• Journal of Radiation Protection and Research
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• v.44 no.2
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• pp.72-78
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• 2019

Background: In the calibration and testing laboratory of Korea Atomic Energy Research Institute, the old X-ray generator used for the production of reference X-ray fields was replaced with a new one. For this newly installed X-ray irradiation system, beam alignment as well as the verification of beam qualities was conducted. Materials and Methods: The existing X-ray generator, Phillips MG325, was replaced with YXLON Y.TU 320-D03 in order to generate reference X-ray fields. Theoretical calculations and Monte Carlo simulations were used to determine initial filter thickness. Beam alignment was performed in three steps to deliver a homogeneous radiation dosage to the target at different distances. Finally, the half-value layers were measured for different X-ray fields to verify beam qualities by using an ion chamber. Results and Discussion: Beam alignment was performed in three steps, and collimators and other components were arranged to maintain the uniformity of the mean air kerma rate within ${\pm}2.5%$ at the effective beam diameter of 28 cm. The beam quality was verified by using half-value layer measurement methods specified by American National Standard Institute (ANSI) N13.11-2009 and International Organization for Standardization (ISO)-4037. For each of the nine beams than can be generated by the new X-ray irradiation system, air kerma rates for X-ray fields of different beam qualifies were measured. The results showed that each air kerma rate and homogeneity coefficient of the first and second half-value layers were within ${\pm}5%$ of the recommended values in the standard documents. Conclusion: The results showed that the new X-ray irradiation system provides beam qualities that are as high as moderate beam qualities offered by National Institute of Standards and Technology in ANSI N13.11-2009 and those for narrow-spectrum series of ISO-4037.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.85-101
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• 2022

Derivative-linked securities (DLS) is a type of derivatives that offer an agreed return when the underlying asset price moves within a specified range by the maturity date. The underlying assets of DLS are diverse such as interest rates, exchange rates, crude oil, or gold. A German 10-year bond rate-linked DLS and a USD-GBP CMS rate-linked DLS have recently become a social issue in Korea due to a huge loss to investors. In this regard, this paper accounts for the payoff structure of these products and evaluates their prices and fair coupon rates as well as risk measures such as Value-at-Risk (VaR) and Tail-Value-at-Risk (TVaR). We would like to examine how risky these products were and whether or not their coupon rates were appropriate. We use Hull-White Model as the stochastic model for the underlying assets and Monte Carlo (MC) methods to obtain numerical results. The no-arbitrage prices of the German 10-year bond rate-linked DLS and the USD-GBP CMS rate-linked DLS at the center of the social issue turned out to be 0.9662% and 0.9355% of the original investment, respectively. Considering that Korea government bond rate for 2018 is about 2%, these values are quite low. The fair coupon rates that make the prices of DLS equal to the original investment are computed as 4.76% for the German 10-year bond rate-linked DLS and 7% for the USD-GBP CMS rate-linked DLS. Their actual coupon rates were 1.4% and 3.5%. The 95% VaR and TVaR of the loss for German 10-year bond rate-linked DLS are 37.30% and 64.45%, and those of the loss for USD-GBP CMS rate-linked DLS are 73.98% and 87.43% of the initial investment. Summing up the numerical results obtained, we could see that the DLS products of our interest were indeed quite unfavorable to individual investors.

• Journal of Radiation Protection and Research
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• v.46 no.2
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• pp.39-47
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• 2021

Background: The National Institutes for Quantum and Radiological Science and Technology-National Institute of Radiological Sciences (QST-NIRS) has continuously investigated the undesired radiation exposure in ion beam radiotherapy mainly in carbon-ion radiotherapy (CIRT). This review introduces our investigations on the secondary neutron dose in CIRT with the broad and scanning beam methods. Materials and Methods: The neutron ambient dose equivalents in CIRT are evaluated based on rem meter (WENDI-II) measurements. The out-of-field organ doses assuming prostate cancer and pediatric brain tumor treatments are also evaluated through the Monte Carlo simulation. This evaluation of the out-of-field dose includes contributions from secondary neutrons and secondary charged particles. Results and Discussion: The measurements of the neutron ambient dose equivalents at a 90#x00B0; angle to the beam axis in CIRT with the broad beam method show that the neutron dose per treatment dose in CIRT is lower than that in proton radiotherapy (PRT). For the scanning beam with the energy scanning technique, the neutron dose per treatment dose in CIRT is lower than that in PRT. Moreover, the out-of-field organ doses in CIRT decreased with distance to the target and are less than the lower bound in intensity-modulated radiotherapy (IMRT) shown in AAPM TG-158 (American Association of Physicists in Medicine Task Group). Conclusion: The evaluation of the out-of-field doses is important from the viewpoint of secondary cancer risk after radiotherapy. Secondary neutrons are the major source in CIRT, especially in the distant area from the target volume. However, the dose level in CIRT is similar or lower than that in PRT and IMRT, even if the contributions from all radiation species are included in the evaluation.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.369-382
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• 2024

To suppress the reverberation in the active sonar system, the non-negative matrix factorization-based reverberation suppression methods have been researched recently. An estimation loss function, which makes the multiplication of basis matrices same as the input signals, has to be considered to design the non-negative matrix factorization methods, but the conventional method simply chooses the Kullback-Leibler divergence asthe lossfunction without any considerations. In this paper, we examined that the Kullback-Leibler divergence is the best lossfunction or there isthe other loss function enhancing the performance. First, we derived a modified reverberation suppression algorithm using the generalized beta-divergence function, which includes the Kullback-Leibler divergence. Then, we performed Monte-Carlo simulations using synthesized reverberation for the modified reverberation suppression method. The results showed that the Kullback-Leibler divergence function (β = 1) has good performances in the high signal-to-reverberation environments, but the intermediate function (β = 1.25) between Kullback-Leibler divergence and Euclidean distance has better performance in the low signal-to-reverberation environments.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.449-459
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• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.

• 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 Korean Geotechnical Society
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• v.23 no.12
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• pp.61-73
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• 2007

As a part of Load and Resistance Factor Design(LRFD) code development in Korea, in this paper an intensive reliability analysis was performed to evaluate reliability levels of the two static bearing capacity methods for driven steel pipe piles adopted in Korean Standards for Structure Foundations by the representative reliability methods of First Order Reliability Method(FORM) and Monte Carlo Simulation(MCS). The resistance bias factors for the two static design methods were evaluated by comparing the representative measured bearing capacities with the design values. In determination of the representative bearing capacities of driven steel pipe piles, the 58 data sets of static load tests and soil property tests were collected and analyzed. The static bearing capacity formula and the Meyerhof method using N values were applied to the calculation of the expected design bearing capacity of the piles. The two representative reliability methods(FORM, MCS) based computer programs were developed to facilitate the reliability analysis in this study. Mean Value First Order Second Moment(MVFOSM) approach that provides a simple closed-form solution and two advanced methods of FORM and MCS were used to conduct the intensive reliability analysis using the resistance bias factor statistics obtained, and the results were then compared. In addition, a parametric study was conducted to identify the sensibility and the influence of the random variables on the reliability analysis under consideration.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.115-122
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• 2016

OBJECTIVES : This study develops an evaluation method, which is useful to inspect pavement condition of specific boroughs. This is because pavement condition is broadly divided into five grades via visual inspection, which does not consider the types of deteriorations, and is decided by an investigator having a subjective viewpoint. This visual inspection method is not a satisfactory method for accurate maintenance when various deteriorations occur. METHODS : The performance model considers several factors such as crack, rutting, and IRI. This method is also modified from borough SPI based on SPI (Seoul Pavement Index). Considering limited budget of borough, PI (prediction index) is suggested, which is related to the grade of pavement condition evaluation and type of materials. Practical correlation review is also conducted with statistical verification by using the Monte Carlo simulation. RESULTS : The results of the study show that modified criteria are reasonable. First, the comparison between the visual inspection result and the SPI result indicates that the R-square value is sufficiently high. Second, through the common section, each evaluation method could be compared, and the result shows considerable similarity, which increases when the range is modified. Finally, PI for predicting remaining life and the random number SPI have common parts, which means that each indicator would be adequate to be used as an evaluation method. CONCLUSIONS : Comparison and analysis results show that the developed evaluation method is reasonable for specific boroughs where financial support is inadequate for the evaluation process by using the newer equipment. Moreover, for more accurate evaluation method, previous visual inspection data should be utilized, and the database of inspection equipment have to be collected.

• Smart Structures and Systems
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• v.22 no.5
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose an algorithm that can estimate the distance using disparity based on stereo vision system, even though the obstacle is located in long ranges as well as short ranges. We use sub-pixel interpolation to minimize quantization errors which deteriorate the distance accuracy when calculating the distance with integer disparity, and also we use enhanced adaptive fuzzy strong tracking Kalman filter(EAFSTKF) to improve the distance accuracy and track the path optimally. The proposed method can solve the divergence problem caused by nonlinear dynamics such as various vehicle movements in the conventional Kalman filter(CKF), and also enhance the distance accuracy and reliability. Our simulation results show that the performance of our method improves by about 13.5% compared to other methods in point of root mean square error rate(RMSER).