• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.340-343
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• 2003

This study presents a practical procedure for the Bayesian inversion of geophysical data by Markov chain Monte Carlo (MCMC) sampling and geostatistics. We have applied geostatistical techniques for the acquisition of prior model information, and then the MCMC method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter. This approach provides an effective way to treat Bayesian inversion of geophysical data and reduce the non-uniqueness by incorporating various prior information.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.41.2-42
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• 2017

We are planning to conduct Monte Carlo simulations for the Na exospheres of the Moon including localized sources on the surface in addition to the global isotropic and anisotropic sources, which were previously studied. The simulation models are based on Lee et al. (2011), who presented a satisfactory interpretation for the isotropic and anisotropic sources of the Lunar Na exosphere. We will compare our preliminary models with existing and the future lunar tail/exospheric observations by the LADEE and NASA's coronagraph-monitoring programs. Ground-based data show global-scale outflows of Na in contrast to small-scale data usually obtained near the orbits of spacecraft.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.613-635
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• 2001

This paper proposes a skewed multivariate probit model for analyzing a correlated binary response data with covariates. The proposed model is formulated by introducing an asymmetric link based upon a skewed multivariate normal distribution. The model connected to the asymmetric multivariate link, allows for flexible modeling of the correlation structure among binary responses and straightforward interpretation of the parameters. However, complex likelihood function of the model prevents us from fitting and analyzing the model analytically. Simulation-based Bayesian inference methodologies are provided to overcome the problem. We examine the suggested methods through two data sets in order to demonstrate their performances.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.169-181
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• 2014

Marginalized random effects models (MREM) are commonly used to analyze longitudinal categorical data when the population-averaged effects is of interest. In these models, random effects are used to explain both subject and time variations. The estimation of the random effects covariance matrix is not simple in MREM because of the high dimension and the positive definiteness. A relatively simple structure for the correlation is assumed such as a homogeneous AR(1) structure; however, it is too strong of an assumption. In consequence, the estimates of the fixed effects can be biased. To avoid this problem, we introduce one approach to explain a heterogenous random effects covariance matrix using a modified Cholesky decomposition. The approach results in parameters that can be easily modeled without concern that the resulting estimator will not be positive definite. The interpretation of the parameters is sensible. We analyze metabolic syndrome data from a Korean Genomic Epidemiology Study using this method.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.229-237
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• 2023

The mechanics underlying photon and electron interactions was validated using our developed Brachytherapy computer code for high Dose Rate (HDR). By comparing the photon cross-section utilizing multiple physics libraries in the developed code, the results were benchmarked against experimental and theoretical findings. Klein-Nishina and experimental cross-section results were in good agreement with the Livermore library results. For two therapeutically relevant materials, the first scattered electron range was measured within 1 mm and 2 mm, which has significant implications for the interpretation of the kernel dose spikes observed in previous research.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.27.1-27.1
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• 2010

Globular cluster (GC) systems in most galaxies, particularly in ellipticals, show bimodal color distributions. Because broadband colors trace metallicity at old ages, this phenomenon has been commonly interpreted as bimodal metallicity distributions, implying the presence of two sub-populations in the globular cluster system within a galaxy. However, a new explanation has recently been proposed, in which the non-linear nature of color-metallicity relations induced by horizontal-branch stars can produce bimodal color distributions even from unimodal metallicity distributions. In this study, we put these two explanations to the test on the origin of color bimodality, using multi-band (U,B,V and I) photometry of globular clusters in NGC 1399, the central giant elliptical galaxy in Fornax galaxy cluster. We find significant changes in the morphology of color distributions when using different colors. The observation is also well reproduced by the Monte Carlo realization of GC color when a unimodal metallicity distribution and the theoretical non-linear color-metallicity relations are assumed. We discuss the implications regarding theories on galaxy formation and evolution.

• Journal of The Korean Astronomical Society
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• v.36 no.3
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• pp.177-187
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• 2003

Active galactic nuclei (AGNs) are distant, powerful sources of radiation over the entire electromagnetic spectrum, from radio waves to gamma-rays. There is much evidence that they are driven by gravitational accretion of stars, dust, and gas, onto central massive black holes (MBHs) imprisoning anywhere from $\~$1 to $\~$10,000 million solar masses; such objects may naturally form in the centers of galaxies during their normal dynamical evolution. A small fraction of AGNs, of the radio-loud type (RLAGNs), are somehow able to generate powerful synchrotron-emitting structures (cores, jets, lobes) with sizes ranging from pc to Mpc. A brief summary of AGN observations and theories is given, with an emphasis on RLAGNs. Preliminary results from the imaging of 10000 extragalactic radio sources observed in the MITVLA snapshot survey, and from a new analytic theory of the time-variable power output from Kerr black hole magnetospheres, are presented. To better understand the complex physical processes within the central engines of AGNs, it is important to confront the observations with theories, from the viewpoint of analyzing the time-variable behaviours of AGNs - which have been recorded over both 'short' human ($10^0-10^9\;s$) and 'long' cosmic ($10^{13} - 10^{17}\;s$) timescales. Some key ingredients of a basic mathematical formalism are outlined, which may help in building detailed Monte-Carlo models of evolving AGN populations; such numerical calculations should be potentially important tools for useful interpretation of the large amounts of statistical data now publicly available for both AGNs and RLAGNs.

• Progress in Medical Physics
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• v.20 no.2
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• pp.51-61
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• 2009

A Compton camera, which is based on the geometrical interpretation of Compton scattering, is a very promising gamma-ray imaging device considering its several advantages over the conventional gamma-ray imaging devices: high imaging sensitivity, 3-D imaging capability from a fixed position, multi-tracing functionality, and almost no limitation in photon energy. In the present study, a Monte Carlo-based, user-friendly Compton imaging simulator was developed in the form of a graphical user interface (GUI) based on Geant4 and $MATLAB^{TM}$. The simulator was tested against the experimental result of the double-scattering Compton camera, which is under development at Hanyang University in Korea. The imaging resolution of the simulated Compton image well agreed with that of the measured image. The imaging sensitivity of the measured data was 2~3 times higher than that of the simulated data, which is due to the fact that the measured data contains the random coincidence events. The performance of a stacking-structure type Compton camera was evaluated by using the simulator. The result shows that the Compton camera shows its highest performance when it uses 4 layers of scatterer detectors.

• Journal of Environmental Health Sciences
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• v.41 no.6
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• pp.425-437
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• 2015

Objectives: Risk assessment is a tool for predicting and reducing uncertainty related to the effects of future activities. Probability approaches are the main elements in risk assessment, but confusion about the interpretation and use of assessment factors often undermines the message of the analyses. The aim of this study is to provide a guideline for systematic reduction plans regarding uncertainty in risk assessment. Methods: Articles and reports were collected online using the key words "uncertainty analysis" on risk assessment. Uncertainty analysis was conducted based on reports focusing on procedures for analysis methods by the World Health Organization (WHO) and U.S. Environmental Protection Agency (USEPA). In addition, case studies were performed in order to verify suggested methods qualitatively and quantitatively with exposure data, including measured data on toluene and styrene in residential spaces and multi-use facilities. Results: Based on an analysis of the data on uncertainty, three major factors including scenario, model, and parameters were identified as the main sources of uncertainty, and tiered approaches were determined. In the case study, the risk of toluene and styrene was evaluated and the most influential factors were also determined. Five reduction plans were presented: providing standard guidelines, using reliable exposure factors, possessing quality controls for analysis and scientific expertise, and introducing a peer review system. Conclusion: In this study, we established a method for reducing uncertainty by taking into account the major factors. Also, we showed a method for uncertainty analysis with tiered approaches. However, uncertainties are difficult to define because they are generated by many factors. Therefore, further studies are needed for the development of technical guidelines based on the representative scenario, model, and parameters developed in this study.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.258-265
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• 2021

High levels for noise and a loss of true signal make the quantitative interpretation of nuclear medicine (NM) images difficult. An application of profile optimization using a sigmoidal function in this study was used to acquire the NM images with high quality. And the images were acquired by using three kinds of reconstruction method using each same sinogram: a standard filtered back-projection (FBP), an iterative reconstruction (IR) technique, and the sigmoidal function profile optimization (SFPO). Comparison of image according to reconstruction method was performed to show a superiority of the SFPO for imaging. The images reconstructed by using the SFPO showed an average of 1.49 times and of 1.17 times better in contrast than the results obtained using the standard FBP and the IR technique, respectively. Higher signal to noise ratios were obtained as an average of 12.30 times and of 3.77 times than results obtained using the standard FBP and the IR technique, respectively. This study confirms that reconstruction with SFPO (vs FBP and vs IR) can lead to better lesion detectability and characterization with noise reduction. It can be developed for future reconstruction technique for the NM imaging.