• Journal of the Korean Society for Marine Environment & Energy
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• v.11 no.1
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• pp.13-23
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• 2008

In coastal region, eutrophication, Do deficit and red tide are frequently occurred by influx of fresh water. When the fresh water containing pollutants is discharged into the sea, the surrounding water is contaminated by dispersion of freshwater flowing into coastal waters. The prediction and analysis about the dispersion process of the discharged fresh water should be conducted. A modeling system using GUI was developed to simulate hydrodynamic flow and fresh water dispersion in coastal waters and to analyze the results efficiently. The modeling module of the system includes a tide model using a finite element method and a fresh water dispersion model using a particle-tracking method. This system was applied to predict the tidal currents and fresh water dispersion in Mokpo coastal zone. To verify accuracy of the hydrodynamic model, the simulation results were compared with observed sea level and time variations of tidal currents showing a good agreement. The fresh water dispersion was verified with observed salinity distribution. The dispersion model also was verified with analytic solutions with advection-diffusion problems in 1-dimensional and 2-dimensional simple domain. The system is operated on GUI environment, to ease the model handling such as inputting data and displaying results. Therefore, anyone can use the system conveniently and observe easily and accurately the simulation results by using graphic functions included in the system. This system can be used widely to decrease the environmental disaster induced by inflow of fresh water into coastal waters.

• Journal of the Korean Society for Marine Environment & Energy
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• v.15 no.3
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• pp.186-197
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• 2012

In order to understand hydrodynamic and water quality changes on the Saemangeum reservoir in accordance to inner development plan, intensive numerical simulations using EFDC have been done. Due to inner dike construction and proposed dredging plans, stratification might occur and yield flow field change. It should be noticed that very conditional gate operation schedule adjusting target water elevation of -1.5 meter causes severe stratification and hence plays an important role in poor water qualities. By using random walk particle tracking residence simulations, it is found that hydrodynamic characteristics depends greatly on riverine inflow conditions. It is also inferred that the northern part of the Mangyeong reservoir behaves as a dead zone and acts as major reasoning of water quality deterioration owing to benthic flux from long-term residing settled sediment.

• Economic Analysis
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• v.27 no.2
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• pp.1-40
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• 2021

Using an unobserved components model that features trend growth as a random walk, we find that GDP trend growth rates had gradually declined from the late 1980s to early 2010s in Korea. To uncover the underlying features of the slowdown, we use trend growth accounting. A major feature appears to be a significant decline in the growth rate of labor productivity. To be specific, the first gradual decline in trend growth, which started in 1988 and continued to 1998, is associated with a drop in TFP measured in labor-augmenting units. This finding is inconsistent with the hypothesis that the slowdown in GDP trend growth can be attributed to the 1997-1998 Korean financial crisis. Sluggish investment growth is behind the second period of the gradual slowdown, from 2002 to 2012.

• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.149-181
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• 2004

In this study we perform empirical tests using KOSPI return to investigate the existence of nonlinear characteristics in the generating process of stock returns. There are three categories in empirical tests; the test of nonlinear dependence, nonlinear stochastic process and nonlinear deterministic chaos. According to the analysis of nonlinearity, stock returns are not normally distributed but leptokurtic, and appear to have nonlinear dependence. And it's decided that the nonlinear structure of stock returns can not be completely explained using nonlinear stochastic models of ARCH-type. Nonlinear deterministic chaos system is the feedback system, which the past incidents influence the present, and it is the fractal structure with self-similarity and has the sensitive dependence on initial conditions. To summarize the results of chaos analysis for KOSPI return, it is the persistent time series, which is not IID and has long memory, takes biased random walk, and is estimated to be fractal distribution. Also correlation dimension, as the approximation of fractal dimension, converged stably within 3 and 4, and maximum Lyapunov exponent has positive value. This suggests that chaotic attractor and the sensitive dependence on initial conditions exist in stock returns. These results fit into the characteristics of chaos system. Therefore it's decided that the generating process of stock returns has nonlinear deterministic structure and follow chaotic process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.420-426
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• 2018

The purpose of this paper is to examine the business cycle in the Jeju region and what differences exist in relation to the nation as a whole, to calculate the relative importance between the random walk stochastic trend and cyclical factor, and to find out its causes and implications. Results of empirical analysis found that the characteristics of the business cycle in the Jeju region were as follows: First, the Jeju region, which is likely to have a growth component of the economy such as technological development and the accumulation of capital, was projected to have a possibility of high growth due to a greater proportion of the stochastic trend factor(46.8%) than the entire country(27.8%). Secondly, employment fluctuation in Jeju, which varies from 0.007 to 0.058 depending on the model, was lowest compared to the fluctuation of other indicators. The employment market in Jeju remained firm, showing that it is not smooth enough to create new jobs despite the production growth in industry. Third, the tourism industry was acting as a stabilizing factor, whereas the mining and manufacturing production was the opposite of tourism industry. This implies that the mining and manufacturing production was based on a weak foundation.

• Knowledge Management Research
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• v.22 no.4
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• pp.119-133
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• 2021

As a large amount of data is produced in each industry, a number of time series pattern prediction studies are being conducted to make quick business decisions. However, there is a limit to predicting specific patterns in nonlinear time series data due to the uncertainty inherent in the data, and there are difficulties in making strategic decisions in corporate management. In addition, in recent decades, various studies have been conducted on data such as demand/supply and financial markets that are suitable for industrial purposes to predict time series data of irregular random walk models, but predict specific rules and achieve sustainable corporate objectives There are difficulties. In this study, the prediction results were compared and analyzed using the Chaos analysis method for roulette data and financial market data, and meaningful results were derived. And, this study confirmed that chaos analysis is useful for finding a new method in analyzing time series data. By comparing and analyzing the characteristics of roulette games with the time series of Korean stock index future, it was derived that predictive power can be improved if the trend is confirmed, and it is meaningful in determining whether nonlinear time series data with high uncertainty have a specific pattern.