• Bulletin of the Korean Chemical Society
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• v.33 no.3
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• pp.971-974
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• 2012

The facilitated diffusion effect on protein-DNA binding is studied. A rigorous theoretical approach is presented to deal with the coupling between one-dimensional and three-dimensional diffusive motions. For a simplified model, the present approach can provide numerically exact results, which are confirmed by the lattice-based Monte Carlo simulations.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.7
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• pp.657-664
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• 2011

This study proposes an inverse method for estimating the boundary temperature in a gas-filled, onedimensional parallel domain enclosed by parallel plates. The distance between the plates is considered submicron to one mm. In the current method, it is assumed that the conditions of both heat flux and temperature are simultaneously applicable to one boundary, while no conditions are applicable to the other boundary The temperature on one of the boundaries should be inversely determined from the known temperature and heat flux on the other boundary. This study proposes a procedure for estimating the unknown boundary temperature through Monte Carlo simulation. Both the forward and inverse problems employ the Monte Carlo approach. The forward (direct) problem is solved by using the direct simulation Monte Carlo while the inverse solution is obtained by the simulated annealing.

• Journal of the Korean Electrochemical Society
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• v.5 no.2
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• pp.79-85
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• 2002

The present article is concerned with the application of the Monte Carlo simulation to electrochemistry of lithium intercalation from the thermodynamic view point. This article first introduced the fundamental concepts of the ensembles, and Ising and lattice gas models in statistical thermodynamics for the Monte Carlo simulation in brief. Finally the Monte Carlo method based upon the lattice gas model was employed to analyse thermodynamics of the lithium intercalation into the transition metal oxides. Especially we dealt with the thermodynamic properties as the electrode potential curve and the partial molar internal energy and entropy of lithium ion in the case of the $LiMn_2O_4$ electrode, and consequently confirmed the utility of the Monte Carlo method in the field of electrochemistry of the lithium intercalation.

• Journal of the Korean Electrochemical Society
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• v.5 no.2
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• pp.86-92
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• 2002

The present article is concerned with the application of the kinetic Monte Carlo simulation to electrochemistry of lithium intercalation from the kinetic view point. Basic concepts of the kinetic Monte Carlo method and the transition state theory were first introduced, and then the simulation procedures were explained to evaluate diffusion process. Finally the kinetic Monte Carlo method based upon the transition state theory was employed under the cell-impedance-controlled constraint to analyse the current transient and the linear sweep voltammogram for the $LiMn_2O_4$ electrode, one of the intercalation compounds. From the results, it was found that the kinetic Monte Carlo method is much relevant to investigate kinetics of the lithium intercalation in the field of electrochemistry.

• Asia-Pacific Journal of Business
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• v.14 no.1
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• pp.149-169
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• 2023

Purpose - The main purpose of this study is to develop the stress test model for Korean banks by exploring the optimal Monte Carlo simulation and BIS forecasting model. Design/methodology/approach - This study selects 15 Korean banks as sample financial firms and collects relevant 76 quarterly data for the period between year 2000 and 2018 from KRX(Korea Excange), Bank of Korea, and FnGuide. The Regression analysis, Unit-root test, and Monte Carlo simulation are hired to analyze the data. Findings - First, most of the sample banks failed to keep 8% BIS ratio for the adverse and severely Adverse Scenarios, implying that Korean banks must make every effort to realize better BIS ratios under adverse market conditions. Second, we suggest the better Monte Carlo simulation model for the Korean banks by finding that the more appropriate volatility should be different depending on variables rather than simple two-sigma which has been used in the previous studies. Third, we find that the stepwise regression model is better fitted than simple regression model in forecasting macro-economic variables for the BIS variables. Fourth, we find that, for the more robust and significant statistical results in designing stress tests, Korean banks are required to construct more valid time-series and cross-sectional data-base. Research implications or Originality - The above results all together show that the optimal volatility in designing optimal Monte Carlo simulation varies depending on the country, and many Korean banks fail to pass sress test under the adverse and severely adverse scenarios, implying that Korean banks need to make improvement in the BIS ratio.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1255-1265
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• 2018

The need for a PSA (Probabilistic Safety Assessment) for a multi-unit at a site is growing after the Fukushima accident. Many countries have been studying issues regarding a multi-unit PSA. One of these issues is the problem of many combinations of accident sequences in a multi-unit PSA. This paper deals with the methodology and software to quantify a PSA scenarios for a multi-unit site. Two approaches are developed to quantify a multi-unit PSA. One is to use a minimal cut set approach, and the other is to use a Monte Carlo approach.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.67-72
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• 2002

A Bayesian testing procedure is proposed for assessment of bioequivalence in both mean and variance which ensures population bioequivalence under normality assumption. We derive the joint posterior distribution of the means and variances in a standard 2 ${\times}$ 2 crossover experimental design and propose a Bayesian testing procedure for bioequivalence based on a Markov chain Monte Carlo methods. The proposed method is applied to a real data set.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.215-221
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• 1997

A new approach in solving design centering problem is presented. Like most stochastic optimization problems, optimal design centering problems have intrinsic difficulties in multivariate intergration of probability density functions. In order to avoid to avoid those difficulties, genetic algorithm and very coarse Monte Carlo simulation are used in this research. The new algorithm performs robustly while producing improved yields. This result implies that the combination of robust optimization methods and approximated simulation schemes would give promising ways for many stochastic optimizations which are inappropriate for mathematical programming.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.268-275
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• 2003

We consider the Bayesian accelerated failure time model. The error distribution is assigned a skewed normal distribution which is including normal distribution. For noninformative priors of regression coefficients, we show the propriety of posterior distribution. A Markov Chain Monte Carlo algorithm(i.e., Gibbs Sampler) is used to obtain a predictive distribution for a future observation and Bayes estimates of regression coefficients.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1027-1028
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• 2011

In this paper, three reliability calculation algorithms: Monte Carlo Simulation (MCS), Reliability Index Approach (RIA), and Sensitivity-based Monte Carlo Simulation (SMCS) are studied. Their efficiency and accuracy are validated by analytic test functions.