM3 method and the NM method (Lee and Kim, 2012) using a Monte Carlo simulation study.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.597-607
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• 2004

The primary interest of drug development studies is identifying the lowest dose level producing a desirable effect over that of the zero-dose control, which is referred as the minimum effective dose (MED). In this paper, we suggest a nonparametric procedure for identifying the MED with binary or ordered categorical response data. Proposed test and Williams' test are compared by Monte Carlo simulation study and discussed.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.253-260
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• 2019

Radiation dose enhancement is a method of increasing the cross section of interaction, thus increasing the deposited dose. This can contribute to linear energy transfer, LET and relative biological effectiveness, RBE. Previous studies on dose enhancement have been mainly focused on X, ${\gamma}-rays$, but in this study, the dose enhancement was analyzed for proton using Monte Carlo simulation using MCNP6. Based on the mathematical modeling method, energy spectrum and relative intensity of spread out Bragg-peak were calculated, and evaluated dose enhancement factor and dose distribution of dose enhancement material, such as aurum and gadolinium. Dose enhancement factor of 1.085-1.120 folds in aurum, 1.047-1.091 folds in gadolinium was shown. In addition, it showed a decrease of 95% modulation range and practical range. This may lead to an uncertain dose in the tumor tissue as well as dose enhancement. Therefore, it is necessary to make appropriate corrections for spread out Bragg-peak and practical range from mass stopping power. It is expected that Monte Carlo simulation for dose enhancement will be used as basic data for in-vivo and in-vitro experiments.