• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2456-2458
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• 1999

The polarization mode dispersion (PMD) that restricts the transmission bandwidth was investigated in standard long single mode fiber which optimized at 1.3${\mu}m$. Although fiber has perfect circular symmetry, each optical fiber has different refractive index profiles. The investigation of PMD with random mode couplings were conducted in three kinds of fiber by the time-domain interferometric method. By using two manufacturing methods, MCVD(Modified Chemical Vapor Deposition) method and VAD(Vapor Phase Axial Deposition) method, the property of mechanical asymmetric lateral pressure, bending and twisting induced polarization mode dispersion were measured. The concatenated optical fibers were compared with other types.

• Current Optics and Photonics
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• v.2 no.3
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• pp.226-232
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• 2018

We propose a triangular-multicore hollow optical fiber (TMC-HOF) design for uncoupled mode-division and space-division multiplexing. The TMC-HOF has three triangular cores, and each core has three modes: $LP_{01}$ and two split $LP_{11}$ modes. The asymmetric structure of the triangular core can split the $LP_{11}$ modes. Using the proposed structures, nine independent modes can propagate in a fiber. We use a fully vectorial finite-element method to estimate effective index, chromatic dispersion, differential group delay (DGD), and confinement loss by controlling the parameters of the TMC-HOF structure. We confirm that the proposed TMC-HOF shows flattened chromatic dispersion, low DGD, low confinement loss, low core-to-core crosstalk, and low crosstalk between adjacent modes. The proposed TMC-HOF can provide a common platform for MDM and SDM applications.

• Coupled systems mechanics
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• v.6 no.1
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• pp.55-74
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• 2017

The evaluation of torsional effects on multistory buildings remains an open issue, despite considerable research efforts and numerous publications. In this study, a large number of multiple test structures are considered with normally distributed topological attributes, in order to quantify the statistically derived relationships between the torsional criteria and response parameters. The linear regression analysis results, depict that the center of twist and the ratio of torsion (ROT) index proved numerically to be the most reliable criteria for the prediction of the modal rotation and displacements, however the residuals distribution and R-squared derived for the ductility demands prediction, was not constant and low respectively. Thus, the assessment of the torsional parameters' contribution to the nonlinear structural response was investigated using artificial neural networks. Utilizing the connection weights approach, the Center of Strength, Torsional Stiffness and the Base Shear Torque curves were found to exhibit the highest impact numerically, while all the other torsional indices' contribution was investigated and quantified.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.149-159
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• 2022

This study investigated the relationship between economic growth and energy security risk levels in Korea using linear and non-linear ARDL methods. While there are many studies on the relationship between energy consumption and economic growth, few studies focus on the relationship between energy security and economic growth considering 4A dimensions of energy security such as energy availability, accessibility, acceptability, and affordability. Energy risk index from Global Energy Institue and GDP data from world bank are used for ARDL and NARDL analysis. Our result of ARDL shows that there is no long-term relationship between energy security risk levels and economic growth. On the other hand, NARDL result shows that there is an asymmetric relationship between economic growth and energy security risk levels in the long run. The results show the importance of expending further research on ensuring energy security to policymakers.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.5
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• pp.31-40
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• 2002

We propose a novel ultra-short asymmetric vertical directional coupler switch (VDCS) with high extinction ratios larger than 30㏈ composed of switching operation induced section (SOIS), extinction ratio adjusted section (ERAS), and extinction ratio enhanced section (ERES). In this VDCSs, switching operation is achieved by changing the refractive index of one core in SOIS. The improvement of extinction ratios larger than 30㏈ for both cross and bar states is achieved by controlling the asymmetry of refractive indices between both cores in ERES. After propagating through ERAS with symmetry in the structure, different extinction ratios between cross and bar states at the end of SOIS are changed to the same value. For this reason, the optimum asymmetry of the refractive indices of cores to have the maximum extinction ratios and the lengths of ERES are the same for cross and bar states. Design guidelines to achieve high extinction ratios with large tolerances are presented.

• Journal of Korean Neurosurgical Society
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• v.47 no.1
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• pp.1-6
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• 2010

Objective: On the basis of preoperative computed tomography (CT) scans, we studied the change of the size of anterior primary division (APD) of the L5 spinal root in the presence of foraminal/extraforaminal entrapment of the L5 spinal root. Methods: Two independent radiologists retrospectively reviewed the preoperative CT scans of 27 patients treated surgically and compared the sizes of the APDs on bilateral L5 spinal roots. If one side APO size was larger than the other side APD size, it was described as left or right "dominancy" and regarded this as "consensus (C)" in case that there was a consensus between the larger APD and the location of sciatica, and regarded as "non-consensus (NC)" in case that there was not a consensus. Oswestry Disability Index (ODI) scores were used for preoperative and postoperative evaluation. Results: On CT scans, twenty-one (77%) of 27 patients were the consensus group (APD swelling) and 6 (22%) were a non-consensus group (APD no swelling). In 9 patients with acute foraminal disc herniations, asymmetric enlargement of the APD on L5 spinal root was detected in all cases (100%) and detected in 11 (64%) of 17 patients with stenosis. Preoperative ODI score was 75-93 (mean 83) and postoperative 001 scores were improved to 13-36 (mean 21). The mean follow-up period was 6 months (range, 3-11 months). Conclusion: An asymmetric enlargement of the APD on L5 spinal root on CT scans is meaningfully associated with a foraminal or extraforaminal entrapment of the L5 spinal root on the lumbosacral junction.

• Korean Journal of Optics and Photonics
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• v.24 no.2
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• pp.64-70
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• 2013

In this paper, two white light emitting diodes(LEDs) were manufactured by using two kinds of yellow phosphor, YAG:Ce and $(Sr,Ba)_2SiO_4:Eu$, and their spectroscopic properties were compared and analyzed. We found that the asymmetric double sigmoidal function can be applied to both white LEDs to obtain the center wavelength, the half width, and the skewness parameters. According to this analysis, the half width of the emitting spectrum of silicate phosphor was smaller than that of YAG phosphor, indicating smaller color rendering index. However, the silicate phosphor exhibited better color stability depending on the driving current than the YAG phosphor. The current dependence of the luminous efficacy of both white LEDs was investigated, which showed that efficacy decreased monotonically with current. The efficacy of the silicate-based white LED was lower than that of the YAG-based LED by about 10~12 lm/W.

• Journal of Ocean Engineering and Technology
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• v.32 no.6
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• pp.419-426
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• 2018

Recently, in an effort to reduce the energy efficiency design index (EEDI), studies on energy saving devices (ESDs) have been conducted. In this study, we designed a post-device suitable for a KRISO container ship (KCS) using computational fluid dynamics (CFD). In order to increase the efficiency of the post-device, a twisted rudder was used, which has a proven performance (showing a 1.34% reduction in DHP compared to the bare hull at 24 knots) in previous research at Pusan National University. In addition, an increase in efficiency was expected by the use of a rudder bulb, including the discontinuous section of the twisted rudder and a divergent propeller cap to prevent the contraction of the wake. The optimization criterion was the case where the delivery power was the least compared with the bare hull. We analyzed the cause of the efficiency increase through an analysis of the self-propulsion factor. The case study for optimization was divided into 4 types (1. clearance of the bulb and cap, 2. shape of the bulb, 3. size of the bulb and cap, and 4. asymmetric bulb). Finally, with a clearance of 50 mm from the ship, a spherical bulb with the cap having an angle of $5^{\circ}$, and an asymmetric rudder bulb with a bulb diameter of 1.2HH/1.4H (horizontal/vertical) showed a 2.05% reduction in DHP compared to the bare hull at 24 knots. We will fabricate a post-device that will be optimized in the future and verify the performance of the post-device through model tests.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.157-162
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• 2023

A highly sensitive refractive index bio-sensor based on grating-assisted strip directional coupler (GASDC) is proposed. The sensor is designed using two asymmetric strip waveguides with a top-loaded grating structure in one of the waveguides. Maximum light couples from one waveguide to the other at the resonance wavelength satisfying phase-matching condition (PMC), and it shows that the change in phase-matching condition with the change in refractive index of the analyte medium in the cover region can be used as a measure of the sensitivity. The proposed sensor will be an on-chip device with a high refractive index sensitivity, and the sensor configuration offers a low propagation loss, thereby enhancing the sensitivity. Furthermore, variation of the sensitivity with the waveguide parameters of sensor is evaluated to optimize the design.

• 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.