• Journal of the Korean GEO-environmental Society
• /
• v.24 no.12
• /
• pp.61-67
• /
• 2023

Heat pipes located underground in urban areas and operated under high temperature and pressure conditions can cause large-scale human and economic damage if damaged. In order to predict damage in advance, damage and construction information of heat pipe are analyzed to derive independent variables that have a correlation with frequency of damage, and a simple regression analysis modified model using each variable is applied to the field. However, as the correlation between independent variables applied to the model increases, the independence between variables is harmed and the reliability of the model decreases. In this study, the independence of the pipe diameter, burial depth, insulation level of monitoring system, and disconnection or short circuit of the detection line, which are judged to be interrelated, was tested to derive a method for combining variables and setting categories necessary to apply to the frequency of damage estimation model. For the test of independence, the continuous variables pipe diameter and burial depth were each converted into three categories, insulation level of monitoring system was converted into two categories, and the categorical variable disconnection or short circuit of the detection line status was kept as two categories. As a result of the test of independence, p-value between pipe diameter and burial depth, level of monitoring system and disconnection or short circuit of the detection line was lower than the significance level (α = 0.05), indicating a large correlation between them. Therefore, the pipe diameter and burial depth were combined into one variable, and the categories of the combined variable were set to 9 considering the previously set categories. The insulation level of monitoring system and the disconnection or short circuit of the detection line were also combined into one variable. Since the insulation level is unreliable when the detection line status is disconnection or short circuit, the categories of the combined variable were set to 3.

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

• Investigative Magnetic Resonance Imaging
• /
• v.17 no.2
• /
• pp.133-143
• /
• 2013

Purpose : To evaluate and compare the accuracy of magnetic resonance imaging (MRI) and ultrasound (US) for detection and estimation of invasion depth of colorectal carcinoma (CRC) by correlation with histopathologic findings in vitro, and to find out the best MR pulse sequence for accurate delineation of tumor from surrounding normal tissue. Materials and Methods: Resected specimens of CRC from 45 patients were examined about tumor detectability and invasion depth of US using high frequency (5-17 MHz) linear transducer in a tube filled with normal saline and MRI in a 8-channel quadrate head coil. The institutional review board approved this study and informed consent was waived. MRI with seven pulse sequences of in- and out-of-phases gradient echo T1 weighted images, fast spin echo T2 weighted image and its fat suppression image, fast imaging employing steady-state acquisition (FIESTA) and its fat suppression image, and diffusion weighted image (DWI) were performed. In each case, both imaging findings of MRI and US were evaluated independently for detection and estimation of invasion depth of tumor by consensus of two radiologists and were compared about diagnostic accuracy according to the histopathologic findings as reference standard. Seven MR pulse sequences were evaluated on the point of accurate delineation of tumor from surrounding normal tissue in each specimen. Results: In specimens of CRC, both imaging modalities of MRI (91.1%) and US (86.7%) showed relatively high diagnostic accuracy to detect tumor and evaluate invasion depth of tumor. In early CRC, diagnostic accuracy of US was 87.5% and that of MRI was 75.0%. There was no statistically significant difference between two imaging modalities (p > 0.05). The best pulse sequence among seven MR sequences for accurate delineation of tumor from surrounding normal tissue in each specimen of CRC was fast spin echo T2 weighted image. Conclusion: MRI and US show relatively high diagnostic accuracy to detect tumor and evaluate invasion depth of resected specimen of CRC. The most excellent pulse sequence of MRI for accurate delineation of tumor from surrounding normal tissue in CRC is fast spin echo T2 weighted image.

• Journal of Korean Society of Transportation
• /
• v.24 no.1 s.87
• /
• pp.29-38
• /
• 2006

After the first opening of the KTX in April 2004, travel time between major cities has been dramatically reduced. The reduction rates range from 32% to 47%. Considering travel time reduction between major cities, this study concerned about the intercity travel impact of the KTX operation. This study aimed to analyze intercity mode choice behavior of Daegu Citizens according to the first opening of the KTX. This study takes place in two sections. These are (i) the section of KTX between Daegu and Seoul, and (ii) the section of KTX between Daegu and Daejeon. This study estimated empirical models for analyzing intercity mode choice behavior according to the first opening of the KTX. This study makes use of the data from travel survey from Daegu metropolitan area. The main part of the survey was carried out in the KTX Dong-Daegu station. The survey data includes the information on travel from Daegu to Daejeon and from Daegu to Seoul. In order to analyze intercity choice behavior according to the frist opening of the KTX, multinomial model structure is used. For the model specification, a variety of behavioral assumptions about the factors which affect the mode choice, were considered. From the empirical model estimation, it is found that OVTT(Out-of-Vehicle Travel Time), OVTC(Out-of-Vehicle Travel Cost), IVTT(In-Vehicle Travel Time), IVTC(In-Vehicle Travel Cost), travel frequency, travel purpose, sex, age, occupation. household income, individual income are significant in choosing intercity travel mode. However, it is found that the intercity nde choice behavior is different between (i) the section of KTX between Daegu and Seoul, and (ii) the section of KTX between Daegu and Daejeon. Furthermore, some policy implications are discussed in conclusion.

• Journal of Korea Water Resources Association
• /
• v.40 no.9
• /
• pp.697-707
• /
• 2007

In this study, we estimated the PMP(Probable Maximum Precipitation) and its transition in case of the typhoon Rusa which happened the biggest damage of all typhoons in the Korea. Specially, we analysed the moisture maximizing rate under the consideration of meteorological condition based on the orographic property when it hits in Gangneung region. The PMP is calculated by the rate of the maximum persisting 12 hours 1000 hPa dew points and representative persisting 12 hours 1000 hPa dew point. The former is influenced by the moisture inflow regions. These regions are determined by the surface wind direction, 850 hPa moisture flux and streamline, which are the critically different aspects compared to that of previous study. The latter is calculated using statistics program (FARD2002) provided by NIDP(National Institute for Disaster Prevention). In this program, the dew point is calculated by reappearance period 50-year frequency analysis from 5% of the level of significant when probability distribution type is applied extreme type I (Gumbel distribution) and parameter estimation method is used the Moment method. So this study indicated for small basin$(3.76km^2)$ the difference the PMP through new method and through existing result of established storm transposition and DAD(Depth-Area-Duration). Consequently, the moisture maximizing rate is calculated in the moisture inflow regions determined by meteorological fields is higher $0.20{\sim}0.40$ range than that of previous study. And the precipitation is increased $16{\sim}31%$ when this rate is applied for calculation.

• Journal of Oral Medicine and Pain
• /
• v.26 no.4
• /
• pp.377-393
• /
• 2001

In order to study the closure stage of cranial sutures and its correlations with age, the ectocranial closure stage of coronal suture, sagittal suture, and lambdoidal suture of 67 skulls was measured. Among the skulls kept at the department of anatomy, college of medicine, Yonsei University, the ones with ages identified were used for this study. These measurements of suture closure were conducted by 4 examiners independently. The sutures were further divided by Frederic's method into 16 suture parts. The closure stages were classified by five stages of Broca-Ribbe. The following results were obtained: 1. The inter-observer reliability among 4 examiners showed high intraclass correlation coefficient of over 0.75(mean : 0.856) in all suture parts. Therefore, the determination of closure stage wasn't influenced by the subjective view of each examiner. 2. In all suture parts, the closure stage increased proportionally with age.(p<0.01) In terms of each suture part, the S2 part of sagittal suture showed the highest correlation(68.1%) while the L1-R part of lambdoidal suture showed the lowest correlation(51.3%). In addition, in terms of suture types, the correlation with age decreased in the order of sagittal suture(60.0%), coronal suture(57.7%), and lambdoidal suture (55.7%). In general, the average value of suture closure stages had 57.8% correlation with age(p<0.01). 3. The most frequent suture closure stage according to age group was '0' for ages below 30, '0' and '1' for ages within the 30's, '1' and '2' for ages within the 40's, and '2' for ages within the 50's. With older age groups, the frequency of '3' and '4' increased, and the suture closure stage increased proportionally with age. 4. The mean age by closure stage of each suture were within the 40's for the closure stage of '1', within the 50's for the closure stage of '2', and from 50's through 60's for the closure stage of '3'. The standard deviation was over 10 for all closure stages. In addition, at the same suture closure stage, the mean age according to the coronal suture was higher than the ages according to the sagittal suture or lambdoidal suture. Especially, C1-R, C1-L, C2-R, and C2-L parts showed the highest age when at the same suture closure stage. 5. The values appropriate for age estimations using suture closure stages of 16 suture parts were calculated, and a calculator for age estimation ($R^2=0.6944$, p<0.01) by ectocranial suture closure stage for Koreans is presented. From the above results, the method of using the closure stage of sutures of the skull to estimate age can be useful in individual identification of forensic science. Further extensive and accurate research using larger samples would be worthy of study.

• Journal of Korea Water Resources Association
• /
• v.44 no.10
• /
• pp.787-795
• /
• 2011

Extreme water events such as heavy rainfalls due to recent climate change are continually increasing and their scale has also shown an increasing trend. To overcome these natural disasters, this policy study suggests securing lateral river space as an effective method for extreme flood. To support the importance of restoration and expansion of lateral river space, Gumi upstream region of the Nakdong River basin was chosen as a target area and flood reduction analysis of the washland by using LISFLOOD model have been examined. The 500-year frequency flood was simulated for the estimation of possibly occurable flood level and it turns out that the secured lateral river space on the selected site effectively lowers about 0.53 m flood level and reduces the flood damage of the city on the lower reaches of the river. In addition, based on this result, multilateral river space securing plans were compared, and conservation easement and natural disaster insurance were suggested for sustainable and cost-effective alternatives. The costs of land purchase and conservation easement for securing the river space were also compared.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.17 no.4
• /
• pp.243-251
• /
• 2012

Real-time monitoring for environmental factors(temperature, salinity, chlorophyll, etc.) and carbonate components( pH and $fCO_2$) was conducted during 5-6th of July, 2012 at a seaweeds farm in Gijang, Busan. Surface temperature and salinity were ranged from $12.5{\sim}17.6^{\circ}C$ and 33.7~34.0, respectively, with highly daily and inter-daily variations due to tide, light frequency(day and night) and currents. Surface $fCO_2$ and pH showed a range of $381{\sim}402{\mu}atm$ and 8.03~8.15, and chlorophyll-a concentration in surface seawater ranged 0.8~5.8 ${\mu}g\;L^{-1}$. Environmental and carbonate factors showed the highest/lowest values around 5 pm of 5th July when the lowest tidal height and strongest thermocline in the water column, suggesting that biological production resulted in decrease of $CO_2$ and increase of pH in the seaweed farm. Processes affecting the surface $fCO_2$ distribution were evaluated using a simple budget model. In day time, biological productions by phytoplankton and macro algae are the main factors for $CO_2$ drawdown and counteracted the amount of $CO_2$ increase by temperature and air-sea exchange. The model values were a little higher than observed values in night time due to the over-estimation of physical mixing. The model suggested that algal production accounted about 14-40% of total $CO_2$ variation in seaweed farm.

• Journal of the Korean Ceramic Society
• /
• v.49 no.5
• /
• pp.404-411
• /
• 2012

The reliability of solid oxide fuel cells (SOFCs) particularly depends on the high quality of solid oxide electrolytes. The application of thinner electrolytes and multi electrolyte layers requires a more reliable characterization method. Most of the investigations on thin film solid electrolytes have been made for the parallel transport along the interface, which is not however directly related to the fuel cell performance of those electrolytes. In this work an array of ion-blocking metallic Ti/Au microelectrodes with about a $160{\mu}m$ diameter was applied on top of an ultrathin ($1{\mu}m$) yttria-stabilized-zirconia/gadolinium-doped-ceria (YSZ/GDC) heterolayer solid electrolyte in a micro-SOFC prepared by PLD as well as an 8-${\mu}m$ thick YSZ layer by screen printing, to study the transport characteristics in the perpendicular direction relevant for fuel cell operation. While the capacitance variation in the electrode area supported the working principle of the measurement technique, other local variations could be related to the quality of the electrolyte layers and deposited electrode points. While the small electrode size and low temperature measurements increaseed the electrolyte resistances enough for the reliable estimation, the impedance spectra appeared to consist of only a large electrode polarization. Modulus representation distinguished two high frequency responses with resistance magnitude differing by orders of magnitude, which can be ascribed to the gadolinium-doped ceria buffer electrolyte layer with a 200 nm thickness and yttria-stabilized zirconia layer of about $1{\mu}m$. The major impedance response was attributed to the resistance due to electron hole conduction in GDC due to the ion-blocking top electrodes with activation energy of 0.7 eV. The respective conductivity values were obtained by model analysis using empirical Havriliak-Negami elements and by temperature adjustments with respect to the conductivity of the YSZ layers.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.6
• /
• pp.679-686
• /
• 2020

In this thesis, an enhanced method for the feature extraction of vocal source signals and score combination using an MCE-Based weight estimation of the score of multiple feature vectors are proposed for the performance improvement of speaker recognition systems. The proposed feature vector is composed of perceptual linear predictive cepstral coefficients, skewness, and kurtosis extracted with lowpass filtered glottal flow signals to eliminate the flat spectrum region, which is a meaningless information section. The proposed feature was used to improve the conventional speaker recognition system utilizing the mel-frequency cepstral coefficients and the perceptual linear predictive cepstral coefficients extracted with the speech signals and Gaussian mixture models. In addition, to increase the reliability of the estimated scores, instead of estimating the weight using the probability distribution of the convectional score, the scores evaluated by the conventional vocal tract, and the proposed feature are fused by the MCE-Based score combination method to find the optimal speaker. The experimental results showed that the proposed feature vectors contained valid information to recognize the speaker. In addition, when speaker recognition is performed by combining the MCE-based multiple feature parameter scores, the recognition system outperformed the conventional one, particularly in low Gaussian mixture cases.