• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.113-119
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• 2012

In this paper we propose the method that detects moving objects in autonomous navigation vehicle using LRF sensor data. Object detection and tracking methods are widely used in research area like safe-driving, safe-navigation of the autonomous vehicle. The proposed method consists of three steps: data segmentation, mobility classification and object tracking. In order to make the raw LRF sensor data to be useful, Occupancy grid is generated and the raw data is segmented according to its appearance. For classifying whether the object is moving or static, trajectory patterns are analysed. As the last step, Markov chain Monte Carlo (MCMC) method is used for tracking the object. Experimental results indicate that the proposed method can accurately detect moving objects.

• Journal of Magnetics
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• v.17 no.4
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• pp.233-241
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• 2012

In this work, Monte Carlo simulation was used to investigate the magnetization properties of thin ferromagnetic films under a perturbation from a supplied heat pulse on one surface of the films. The finite difference method was used to extract the local temperature of each layer of the films as a function of time for various heat source power and heating period. Then, with the variation of the films temperature, Metropolis method was used to update the magnetic moment in magnetic grain, under the Ising framework and using the FePt parameters. With the extracted magnetization profiles, the relationship between magnetization relaxation in accordance with relevant heat parameters and films thickness was reported and discussed, with a purpose to form a database for future use.

• Proceedings of the Korea Concrete Institute Conference
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• 2009.05a
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• pp.301-302
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• 2009

Uncertainties in carbonation process of concrete structures are treated by probability-based durability analysis for carbonation using Monte Carlo simulation technique. The results requires the minimum cover thickness of 53mm for 10% of corrosion probability under 4mm/$year^{0.5}$ of carbonation coefficient. The more researches on statistical properties of design variables may give reliable durability analysis/design methods for carbonation of concrete structures.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.2
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• pp.121-128
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• 2004

This paper presents a new approach for determining an accurate incentive levels of Direct Load Control (DLC) program using sequential Monte Carlo Simulation (MCS) techniques. The economic analysis of DLC resources needs to identify the hourly-by-hourly expected energy-not-served resulting from the random outage characteristics of generators as well as to reflect the availability and duration of DLC resources, which results the computational explosion. Therefore, the conventional methods are based on the scenario approaches to reduce the computation time as well as to avoid the complexity of economic studies. In this paper, we have developed a new technique based on the sequential MCS to evaluate the required expected load control amount in each hour and to decide the incentive level satisfying the economic constraints. In addition, the mathematical formulation for DLC programs' economic evaluations are developed. To show the efficiency and effectiveness of the suggested method, the numerical studies have been performed for the modified IEEE reliability test system.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.785-790
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• 2008

Vibration of a non-linear system under random parametric excitations was evaluated by probablistic methods. The non-linear characteristic terms of a system were quasi-linearized and excitation terms were remained as they were given. An analytical method where the square mean of error was minimized was ysed. An alternative method was an energy method where the damping energy and rstoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Journal of Korean Society for Quality Management
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• v.43 no.3
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• pp.239-252
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• 2015

Purpose: Lead has been widely used in radiation shielding for its low price and high workability. Recently in several europe countries, use of lead was banned for environmental issues. Also lead can cause health problems like alergies. Alternative materials for lead are highly required. The purpose of this study was to propose lead free radiation shielding material. Methods: Research of radiation shielding in Korea is not easy for certain limits such as radiation materials, experimental facilities and places. The collected data through the research were simulated using MCNPX. The simulation tools used for this study were utilized Monte Carlo method. Results: we suggest new design of lead free radiation shielding material using MCNPX code comparing shielding performance of new composite materials to lead. Conclusion: This newly introduced nano-scale composite of metal and polymer makes new chance for highly lightened radiation protective garments with endurable shielding performance.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.305-313
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• 2002

Regarding to inference about a scalar measure of internal scatter of Ρ-variate normal population, this paper considers an interval estimation of the generalized variance, │$\Sigma$│. Due to complicate sampling distribution, fully parametric frequentist approach for the interval estimation is not available and thus Bayesian method is pursued to calculate the highest probability density (HPD) interval for the generalized variance. It is seen that the marginal posterior distribution of the generalized variance is intractable, and hence a weighted Monte Carlo method, a variant of Chen and Shao (1999) method, is developed to calculate the HPD interval of the generalized variance. Necessary theories involved in the method and computation are provided. Finally, a simulation study is given to illustrate and examine the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.113-114
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• 2006

Vibration of a non-linear system under random excitations was evaluated by probabilistic methods. The non-linear characteristic terms of a system structure were quasi-linearized and excitation terms were remained as they were. An analytical method where the square mean of error was minimized was used. An alternative method was an energy method where the damping energy and restoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.545-557
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• 2018

The inclusion of covariates in the model often affects not only the estimates of meaningful variables of interest but also its statistical significance. Such gap between statistical and subject-matter significance is a critical issue in huge sample studies. A popular huge sample study, the sample cohort data from Korean National Health Insurance Service, showed such gap of significance in the inference for the effect of obesity on cause of mortality, requiring careful consideration. In this regard, this paper proposes a sample size calibration method based on a Monte Carlo t (or z)-test approach without Monte Carlo simulation, and also proposes a test procedure for subject-matter significance using this calibration method in order to complement the deflated p-value in the huge sample size. Our calibration method shows no subject-matter significance of the obesity paradox regardless of race, sex, and age groups, unlike traditional statistical suggestions based on p-values.

• Publications of The Korean Astronomical Society
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• v.24 no.1
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• pp.43-51
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• 2009

We present a Monte-Carlo simulation code, which solves the problem of dust-scattering in interstellar dust clouds with arbitrary light source distribution and dust density structure, and calculate the surface brightness distribution. The method is very flexible and can be applied to radiative transfer problems occurring not only in a single dust cloud, but also in extragalactic dust environment. We compare, for performance test, the result of Monte-Carlo simulation with the well-known analytic approximation for a spherically symmetric homogeneous cloud. We find that the Code approximation gives a very accurate result.