• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.303-309
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• 2004

In this paper, an adaptive Bayesian approach to image segmentation was developed for boundary detection. Both image intensities and texture information were used for obtaining better quality of the image segmentation by using the C programming language. Fuzzy c-mean clustering was applied fer the conditional probability density function, and Gibbs random field model was used for the prior probability density function. To simply test the algorithm, a synthetic image (256$\times$256) with a set of low gray values (50, 100, 150 and 200) was created and normalized between 0 and 1 n double precision. Results have been presented that demonstrate the effectiveness of the algorithm in segmenting the synthetic image, resulting in more than 99% accuracy when noise characteristics are correctly modeled. The algorithm was applied to the Antarctic mosaic that was generated using 1963 Declassified Intelligence Satellite Photographs. The accuracy of the resulting vector map was estimated about 300-m.

• Earthquakes and Structures
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• v.2 no.4
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• pp.357-376
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• 2011

Ground motion models predict the mean and standard deviation of the logarithm of spectral acceleration, as a function of predictor variables such as earthquake magnitude, distance and site condition. Such models have been developed for a variety of seismic environments throughout the world. Some calculations, such as the Conditional Mean Spectrum calculation, use this information but additionally require knowledge of correlation coefficients between logarithmic spectral acceleration values at multiple periods. Such correlation predictions have, to date, been developed primarily from data recorded in the Western United States from active shallow crustal earthquakes. This paper describes results from a study of spectral acceleration correlations from Japanese earthquake ground motion data that includes both crustal and subduction zone earthquakes. Comparisons are made between estimated correlations for Japanese response spectral ordinates and correlation estimates developed from Western United States ground motion data. The effect of ground motion model, earthquake source mechanism, seismic zone, site conditions, and source to site distance on estimated correlations is evaluated and discussed. Confidence intervals on these correlation estimates are introduced, to aid in identifying statistically significant differences in correlations among the factors considered. Observed general trends in correlation are similar to previous studies, with the exception of correlation of spectral accelerations between orthogonal components, which is seen to be higher here than previously observed. Some differences in correlations between earthquake source zones and earthquake mechanisms are observed, and so tables of correlations coefficients for each specific case are provided.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.17 no.3
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• pp.178-187
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• 2005

A reliability analysis model f3r studying the influence of joint distribution of wave heights and periods on wave un-up is presented in this paper. From the definition of failure mode related to wave run-up, a reliability function may be formulated which can be considered uncertainties of water level. In particular, the reliability analysis model can be directly taken into account statistical properties and distributions of wave periods by considering wave period in the reliability function to be a random variable. Also, variations of wave height distribution conditioned to mean wave periods can be taken into account correctly. By comparison of results of additional reliability analysis using extreme distributions with those resulted from joint distribution of wave height and periods, it is found that probabilities of failure evaluated by the latter is larger than those by the former. Although the freeboard of sloped-breakwater structures can be determined by extreme distribution based on the long-term measurements, it may be necessary to investigate additionally into wave run-up by using the present reliability analysis model formulated to consider joint distribution of a single storm event. In addition, it may be found that the effect of spectral bandwidth parameter on reliability index may be little, but the effect of wave height distribution conditioned to mean wave periods is straightforward. Therefore, it may be confirmed that effects of wave periods on the probability of failure of wave run-up may be taken into account through the conditional distribution of wave heights. Finally, the probabilities of failure with respect to freeboard of sloped-breakwater structures can be estimated by which the rational determination of crest level of sloped-breakwater structures may be possible.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.

• Korean Journal of Culture and Social Issue
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• v.29 no.4
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• pp.455-476
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• 2023

This study focused on the characteristics of motiveless crimes that mainly originated from interpersonal problems and were acts of revenge against innocent third parties. This study confirmed the relationship between the experience of social exclusion and displaced aggression and examined the relationship between the two variables. We sought to confirm the role of related factors such as stress and social support. For this purpose, we established and tested hypotheses about the mediatingon effect of stress and the moderated mediatingon effect of social support on the effect of social exclusion experience on displaced aggression among 353 adult males aged between 19 and 49 years. The main results are that, first, social exclusion had a positive effect on displaced aggression. Second, stress was found to partially mediate the relationship between social exclusion and displaced aggression. Third, the hypothesis that social support would moderate the mediating effect of stress was not provedvaild, but the conditional direct effect of social support was confirmed in the mediation model. In other words, social support did not affect the indirect effect mediated by stress, but appeared to moderate the direct effect between social exclusion and displaced aggression. Social exclusion's prediction of displaced aggression was significant only in the average social support group (mean) and the high group (M+1SD), and appeared to increase as the group increased. This means that in groups with high social support, displaced aggression is used as a stress control strategy, which is a different result from previous studies that found that social support plays a role in lowerings aggression. People with low levels of social support showed unexpected results in that they used displaced aggression less frequently despite their experiencinge of social exclusion. In the discussion, the social implications of these results were interpreted, and additional research ideas were proposed to specify the relationship between social exclusion and displaced aggression.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.49-67
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• 2006

This study examines whether won/dollar futures have price discovery function and volatility spillover effect or not, using intraday won/dollar futures prices, volumes, and spot rates for the interval from March 2, 2005 through May 30, 2005. Futures prices and spot rates are non-stationary, but there is the cointegration relationship between two time series. Futures returns, spot returns, and volumes are stationary. Asymmetric effects on volatility in futures returns and spot returns does not exist. Analytical results of mean equations of the BGARCH-EC (bivariate GARCH-error correction) model show that the increase of futures returns raise spot returns after 5 minutes, which implies that futures returns lead spot returns and won/dollar futures have price discovery function. In addition, the long-run equilibrium relationship between the two returns could help forecast spot returns. Analytical results of variance equations indicate that short-run innovations in the futures market positively affect the conditional variances of spot returns, that is, there is the volatility spillover effect in the won/dollar futures market. A dummy variable of volumes does not have an effect on two returns but influences significantly on two conditional variances.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.233-239
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• 2006

Most research for until at now link travel time were research for mean link travel time calculate or estimate which uses the average of the individual vehicle. however, the link travel time distribution is divided caused by with the impact factor which is various traffic condition, signal operation condition and the road conditional etc. preceding study result for link travel time distribution characteristic showed that the patterns of going through traffic were divided up to 2 in the link travel times. therefore, it will be more accurate to divide up the link travel time into the one involving delay and the other without delay, rather than using the average link travel time in terms of assessing the traffic situation. this study is it analyzed transit hour distribution characteristic and a cause using examine to the variables which give an effect at link travel time distribute using simulation program and determinate link travel time distribute ratio estimation model. to assess the distribution of the link travel times, this research develops the regression model and the fuzzy model. the variables that have high level of correlations in both estimation models are the rest time of green ball and the delay vehicles. these variables were used to construct the methods in the estimation models. The comparison of the two estimation models-fuzzy and regression model- showed that fuzzy model out-competed the regression model in terms of reliability and applicability.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.6
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• pp.635-641
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• 2010

Time-varying channel characteristics in OFDM systems over doubly selective channels cause inter-carrier interferences(ICI) in the frequency domain. Time domain windowing gives rise to restriction on the bandwidth of the frequency domain channel matrix and makes it possible to approximate the OFDM system as a simplified linear input-output model. When successive interference cancellation based on linear MMSE estimation is employed for channel equalization in OFDM systems, symbol detection ordering produces considerable effects on overall system performances. In this paper, we show the reduction of the residual ICI by time domain windowing and the resultant performance improvements, and investigate the effects of SINR- and CSEP-based symbol detection ordering on the performance of successive interference cancellation.

• 대한예방의학회:학술대회논문집
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• 1994.02a
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• pp.651-657
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• 1994

To assess quantitatively the association between benzene exposure and leukemia, we examined the mortality rate of a cohort with occupational exposure to benzene. Cumulative exposure for each cohort member was estimated from historical air-sampling data and, when no sampling data existed, from interpolation on the basis of existing data. The overall standardized mortality ratio (a measure of relative risk multiplied by 100) for leukemia was 337 (95 percent confidence interval, 154 to 641), and that for multiple myeloma was 409 (95 percent confidence interval, 110 to 1047). With stratification according to levels of cumulative exposure, the standardized mortality ratios for leukemia increased from 109 to 322, 1186, and 6637 with increases in cumulative benzene exposure from less than 40 parts per million-years (ppm-years), to 40 to 199, 200 to 399, and 400 or more. respectively. A cumulative benzene exposure of 400 ppm years is equivalent to a mean annual exposure of 10 ppm over a 40-year working lifetime; 10 ppm is the currently enforceable standard in the United States for occupational exposure to benzene. To examine the shape of the exposure-response relation, we performed a conditional logistic-regression analysis, in which 10 controls were matched to each cohort member with leukemia. From this model, it can be calculated that protection from benzene induced leukemia would increase exponentially with any reduction in the permissible exposure limit.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2555-2564
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• 2000

In this paper, a new unsupervised image segmentation algorithm is proposed. To model the contextual information presented in images, the characteristics of the Markov random fields (MRF) are utilized. Textured images are modeled as realizations of the stationary Gaussian MRF on a two-dimensional square lattice using the conditional autoregressive (CAR) equations with a second-order noncausal neighborhood. To detect boundaries, hypothesis tests over two masked areas are performed. Under the hypothesis, masked areas are assumed to belong to the same class of textures and CAR equation parameters are estimated in a minimum-mean-square-error (MMSE) sense. If the hypothesis is rejected, a measure of dissimilarity between two areas is accumulated on the rejected area. This approach produces potential edge maps. Using these maps, boundary detection can be performed, which resulting no micro edges. The performance of the proposed algorithm is evaluated by some experiments using real images as weB as synthetic ones. The experiments demonstrate that the proposed algorithm can produce satisfactorY segmentation without any a priori information.