• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.241-248
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• 1997

This paper presents the development procedure and application of the generic component reliability data base considering the dependency among dependent generic compendia in NPPs (Nuclear Power Plants) PSA (Probabilistic Safety Assessment) under construction or without operating history. We use MPRDP (Multi-Purpose Reliability Data Processor) code developed in KAERI (Korea Atomic Energy Research Institute) based on a PEB (Parametric Empirical Bayesian) procedure to estimate the reliability. The employed model in this study accounts for the relative credibility as well as the dependency among generic estimates. Numerical examples and the part of summarized reliability data table are provided as the application.

• East Asian Economic Review
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• v.27 no.3
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• pp.179-211
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• 2023

This paper investigates the relationship between the spread of COVID-19 and time preference. In contrast to previous studies that compared time preferences before and during the pandemic, this study estimates time preferences during the COVID-19 period using eight surveys conducted over two years. Additionally, a regression analysis was conducted on the number of new COVID-19 cases and the time elapsed since the outbreak, with estimated time preference as the dependent variable. Despite a small sample size, statistically significant results were obtained, showing that as the number of new cases increased, time preference also increased. However, this effect diminished over time and disappeared by the end of 2021 in Japan. This may be due to the public's growing familiarity with the risks of COVID-19 and the availability of vaccines and treatments. Despite a significant increase in new cases in 2022, time preference was lower than immediately after the outbreak, and this was reflected in private investments. Immediately after the outbreak of COVID-19, private investments decreased by 12% compared to the previous year, but the investments are returning in 2022 despite the surge in the number of cases. The trend of time preference explains the trend of Japanese private investments very well.

• The Journal of Economics, Marketing and Management
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• v.12 no.3
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• pp.1-12
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• 2024

Purpose: As a major economy attracting foreign investment, China is currently facing significant international economic pressure due to the appreciation of the RMB. Additionally, China is at a critical period of socio-economic development, where foreign direct investment (FDI) plays an indispensable role in stabilizing economic growth, adjusting industrial structure, and promoting economic transformation. Research design, data and methodology: This paper focuses on the relationship between RMB exchange rate expectations and FDI. It examines the magnitude of their relationship through empirical research using cointegration tests, Granger causality tests, and BVAR (Bayesian Vector Autoregression) analysis. Results: The comprehensive study of the empirical results in this paper concludes that there is a long-term cointegrated relationship between China's RMB exchange rate expectations and foreign direct investment, indicating that their relationship is stable in the long run. It is also found that RMB exchange rate expectations have a significantly positive impact in the short term, but this impact is not significant in the long term. Conclusions: The paper also considers the possibility of establishing a China-EU Free Trade Area in the future and offers policy recommendations regarding RMB exchange rate expectations and foreign direct investment.

• Animal Bioscience
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• v.35 no.5
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• pp.648-658
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• 2022

Objective: The identification of nonlinear mixed models that describe the growth trajectory of New Zealand rabbits was performed based on weight records and carcass measures obtained using ultrasonography. Methods: Phenotypic records of body weight (BW) and loin eye area (LEA) were collected from 66 animals raised in a didactic-productive module of cuniculture located in the southern Piaui state, Brazil. The following nonlinear models were tested considering fixed parameters: Brody, Gompertz, Logistic, Richards, Meloun 1, modified Michaelis-Menten, Santana, and von Bertalanffy. The coefficient of determination (R²), mean squared error, percentage of convergence of each model (%C), mean absolute deviation of residuals, Akaike information criterion (AIC), and Bayesian information criterion (BIC) were used to determine the best model. The model that best described the growth trajectory for each trait was also used under the context of mixed models, considering two parameters that admit biological interpretation (A and k) with random effects. Results: The von Bertalanffy model was the best fitting model for BW according to the highest value of R² (0.98) and lowest values of AIC (6,675.30) and BIC (6,691.90). For LEA, the Logistic model was the most appropriate due to the results of R² (0.52), AIC (783.90), and BIC (798.40) obtained using this model. The absolute growth rates estimated using the von Bertalanffy and Logistic models for BW and LEA were 21.51g/d and 3.16 cm², respectively. The relative growth rates at the inflection point were 0.028 for BW (von Bertalanffy) and 0.014 for LEA (Logistic). Conclusion: The von Bertalanffy and Logistic models with random effect at the asymptotic weight are recommended for analysis of ponderal and carcass growth trajectories in New Zealand rabbits. The inclusion of random effects in the asymptotic weight and maturity rate improves the quality of fit in comparison to fixed models.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.75-88
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• 2009

The main purpose of the current research is to introduce the alternative algorithm of the non-recursive batch filter based on the unscented transformation in which the linearization process is unnecessary. The presented algorithm is applied to the orbit determination of a low earth orbiting satellite and compared its results with those of the well-known Bayesian batch least squares estimation and the iterative UKF smoother (IUKS). The system dynamic equations consist of the Earth's geo-potential, the atmospheric drag, solar radiation pressure and the lunar/solar gravitational perturbations. The range, azimuth and elevation angles of the satellite measured from ground stations are used for orbit determination. The characteristics of the non recursive unscented batch filter are analyzed for various aspects, including accuracy of the determined orbit, sensitivity to the initial uncertainty, measurement noise and stability performance in a realistic dynamic system and measurement model. As a result, under large non-linear conditions, the presented non-recursive batch filter yields more accurate results than the other batch filters about 5% for initial uncertainty test and 12% for measurement noise test. Moreover, the presented filter exhibits better convergence reliability than the Bayesian least squares. Hence, it is concluded that the non-recursive batch filter based on the unscented transformation is effectively applicable for highly nonlinear batch estimation problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• Journal of Acupuncture Research
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• v.30 no.3
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• pp.39-49
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• 2013

Objectives : The purpose of this study is to assess the effect of Taegeuk acupuncture on reducing mental stress by analyzing heart rate variability in Soeumin. Methods : Six Soeumin-diagnosed men participated in this study. They were randomly divided into group A and group B. Each participant went through 4 sessions every week with 1 week of washout period in between each session. HRV was measured three times at every session; at baseline, after administering mentally stressful circumstances and after applying Soeumin Taegeuk acupuncture or Soyangin Taegeuk acupuncture. This study was designed as a crossover clinical trial. Group A participants were treated with two sets of Soeumin Taegeuk and Soyangin Taegeuk acupuncture treatment in respective order (i.e. Soeumin Taegeuk - Soyangin Taegeuk - Soeumin Taegeuk - Soyangin Taegeuk acupuncture treatment). Group B participants were treated with reverse-ordered acupuncture treatment (i.e. Soyangin Taegeuk - Soeumin Taegeuk - Soyangin Taegeuk - Soeumin Taegeuk acupuncture treatment ). Bayesian analysis was performed by using WinBUGS(Ver. 1.4.3) for comparison between Soeumin Taegeuk acupuncture and Soyangin Taegeuk acupuncture. Results : Overall, Soeumin Taegeuk acupuncture tends to reduce LF/HF ratio, LF, HF, LF(Norm) and increase HF(Norm) more than Soyangin Taegeuk acupuncture, but the difference was not statistically significant. In one participant, however, Soeumin Taegeuk acupuncture reduced LF/HF ratio, LF(Norm) and increased HF(Norm) more than Soyangin Taegeuk acupuncture, and the difference was stastatistically significant. Conclusions : This study suggests that Soeumin Taegeuk acupuncture might be an effective means of stabilizing mental stress-induced imbalance of autonomic nervous system for Soeumin.

• KDI Journal of Economic Policy
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• v.36 no.2
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• pp.103-136
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• 2014

The covered interest rate parity condition (CIRP) has been widely used in open macroeconomic analysis, risk management, exchange rate forecasts, and so forth. Due to the recent global financial crises, there have been remarkable changes in the financial markets of the emerging markets. These changes possibly influenced the dynamics of the covered interest rate parity condition. In this paper, we investigate whether the CIRP dynamics has changed, and what is the nature of the regime changes. To do this, we propose and estimate multiple-state Markov regime switching models using a Bayesian MCMC method. Our estimation results indicate that the default risk or the deviation from the CIRP has been decreased after the crisis. It seems to be associated with the more active interaction between the short-term bond market and the short-term foreign exchange market than before. The tightened relation of these two financial markets is caused by the arbitrage transaction of foreign investors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.772-780
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• 2008

K-means is one of the simplest unsupervised learning algorithms that solve the clustering problem. However K-means suffers the basic shortcoming: the number of clusters k has to be known in advance. In this paper, we propose extensions of X-means, which can estimate the number of clusters using Bayesian information criterion(BIC). We introduce two different versions of algorithm: modified X-means(MX-means) and generalized X-means(GX-means), which employ one full covariance matrix for one cluster and so can estimate the number of clusters efficiently without severe over-fitting which X-means suffers due to its spherical cluster assumption. The algorithms start with one cluster and try to split a cluster iteratively to maximize the BIC score. The former uses K-means algorithm to find a set of optimal clusters with current k, which makes it simple and fast. However it generates wrongly estimated centers when the clusters are overlapped. The latter uses EM algorithm to estimate the parameters and generates more stable clusters even when the clusters are overlapped. Experiments with synthetic data show that the purposed methods can provide a robust estimate of the number of clusters and cluster parameters compared to other existing top-down algorithms.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.163-170
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• 2019

Over the past decade, the development of the Web explosively increased the data. Feature selection step is an important step in extracting valuable data from a large amount of data. This study proposes a novel opinion mining model based on combining feature selection (FS) methods with Word embedding to vector (Word2vec) and BOW (Bag-of-words). FS methods adopted for this study are CFS (Correlation based FS) and IG (Information Gain). To select an optimal FS method, a number of classifiers ranging from LR (logistic regression), NN (neural network), NBN (naive Bayesian network) to RF (random forest), RS (random subspace), ST (stacking). Empirical results with electronics and kitchen datasets showed that LR and ST classifiers combined with IG applied to BOW features yield best performance in opinion mining. Results with laptop and restaurant datasets revealed that the RF classifier using IG applied to Word2vec features represents best performance in opinion mining.