• Asian Journal of Innovation and Policy
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• v.10 no.1
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• pp.108-131
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• 2021

The increase of international trade across countries and borders results in increased risks associated with the inflow of new pests and diseases. These risks are likely to be increased more rapidly due to climate change. Some countries implement strict regulations on imports to prevent these risks and protect biosecurity, food safety, and public health. However, the problems arise when the diseases and pests are found in a country where their economic structure largely depends on agricultural exports and cause ripple effects on other industries and ecosystems. Therefore, establishing an effective quarantine system is essential to protect and recover from the damage caused by non-native diseases and pests. This study's objectives are 1) analyzing the agricultural policies relate to the quarantine system on diseases and pests in Korea, 2) evaluating the Korea plant quarantine system's value, and 3) simulating plant quarantine policy strategies. We estimated the Korean quarantine system's benefits on diseases and pests to reach these objectives. The benefits are measured with a willingness to pay from respondents surveyed by the contingent valuation method (CVM). The CVM approach directly asks people how much they would willingly pay for food security. Finally, the Korean quarantine system's values are simulated with several policy scenarios and different scales of infection at the regional level. The results of this study can deliver policy implications on the quarantine system innovation in developing countries including Asia.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.131-146
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• 2022

Logit models are commonly used to predicting and classifying categorical response variables. Most Bayesian approaches to logit models are implemented based on the Metropolis-Hastings algorithm. However, the algorithm has disadvantages of slow convergence and difficulty in ensuring adequacy for the proposal distribution. Therefore, we use auxiliary mixture sampler proposed by Frühwirth-Schnatter and Frühwirth (2007) to estimate logit models. This method introduces two sequences of auxiliary latent variables to make logit models satisfy normality and linearity. As a result, the method leads that logit model can be easily implemented by Gibbs sampling. We applied the proposed method to diabetes data from the Community Health Survey (2020) of the Korea Disease Control and Prevention Agency and compared performance with Metropolis-Hastings algorithm. In addition, we showed that the logit model using auxiliary mixture sampling has a great classification performance comparable to that of the machine learning models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1060-1070
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• 2022

With the development of information technology, the size of the system has become larger and diversified, and the existing role-based access control has faced limitations. Blockchain technology is being used in various fields by presenting new solutions to existing security vulnerabilities. This paper suggests efficient role-based access control in a blockchain where the required gas and processing time vary depending on the access frequency and capacity of the storage. The proposed method redefines the role of reusable units, introduces a hierarchical structure that can efficiently reflect dynamic states to enhance efficiency and scalability, and includes user-centered authentication functions to enable cryptocurrency linkage. The proposed model was theoretically verified using Markov chain, implemented in Ethereum private network, and compared experiments on representative functions were conducted to verify the time and gas efficiency required for user addition and transaction registration. Based on this in the future, structural expansion and experiments are required in consideration of exception situations.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.115-127
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• 2023

Multinomial probit model is a popular model for multiclass classification and choice model. Markov chain Monte Carlo (MCMC) method is widely used for estimating multinomial probit model, but its computational cost is high. However, it is well known that variational Bayesian approximation is more computationally efficient than MCMC, because it uses subsets of samples. In this study, we describe multinomial probit model with Gaussian process classification and how to employ variational Bayesian approximation on the model. This study also compares the results of variational Bayesian multinomial probit model to the results of naive Bayes, K-nearest neighbors and support vector machine for the UCI mice protein expression level data.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.461-461
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• 2023

하구담수호는 하구에 방조제를 축조하여 인공적으로 조성된 저수지로 배수갑문을 통해 적정수위를 유지하고 담수된 물은 농업용수, 공업 및 생활용수로 활용되고 있다. 최근 담수호 수질을 살펴보면 호소수 수질환경기준 IV등급을 상회하여 농업용수로 부적합한 것으로 나타났다. 하구담수호 수질은 간척농지와 담수호 유역내 농경지, 축사 등에서 배출되는 영양염류, 유사 등에 의해 오염되며, 이들은 경지의 경사, 토양, 강우 특성 등과 같이 다양한 인자들에 의하여 영향을 받는다. 도시화와 기후변화 등으로 인해 변화하는 환경에서 지속가능한 수자원 관리를 위해 하구담수호 물환경의 변화를 분석할 필요가 있다. 따라서 본 연구에서는 간월호 유역을 대상으로 유역-호소 연계 모형을 이용하여 미래 기상, 토지이용, 용수수요량 등의 변화에 따른 담수호 물환경을 분석하였다. SSP(Shared Socioeconomic Pathways) 기후변화 시나리오를 활용하여 미래 기상을 적용하였으며 Markov Chain기법 및 FLUS (Future Land-Use Simulation model)모형을 통해 미래 토지이용을 구축하였다. 미래 환경 변화를 적용하여 HSPF-EFDC-WASP 모형을 구동하여 담수호의 수문, 수질 분석을 수행하였다. 이 연구의 결과는 미래의 환경 변화에 대응하기 위해 하구담수호를 관리하기 위한 효과적인 전략을 개발하는 데 활용될 것으로 사료된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.527-534
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• 2023

Triple modular redundancy (TMR) systems can continue their mission by virtue of their structural redundancy even if one processor is attacked by faults. In this paper, we propose a new fault tolerance strategy by introducing checkpoints into the TMR system in which data saving and fault detection processes are separated while they corporate together in the conventional checkpoints. Faults in one processor are tolerated by synchronizing the state of three processors upon detecting faults. Simultaneous faults occurring to more than one processor are tolerated by re-executing the task from the latest checkpoint. We propose the checkpoint placement and fault detection strategy to maximize the probability of successful execution of a task within the given deadline. We develop the Markov chain model for the TMR system having the proposed checkpoint strategy, and derive the optimal fault detection and checkpoint interval.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.70.2-71
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• 2021

We examine gas kinematics and star formation activities of NGC 6822, a gas-rich dwarf irregular galaxy in the Local Group at a distance of ~490 kpc. We perform profile decomposition of all the line-of-sight (LOS) HI velocity profiles of the high-resolution (42.4" × 12" spatial; 1.6 km/s spectral) HI data cube of the galaxy, taken with the Australian Telescope Compact Array (ATCA). To this end, we use a novel tool based on Bayesian Markov Chain Monte Carlo (MCMC) techniques, the so-called BAYGAUD, which allows us to decompose a velocity profile into an optimal number of Gaussian components in a quantitative manner. We group all the decomposed components into bulk-narrow, bulk-broad, and non-bulk gas components classified with respect to their velocity dispersions and the amounts of velocity offset from the global kinematics, respectively. Using the surface densities and velocity dispersions of the kinematically decomposed HI gas maps together with the rotation curve of NGC 6822, we derive Toomre-Q parameters for individual regions of the galaxy which quantify the level of local gravitational instability of the gaseous disk. We also measure the local star formation rate (SFR) of the corresponding regions in the galaxy by combining GALEX Far-ultraviolet (FUV) and WISE 22㎛ images. We then relate the gas and SFR surface densities in order to investigate the local Kennicutt-Schmidt (K-S) law of gravitationally unstable regions which are selected from the Toomre Q analysis. Of the three groups, the bulk-narrow, bulk-broad and non-bulk gas components, we find that the lower Toomre-Q values the bulk-narrow gas components have, the more consistent with the linear extension of the K-S law derived from molecular hydrogen (H2) observations.

• Journal of Korea Trade
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• v.27 no.2
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• pp.96-114
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• 2023

Purpose - This paper elucidates a nexus between the occurrence of rare disaster events and the volatility of economic growth by distinguishing the likelihood of rare events from stochastic volatility. We provide new empirical facts based on a quarterly time series. In particular, we focus on the role of financial liberalization in spreading the economic crisis in developing countries. Design/methodology - We use quarterly data on consumption expenditure (real per capita consumption) from 44 countries, including advanced and developing countries, ending in the fourth quarter of 2020. We estimate the likelihood of rare event occurrences and stochastic volatility for countries using the Bayesian Markov chain Monte Carlo (MCMC) method developed by Barro and Jin (2021). We present our estimation results for the relationship between rare disaster events, stochastic volatility, and growth volatility. Findings - We find the global common disaster event, the COVID-19 pandemic, and thirteen country-specific disaster events. Consumption falls by about 7% on average in the first quarter of a disaster and by 4% in the long run. The occurrence of rare disaster events and the volatility of gross domestic product (GDP) growth are positively correlated (4.8%), whereas the rare events and GDP growth rate are negatively correlated (-12.1%). In particular, financial liberalization has played an important role in exacerbating the adverse impact of both rare disasters and financial market instability on growth volatility. Several case studies, including the case of South Korea, provide insights into the cause of major financial crises in small open developing countries, including the Asian currency crisis of 1998. Originality/value - This paper presents new empirical facts on the relationship between the occurrence of rare disaster events (or stochastic volatility) and growth volatility. Increasing data frequency allows for greater accuracy in assessing a country's specific risk. Our findings suggest that financial market and institutional stability can be vital for buffering against rare disaster shocks. It is necessary to preemptively strengthen the foundation for financial stability in developing countries and increase the quality of the information provided to markets.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.326-326
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• 2021

장기간에 걸쳐 넓은 지역에 대해 발생하는 가뭄을 예측하기위해 많은 학자들의 기술적, 학술적 시도가 있어왔다. 본 연구에서는 복잡한 시계열을 가진 가뭄을 전망하는 방법 중 시나리오에 기반을 둔 가뭄전망 방법과 실시간으로 가뭄을 예측하는 비시나리오 기반의 방법 등을 이용하여 미래 가뭄전망을 실시했다. 시나리오에 기반을 둔 가뭄전망 방법으로는, 3개월 GCM(General Circulation Model) 예측 결과를 바탕으로 2009년도 PDSI(Palmer Drought Severity Index) 가뭄지수를 산정하여 가뭄심도에 대한 단기예측을 실시하였다. 또, 통계학적 방법과 물리적 모델(Physical model)에 기반을 둔 확정론적 수치해석 방법을 이용하여 비시나리오 기반 가뭄을 예측했다. 기존 가뭄을 통계학적 방법으로 예측하기 위해서 시도된 대표적인 방법으로 ARIMA(Autoregressive Integrated Moving Average) 모델의 예측에 대한 한계를 극복하기위해 서포트 벡터 회귀(support vector regression, SVR)와 웨이블릿(wavelet neural network) 신경망을 이용해 SPI를 측정하였다. 최적모델구조는 RMSE(root mean square error), MAE(mean absolute error) 및 R(correlation Coefficient)를 통해 선정하였고, 1-6개월의 선행예보 시간을 갖고 가뭄을 전망하였다. 그리고 SPI를 이용하여, 마코프 연쇄(Markov chain) 및 대수선형모델(log-linear model)을 적용하여 SPI기반 가뭄예측의 정확도를 검증하였으며, 터키의 아나톨리아(Anatolia) 지역을 대상으로 뉴로퍼지모델(Neuro-Fuzzy)을 적용하여 1964-2006년 기간의 월평균 강수량과 SPI를 바탕으로 가뭄을 예측하였다. 가뭄 빈도와 패턴이 불규칙적으로 변하며 지역별 강수량의 양극화가 심화됨에 따라 가뭄예측의 정확도를 높여야 하는 요구가 커지고 있다. 본 연구에서는 복잡하고 비선형성으로 이루어진 가뭄 패턴을 기상학적 가뭄의 정도를 나타내는 표준강수증발지수(SPEI, Standardized Precipitation Evapotranspiration Index)인 월SPEI와 일SPEI를 기계학습모델에 적용하여 예측개선 모형을 개발하고자 한다.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.61.4-62
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• 2020

We present H I gas kinematics and star formation activities of NGC 6822, a dwarf galaxy located in the Local Volume at a distance of ~490 kpc. We perform profile decomposition of the line-of-sight velocity profiles of the high-resolution (~42.4" × 12") spatial; ~1.6 km/s spectral) H I data cube taken with the Australia Telescope Compact Array (ATCA). For this, we use a new tool, the so-called BAYGAUD (BAYesian GAUssian Decompositor) which is based on Bayesian Markov Chain Monte Carlo (MCMC) techniques, allowing us to decompose a line-of-sight velocity profile into an optimal number of Gaussian components in a quantitative manner. We classify the decomposed H I gas components of NGC 6822 into kinematically cold, warm or hot ones with respect to their velocity dispersion: 1) cold: < 4 km/s, 2) warm: 4 ~ 8 km/s, 3) hot: > 8 km/s. We then derive the Toomre-Q parameters of NGC 6822 using the kinematically decomposed H I gas maps. We also correlate their gas surface densities with the surface star formation rates derived using both GALEX far-ultraviolet and WISE 22 micron data to examine the impact of gas turbulence caused by stellar feedback on the Kennicutt-Schmidt (K-S) law. The kinematically cold component is likely to better follow the linear extension of the Kennicutt-Schmidt (K-S) law for molecular hydrogen (H2) at the low gas surface density regime where H I is not saturated.