• 전자공학회논문지A
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• 제31A권5호
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• pp.134-148
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• 1994

A full two-dimensional MOSFET simulator utilizing the Mixed Particle Monte Carlo method is introduced. Particle simulation for both electrons and holes are self-consistently coupled with Poisson 's equation. To demonstrate the performance of the simulator, steady state and transient state solutions of the terminal characteristics and the internal physical quantities are obtained for 0.25$\mu$m MOSFETs with three different structures` conventional single drain, LDD and GOLD MOSFET structures.

• Communications for Statistical Applications and Methods
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• 제5권1호
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• pp.55-67
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• 1998

Recent work by Shin and Sarkar (1996) examines model misspecification problems for nonstationary time series. Shin and Sarkar introduce a general regression model with integrated errors and one system of integrated regressors and discuss the limiting distributions of the OLS estimators and the usual OLS statistics such as $\hat{\sigma^2}$t, DW and $R^2$. We analyze three different model misspecification problems through a Monte Carlo study and investigate each model misspecification problem. Our Monte Carlo experiments show that DW and $R^2$ can be in general used as diagnostic tools to detect spurious regression, misspecification of nonstationary autoregressive and polynomial regression models.

• Journal of the Korean Statistical Society
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• 제36권3호
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• pp.435-445
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• 2007

This paper addresses for the first time the use of complete data information criteria in unsupervised learning of the Naive-Bayes model. A Monte Carlo study sets a large experimental design to assess these criteria, unusual in the Bayesian network literature. The simulation results show that complete data information criteria underperforms the Bayesian information criterion (BIC) for these Bayesian networks.

• 한국세라믹학회지
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• 제23권5호
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• pp.47-54
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• 1986

The structures of crystalline vitreous and liquid $SiO_2$ were Monte carlo simulated employing the potential energy function comprising Lennard-Jones 2-body and Axilrod-Teller 3-body potentials. Although the Si-O-Si angular distribution functions obtained in the simulation appear to be higher than the experimental results the other simulation results including SiO, O-O and Si-Si radial distribution functions and O-Si-O anglular distribution functions agree well with experimental data within acceptable limits. Themost important outcome in this study is that various $SiO_2$forms were successfully reproduced with the same potential energy function.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1988년도 춘계학술대회 논문집
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• pp.56-59
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• 1988

Electron transport properties of gallium arsenide in an electric field are simulated the drift velocity, Mn.energy, electron occupation, mobility in the temperature range $77^{\circ}K-500^{\circ}K$ using a Monte Carlo Method. Therefore it can be used for a GaAs MESFET design.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2000년도 봄 학술발표논문집 Vol.27 No.1 (B)
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• pp.235-237
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• 2000

본 논문에서는 환경의 변화에 민감한 시계열 데이터인 주가의 변동과정을 보다 효과적으로 설명하기 위한 방안의 하나로 강화 학습 모형의 도입을 제안하며, 특정 시점의 주가 추세를 평가하는 기준으로 가치도 함수를 채택한다. 가치도 함수의 계산에는 강화 학습 알고리즘의 일종인 Monte Carlo 알고리즘을 적용하고, 신경망 구현에 의해 구한 근사 가치도의 적절성을 평가하였다. 실험 결과로 볼 때, 여타 강화 학습 알고리즘을 추가적으로 적용할 경우, 주가 변동의 시계열적 특성을 더욱 잘 반영할 수 있을 것으로 판단된다.

• Korea-Australia Rheology Journal
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• 제19권1호
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• pp.7-16
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• 2007

A dynamic Monte Carlo percolation grid simulation is used to predict the cure behaviour of thermoset materials. Molecules are distributed in a fixed grid and a probability of reaction is assigned to each pair of neighbouring units considering both reaction rates and diffusion. The concentration and network characteristics are predicted throughout the whole curing process and compared to experimental data for an epoxy-amine matrix.

• Journal of the Korean Data and Information Science Society
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• 제11권2호
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• pp.139-155
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• 2000

An exclusive simulation study is conducted in computing means for order statistics in standard normal variate. Monte Carlo moments are used in Shapiro-Francia W' statistic computation. Finally, quantiles for Shapiro-Francia W' are generated. The study shows that in computing means for order statistics in standard normal variate, complicated distributions and intensive numerical integrations can be avoided by using Monte Carlo simulation. Lack of accuracy is minimal and computation simplicity is noteworthy.

• Nuclear Engineering and Technology
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• 제41권4호
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• pp.381-390
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• 2009

This article provides selects of outstanding problems in computational neutron transport, with some suggested approaches thereto, as follows: i) ray effect in discrete ordinates method, ii) diffusion synthetic acceleration in strongly heterogeneous problems, iii) method of characteristics extension to three-dimensional geometry, iv) fission source and $k_{eff}$ convergence in Monte Carlo, v) depletion in Monte Carlo, vi) nuclear data evaluation, and vii) uncertainty estimation, including covariance data.

• 한국시뮬레이션학회논문지
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• 제9권3호
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• pp.43-51
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• 2000

In regression model, we estimate the unknown parameters by using various methods. There are the least squares method which is the most general, the least absolute deviation method, the regression quantile method and the asymmetric least squares method. In this paper, we will compare each others with two cases: firstly the theoretical comparison in the asymptotic sense and then the practical comparison using Monte Carlo simulation for a small sample size.