• Journal of Korean Society of Transportation
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• v.35 no.1
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• pp.1-10
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• 2017

The compact city usually provides good accessibility of residents with multiple transportation modes. However, in a compact city, annual average of travel distance per household by car is relatively short due to more congested traffic condition and larger travel cost than disperse city. As a result, total travel demand is decreasing when the region becomes more compact. Therefore compact development is regarded as one of the sustainable choices for future urban planning in many countries. This study aims at an empirical analysis of the relationship between urban compactness and travel demand based upon land-use and travel data for city of Seoul. In this study, 424 sub-districts with the mixed land-use patterns are assessed in a hexagonal diagram. The measurement is based on the relative deviation of each sector's characteristics including numbers of residence, manufacture, and trade & service. Multiple linear regression models are developed to analyze the effects of urban compactness on zonal trip generations. As a result, the trip generation rate in the residence-intensive and mixed-use areas is found to be relatively low. Furthermore, residents in high-compact areas tend to use public transport more often than residents in less compact areas.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.1
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• pp.29-34
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• 2022

In this paper, the floor acceleration for the seismic design of non-structural elements was evaluated using the core shape as a planar variable. Linear time history analysis using 20 models with 5 different planes and 4 different floors on each plane depending on the change in the shape (position and specific gravity) of the core in the square biaxially symmetric plane was performed. The analysis confirmed that the torsional amplification of the floor acceleration was up to 1.7 times in the plane subjected to eccentricity depending on the position of the core, and the effect of torsion was the greatest in the middle floor of the structure. In a plane where only the specific gravity of the core was changed without eccentricity, when the period was less than 0.4694 s, the maximum floor acceleration decreased in the lower floors and increased in the upper floors as the period increased. Conversely, when the period was 0.4694 s or more, it was confirmed that the floor acceleration increased in the lower part and decreased in the upper part as the period increased.

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.221-228
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• 2008

To estimate array shape with reference sources in SONAR systems, nearfield signal modeling is required for the reference sources near a towed array. Array shape estimation method based on the nearfield signal modeling generally exploits the spatial covariance matrix of the received reference sources. Among those method, nearfield eigenvector method uses the eigenvector corresponding to the maximum eigenvalue as a steering vector of the reference source. In this paper, we propose a simplified subspace fitting method based on the nearfield signal modeling with spherical wave modeling. Furthermore, we analyze performance of the array shape estimation methods based on the nearfield signal modeling for various environments. The results of the numerical experiments indicate that the simplified subspace fitting method and the nearfield eigenvector method with single reference source shows almost similar performance. Furthermore, the simplified subspace fitting method with 2 reference sources consistently estimates the shape of the array regardless of the incident angle of the reference sources, whereas the nearfield eigenvector method cannot apply for the case of 2 reference sources.

• Journal of the Korean Geotechnical Society
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• v.15 no.4
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• pp.113-132
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• 1999

Recently in Korea, application of the soil nailing is gradually extended to the sites of excavations and slopes having various ground conditions and field characteristics. Design of the soil nailing is generally carried out in two steps, The First step is to examine the minimum safety factor against a sliding of the reinforced nailed-soil mass based on the limit equilibrium approach, and the second step is to check the maximum displacement expected to occur at facing using the numerical analysis technique. However, design parameters related to the soil nailing system are so various that a reliable design method considering interrelationships between these design parameters is continuously necessary. Additionally, taking into account the anisotropic characteristics of in-situ grounds, disturbances in collecting the soil samples and errors in measurements, a systematic analysis of the field measurement data as well as a rational technique of the optimum design is required to improve with respect to economical efficiency. As a part of these purposes, in the present study, a procedure for the optimum design of a soil nailing excavation wall system is proposed. Focusing on a minimization of the expenses in construction, the optimum design procedure is formulated based on the genetic algorithm. Neural network theory is further adopted in predicting the maximum horizontal displacement at a shotcrete facing. Using the proposed procedure, various effects of relevant design parameters are also analyzed. Finally, an optimized design section is compared with the existing design section at the excavation site being constructed, in order to verify a validity of the proposed procedure.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Radiation Oncology Journal
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• v.26 no.3
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• pp.189-194
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• 2008

Purpose: We designed a water-based bolus device for radiation therapy in Kaposi's sarcoma. This study evaluated the usefulness of this new device and compared it with the currently used rice-based bolus. Materials and Methods: We fashioned a polystyrene box and cut a hole in order to insert patient's extremities while the patient was in the supine position. We used a vacuum-vinyl based polymer to reduce water leakage. Next, we eliminated air using a vacuum pump and a vacuum valve to reduce the air gap between the water and extremities in the vacuum-vinyl box. We performed CT scans to evaluate the density difference of the fabricated water-based bolus device when the device in which the rice-based bolus was placed directly, the rice-based bolus with polymer-vinyl packed rice, and the water were all put in. We analyzed the density change with the air gap volume using a planning system. In addition, we measured the homogeneity and dose in the low-extremities phantom, attached to six TLD, and wrapped film exposed in parallel-opposite fields with the LINAC under the same conditions as the set-up of the CT-simulator. Results: The density value of the rice-based bolus with the rice put in directly was 14% lower than that of the water-based bolus. Moreover, the value of the other experiments in the rice-based bolus with the polymer-vinyl packed rice showed an 18% reduction in density. The analysis of the EDR2 film revealed that the water-based bolus shows a more homogeneous dose plan, which was superior by $4{\sim}4.4%$ to the rice-base bolus. The mean TLD readings of the rice-based bolus, with the rice put directly into the polystyrene box had a 3.4% higher density value. Moreover, the density value in the case of the rice-based bolus with polymer-vinyl packed rice had a 4.3% higher reading compared to the water-based bolus. Conclusion: Our custom-made water-based bolus device increases the accuracy of the set-up by confirming the treatment field. It also improves the accuracy of the therapy owing to the reduction of the air gap using a vacuum pump and a vacuum valve. This set-up represents a promising alternative device for delivering a homogenous dose to the target volume.

• Journal of Bio-Environment Control
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• v.29 no.2
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• pp.161-170
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• 2020

There is systematic spatial variations in environmental properties due to sensitive reaction to external conditions at plastic greenhouse occupied 99.2% of domestic agricultural facilities. In order to construct 3 dimensional distribution of temperature, relative humidity, CO₂ and illuminance, measurement matrix as 3 by 3 by 5 in direction of width, height and length, respectively, dividing indoor space of greenhouse was designed and tested at experimental site. Linear regression analysis was conducted to evaluate optimal estimation method in terms with horizontal and vertical variations. Even though sole measurement point for temperature and relative humidity could be feasible to assess indoor condition, multiple measurement matrix is inevitably required to improve spatial precision at certain time domain such as period of sunrise and sunset. In case with CO₂, multiple measurement matrix could not successfully improve the spatial predictability during a whole experimental period. In case with illuminance, prediction performance was getting smaller after a time period of sunrise due to systematic interference such as indoor structure. Thus, multiple sensing methodology was proposed in direction of length at higher height than growing bed, which could compensate estimation error in spatial domain. Appropriate measurement matrix could be constructed considering the transition of stability in indoor environmental properties due to external variations. As a result, optimal measurement matrix should be carefully designed considering flexibility of construction relevant with the type of property, indoor structure, the purpose of crop and the period of growth. For an instance, partial cooling and heating system to save a consumption of energy supplement could be successfully accomplished by the deployment of multiple measurement matrix.