• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.445-456
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• 2017

For impact assessment of inundation in coastal area due to sea level rise (SLR), model for estimating future peak water level was constructed using observed mean sea level (MSL), storm surge level (SSL) data and calculated tide level (TL) data. Based on time series analysis and quadratic polynomial model for SLR and Monte-Carlo simulation for IC, SSL and TL, 100-year return peak water level is expected to be 2.3, 2.6, 2.8m, respectively (each corresponding to year 2050, 2080, 2100). Further analysis on future potential inundation area showed U-dong, Yongho-dong, Songjeong-dong, Jaesong-dong to be at high risk.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.2
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• pp.47-53
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• 2014

The paper investigates the limit state of deflection for short and medium span steel girder bridges. Deflection depends on stiffness of steel girders and integrity of the reinforced concrete slab (composite action). Load and resistance parameters are treated as random variables. A probabilistic model is developed for prediction of the deflection. The structural performance can be affected by deterioration of components, in particular corrosion of steel girders. In addition, the creep of concrete can greatly influence the deflection of composite structures. Therefore, the statistical models for creep and corrosion of structural steel are incorporated in the model. Structures designed according to the AASHTO LRFD Code are considered. Load and resistance models are developed to account for time-variability of the parameters. Monte Carlo simulations are used to estimate the deflections and probabilities of serviceability failure. Different span lengths and girder spacing are considered for structures designed as moment-controlled and deflection-controlled. A summary of obtained results is presented.

• Journal of the Korean Ceramic Society
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• v.32 no.11
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• pp.1292-1300
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• 1995

The ionic conductivity of NASICON solid electrolytes was simulated by using Monte Carlo Method (MCM). There were included two conduction paths: (1) Na1-Na2 and (2) Na1-Na2 including Na2-Na2. We assumed that mid-Na ions provde an additional driving force for Na mobile ions due to the interionic repulsion between Na1 and Na2 ions. The inflection point of vacancy availability factor, V has been shown at nearby x=2, the maximum mid-Na ions. The inflection point of vacancy availability factor, V has been shown at nearby x=2, the maximum mid-Na sites are occupied. The effective jump frequency factor, V has been shown at nearby x=2, the maximum mid-Na sites are occupied. The effective jump frequency factor, W increased rapidly with the composition at low temperature, but decreased at high temperature region. On Na1-Na2 conduction path, the minimum of charge correlation factor, fc and the maximum of $\sigma$T were appeared at x=2.0. this indicated that mid-Na ions affect on the high ionic conductivity behavior. At the whole range of NASICON composition, 1n $\sigma$T vs. 1/T* plots have been shown Arrhenius behavior but 1n (VWFc) vs. 1/T* have been shown the Arrhenius type tendency at x=2, which mid-Na is being the maximum. The results of MCM agreed with the experimental one when the chosen saddle point value was 6$\varepsilon$ : 3$\varepsilon$. Here the calculated characteristic parameter of materials, K and the phase transition temperature were -4.001$\times$103 and 178$^{\circ}C$ (1/T*=1.92, 1000/T=2.22), respectively.

• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.218-227
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• 2017

In this paper, an algorithm to calculate both bearing and distance error for target detection and localization is proposed using the Cramer Rao lower bound to estimate the minium variance of their error in DOA (Direction Of Arrival) estimation. The performance of arrays in detection and localization depends on the accuracy of DOA, which is affected by a variation of SNR (Signal to Noise Ratio). The SNR is determined by sonar parameters such as a SL (Source Level), TL (Transmission Loss), NL (Noise Level), array shape and beam steering angle. For verification of the suggested method, a Monte Carlo simulation was performed to probabilistically calculate the bearing and distance error according to the SNR which varies with the relative position of the target in space and noise level.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.49-56
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• 2010

In this paper, we implement a Hadoop based cluster for cloud computing and evaluate the performance of this cluster based on application characteristics by executing RandomTextWriter, WordCount, and PI applications. A RandomTextWriter creates given amount of random words and stores them in the HDFS(Hadoop Distributed File System). A WordCount reads an input file and determines the frequency of a given word per block unit. PI application induces PI value using the Monte Carlo law. During simulation, we investigate the effect of data block size and the number of replications on the execution time of applications. Through simulation, we have confirmed that the execution time of RandomTextWriter was proportional to the number of replications. However, the execution time of WordCount and PI were not affected by the number of replications. Moreover, the execution time of WordCount was optimum when the block size was 64~256MB. Therefore, these results show that the performance of cloud computing system can be enhanced by using a scheduling scheme that considers application's characteristics.

• Journal of Radiation Protection and Research
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• v.28 no.2
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• pp.79-85
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• 2003

This study was intended to estimate Hp(10) recommended by the ICRU using the $CaSO_4:Dy,P$ element developed in the KAERI. For the estimation of Hp(10), TL response should be compensated properly through the energy range using filter materials since $CaSO_4:Dy,P$ is of severe photon energy dependent response. Various experiments and computations using Monte Carlo Code were carried out for designing filter satisfying the performance requirements of the ISO related to TL dosimeter. Under the completed filter, the relative response of $CaSO_4:Dy,P$ showed $0.75{\sim}1.0$ for photons in the range of $20{\sim}662keV$. Especially it was possible to reduce the thickness of front filter and simplify the filter combination with rear filter of larger diameter and to considerably improve angular dependence by introducing taper to the filler.

• Journal of the Korea Society for Simulation
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• v.27 no.3
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• pp.99-107
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• 2018

In this paper, we study target tracking in two dimensional space using a Extended Kalman filter(EKF), various Extended Kalman Filter and Cost-Reference Particle Filter(CRPF), which can effectively estimate the state values of nonlinear measurement equation. We introduce various Extended Kalman Filter which the Unscented Kalman Filter(UKF), the Central Difference Kalman Filter(CDKF), the Square Root Unscented Kalman Filter(SR-UKF), and the Central Difference Kalman Filter(SR-CDKF). In this study, we calculate Mean Square Error(MSE) of each filters using Monte-Carlo simulation with unknown noise statistics. Simulation results show that among the various of Extended Kalman filter, Square Root Central Difference Kalman Filter has the best results in terms of speed and performance. And, the Cost-Reference Particle Filter has an advantageous feature that it does not need to know the noise distribution differently from Extended Kalman Filter, and the simulation result shows that the excellent in term of processing speed and accuracy.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1175-1182
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• 2011

In this paper, properties of exact confidence interval and some approximate confidence intervals of hyper-geometric parameter, that is the probability of success p in the population is discussed. Usually, binomial distribution is a well known discrete distribution with abundant usage. Hypergeometric distribution frequently replaces a binomial distribution when it is desirable to make allowance for the finiteness of the population size. For example, an application of the hypergeometric distribution arises in describing a probability model for the number of children attacked by an infectious disease, when a fixed number of them are exposed to it. Exact confidence interval estimation of hypergeometric parameter is reviewed. We consider the approximation of hypergeometirc distribution to the binomial and normal distribution respectively. Approximate confidence intervals based on these approximation are also adequately discussed. The performance of exact confidence interval estimates and approximate confidence intervals of hypergeometric parameter is compared in terms of actual coverage probability by small sample Monte Carlo simulation.

• Economic and Environmental Geology
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• v.28 no.5
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• pp.503-512
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• 1995

Groundwater flow in fracture networks is simulated using a discrete fracture (DF) model which assume that groundwater flows only through the fracture network. This assumption is available if the permeability of rock matrix is very low. It is almost impossible to describe fracture networks perfectly, so a stochastic approach is used. The stochastic approach assumes that the characteristic parameters in fracture network have special distribution patterns. The stochastic model generates fracture networks with some characteristic parameters. The finite element method is used to compute fracture flows. One-dimensional line element is the element type of the finite elements. The simulation results are shown by dominant flow paths in the fracture network. The dominant flow path can be found from the simulated groundwater flow field. The model developed in this study provides the tool to estimate the influences of characteristic parameters on groundwater flow in fracture networks. The influences of some characteristic parameters on the frcture flow are estimated by the Monte Carlo simulation based on 30 realizations.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.291-305
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• 2013

Collective traffic data (BPS, PPS etc.) for detection against the distributed denial of service attack on network is the time sequencing big data. The algorithm to detect the change point in the big data should be accurate and exceed in detection time and detection capability. In this work, the sliding window and discretization method is used to detect the change point in the big data, and propose five nonparametric test statistics using empirical distribution functions and ranks. With various distribution functions and their parameters, the detection time and capability including the detection delay time and the detection ratio for five test methods are explored and discussed via monte carlo simulation and illustrative examples.