• KDI Journal of Economic Policy
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• v.27 no.1
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• pp.157-183
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• 2005

Using a multi-sector dynamic stochastic general equilibrium model, we investigate the dynamic effects of a variety of shocks to a small open economy. In particular, we calibrate the model to match the main characteristics of business cycles in Korea and analyze the effects of external shocks: the terms of trade and world real interest rate shocks. Business cycles in Korea more closely follow those of the G7 countries rather than Asian countries. The simulation results suggest that an improvement in the terms of trade has positive impact on investment, output and consumption, while a decrease in the world interest rate has a significant and positive effect on investment. This paper concludes that external shocks significantly influence business cycle fluctuations in Korea.

• Journal of Ecology and Environment
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• v.33 no.1
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• pp.47-57
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• 2010

To understand day-to-day fluctuations in soil moisture content in Seoul, I simulated daily soil moisture content from 1908 to 2009 using long-term climatic precipitation and temperature data collected at the Surface Synoptic Meteorological Station in Seoul for the last 98 years with a hydrological simulation model, BROOK. The output data set from the BROOK model allowed me to examine day-to-day fluctuations and the severity and duration of droughts in the Seoul area. Although the soil moisture content is highly dependent on the occurrence of precipitation, the pattern of changes in daily soil moisture content was clearly quite different from that of precipitation. Generally, there were several phases in the dynamics of daily soil moisture content. The period from mid-May to late June can be categorized as the initial period of decreasing soil moisture content. With the initiation of the monsoon season in late June, soil moisture content sharply increases until mid-July. From the termination of the rainy season in mid-July, daily soil moisture content decreases again. Highly stochastic events of typhoons from late June to October bring large amount of rain to the Korean peninsula, culminating in late August, and increase the soil moisture content again from late August to early September. From early September until early October, another sharp decrease in soil moisture content was observed. The period from early October to mid-May of the next year can be categorized as a recharging period when soil moisture content shows an increasing trend. It is interesting to note that no statistically significant increase in mean annual soil moisture content in Seoul, Korea was observed over the last 98 years. By simulating daily soil moisture content, I was also able to reconstruct drought phenomena to understand the severity and duration of droughts in Seoul area. During the period from 1908 to 2009, droughts in the years 1913, 1979, 1939, and 2006 were categorized as 'severe' and those in 1988 and 1982 were categorized as 'extreme'. This information provides ecologists with further potential to interpret natural phenomenon, including tree growth and the decline of tree species in Korea.

• Earthquakes and Structures
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• v.15 no.3
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• pp.335-350
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• 2018

This paper presents numerical modelling, modal testing, finite element model updating, linear and nonlinear earthquake behavior of a reinforced concrete building model. A 1/2 geometrically scale, two-storey, reinforced concrete frame model with raft base were constructed, tested and analyzed. Modal testing on the model using ambient vibrations is performed to illustrate the dynamic characteristics experimentally. Finite element model of the structure is developed by ANSYS software and dynamic characteristics such as natural frequencies, mode shapes and damping ratios are calculated numerically. The enhanced frequency domain decomposition method and the stochastic subspace identification method are used for identifying dynamic characteristics experimentally and such values are used to update the finite element models. Different parameters of the model are calibrated using manual tuning process to minimize the differences between the numerically calculated and experimentally measured dynamic characteristics. The maximum difference between the measured and numerically calculated frequencies is reduced from 28.47% to 4.75% with the model updating. To determine the effects of the finite element model updating on the earthquake behavior, linear and nonlinear earthquake analyses are performed using 1992 Erzincan earthquake record, before and after model updating. After model updating, the maximum differences in the displacements and stresses were obtained as 29% and 25% for the linear earthquake analysis and 28% and 47% for the nonlinear earthquake analysis compared with that obtained from initial earthquake results before model updating. These differences state that finite element model updating provides a significant influence on linear and especially nonlinear earthquake behavior of buildings.

• Smart Structures and Systems
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• v.14 no.1
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• pp.39-54
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• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• Water for future
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• v.27 no.3
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• pp.45-54
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• 1994

Basic theory of fractal dimension is introduced and performed for the generated time series using the water balance model. The water balance equation over a large area is analyzed at seasonal time scales. In the generation and modification of mesoscale circulation local recycling of precipitation and dynamic effects of soil moisture are explicitly included. Time delay is incorporated in the analysis. Depending on the parameter values, the system showed different senarios in the evolution such as fixed point, limit cycle, and chaotic types of behavior. The stochastic behavior of the generated time series is due to deterministic chaos which arises from a nonlinear dynamic system with a limited number of equations whose trajectories are highly sensitive to initial conditions. The presence of noise arose from the characterization of the incoming precipitation, destroys the organized structure of the attractor. The existence of the attractor although noise is present is very important to the short-term prediction of the evolution. The implications of this nonlinear dynamics are important for the interpretation and modeling of hydrologic records and phenomena.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.2
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• pp.96-115
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• 2007

Background and Purpose: Electroencephalogram(EEG) is a multi-scaled signal consisting of several components of time series with different origins. Recently, because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to chaos theory, irregular signals of EEG can also result from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the correlation dimension. The aim of this study is to analyze correlation between the correlation dimension of EEG and psychological Test (TCI). Methods: Before and after moxibustion treatment, EEG raw data were measured by moving windows during 15 minutes. The correlation dimension(D2) was calculated from stabilized 40 seconds in 15 minutes data. 8 channels EEG study on the Fp, F, T, P was carried out in 30 subjects. Results: Correlation analysis of TCI test is calculated with deterministic non-linear data and stochastic non-linear data. 1. Novelty seeking in temperament is positive correlated with D2 of EEG on Fp. 2. reward dependence in temperament is positive correlated with D2 of EEG on T3,T4 and negative correlated with D2 of EEG on P3,P4. 3. self directedness in character is positive correlated with D2 of EEG on F4, P3. 4. Harm avoidance is negative correlated with D2 of EEG on Fp2, T3, P3. Conclusion: These results suggest that nonlinear analysis of EEG can quantify dynamic state of brain abolut psychological Test (TCI).

• Journal of the Korean Society for Library and Information Science
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• v.52 no.1
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• pp.231-258
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• 2018

This study attempted to identify dynamically changing structure and analyze factors of collaboration. In order to perform this study, 1,631 articles in SCI journals were collected, and 3,898 researchers' information were extracted. To examine the dynamics of collaboration networks, the co-authorship data collected from 2001 to 2015 were divided into three sets, and were analyzed with respect to each period. The results of this study were summed up as: 1) "Co-authorship of the last year" was entirely significant factors while research career was significant only in the period of 2 to 3. 2) It was found that "Influence of the researchers" and "Emergence of the researchers" were significant factors in the period of 2 to 3 and in the period of 1 to 2. 3) "Same institutions", "Same subject", and "Journal similarity" were significant factors in all periods.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.959-967
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• 2008

Disaggregation techniques are widely used to transform observed daily rainfall values into hourly ones, which serve as important inputs for flood forecasting purposes. However, an important limitation with most of the existing disaggregation techniques is that they treat the rainfall process as a realization of a stochastic process, thus raising questions on the lack of connection between the structure of the models on one hand and the underlying physics of the rainfall process on the other. The present study introduces a nonlinear deterministic (and specifically chaotic) framework to study the dynamic characteristics of rainfall distributions across different temporal scales (i.e. weights between scales), and thus the possibility of rainfall disaggregation. Rainfall data from the Seoul station (recorded by the Korea Meteorological Administration) are considered for the present investigation, and weights between only successively doubled resolutions (i.e., 24-hr to 12-hr, 12-hr to 6-hr, 6-hr to 3-hr) are analyzed. The correlation dimension method is employed to investigate the presence of chaotic behavior in the time series of weights, and a local approximation technique is employed for rainfall disaggregation. The results indicate the presence of chaotic behavior in the dynamics of weights between the successively doubled scales studied. The modeled (disaggregated) rainfall values are found to be in good agreement with the observed ones in their overall matching (e.g. correlation coefficient and low mean square error). While the general trend (rainfall amount and time of occurrence) is clearly captured, an underestimation of the maximum values are found.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.101-107
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• 2013

Because forest fires are predicted to increase in severity and frequency under global climate change with important environmental implications, an understanding of fire dynamics is critical for mitigation of these negative effects. For the reason, researchers with different background, such as ecologists, physicists, and mathematical biologists, have developed the simulation models to mimic the forest fire spread patterns. In this study, we suggested a novel model considering the wind effect. Our theoretical forest was comprised of two different tree species with varying probabilities of transferring fire that were randomly distributed in space at densities ranging from 0.0 (low) to 1.0 (high). We then studied the distributional patterns of burnt trees using a two-dimensional stochastic cellular automata model with minimized local rules. We investigated the time, T, that the number of burnt trees reaches 25% of the whole trees for different values of the initial tree density, fire transition probability, and the degree of wind strength. Simulation results showed that the values of T decreased with the increase of tree density, and the wind effect decreased in the case of too high or low tree density. We believe that our model can be a useful tool to explore forest fire spreading patterns.