• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.364-368
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• 2009

자궁경부암은 다른 암과 달리 전암(前癌) 단계가 존재하므로 조기에 발견할 경우 생존율이 높다. 그러나 검체 적정성의 부족과 검체 체취의 오류로 인해 질병이 있음에도 음성으로 나타나는 위음성률이 높다. 따라서 본 논문에서는 세포 도말검사에서 사용되는 자궁 경부진 세포에서 암종 세포를 추출하는 방법을 제안한다. 영상의 배경 그리고 핵과 세포질 영역의 구분이 중요하기 때문에 조기 자궁 경부 세포진 영상에서 핵의 추출은 Lighting Compensation을 적용하여 영상을 보정하고, 명암도 분포가 가장 작은 B 채널과 명암도 분포가 높은 R채널과의 OR 연산을 적용한 후, $3{\times}3$마스크를 이용하여 잡음을 제거한다. 잡음이 제거된 영상을 이진화하고 Grassfire 알고리즘을 이용하여 암종 세포의 후보 객체를 추출한다. 추출된 세포 객체에서 핵의 크기, 핵의 면적과 핵의 외곽의 방향성 정보를 이용하여 백혈구와 잡음으로 구성된 객체를 제거한다. 세포 도말검사 과정에서 겹쳐진 부분은 거리 함수와 명암도를 이용하여 마커를 추출하고 추출된 마커 정보와 워터쉐드 알고리즘을 적용하여 겹쳐진 암종 세포를 분리한다. 자궁경부 편평 세포진 400 배율 영상과 자궁 경부 상피내 종양 400 배율 영상을 대상으로 실험한 결과, 기존의 자궁 경부진 암종 세포 추출 방법보다 효과적으로 암종 세포 영역이 추출되는 것을 확인하였다.

• Geophysics and Geophysical Exploration
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• v.14 no.3
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• pp.220-226
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• 2011

In the elastic wave equations, both horizontal and vertical displacements are defined. Since we can measure both the horizontal and vertical displacements in field acquisition, these displacements compose a displacement vector. In this study, we propose a frequency-domain elastic waveform inversion technique taking advantage of the magnitudes of displacement vectors to define objective function. When we apply this displacement-vector objective function to the frequency-domain waveform inversion, the inversion process naturally incorporates the back-propagation algorithm. Through the inversion examples with the Marmousi model and the SEG/EAGE salt model, we could note that the RMS error of the solution obtained by our algorithm decreased more stably than that of the conventional method. Particularly, the density of the Marmousi model and the low-velocity sub-salt zone of the SEG/EAGE salt model were successfully recovered. Since the gradient direction obtained from the proposed objective function is numerically unstable, we need additional study to stabilize the gradient direction. In order to perform the waveform inversion using the displacementvector objective function, it is necessary to acquire multi-component data. Hence, more rigorous study should be continued for the multi-component land acquisition or OBC (Ocean Bottom Cable) multi-component survey.

• Journal of KSNVE
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• v.6 no.3
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• pp.341-347
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• 1996

Vibration analysis is one of the most powerful tools available for the detection and isolation of incipient faults in mechanical systems. The methods of vibration analysis in use today and under continuous study are broad band vibration monitoring, time domain analysis, and frequency domain analysis. In recent years, great interest has been generated concerning the use of time- frequency repesentation and its application for a machinery diagnostics and condition monitoring system. The objective of the study described in this paper was to develop a new diagnostic tool for the rotating machinery. This paper introduces a new time frequency representation. Directional Winger-Ville Distribution, which analyese the time-frequency structure of the rotating machinery vibration.

• Journal of Internet Computing and Services
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• v.4 no.6
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• pp.57-67
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• 2003

The recent rapid development of multimedia and optical technologies brings great attention to application systems to process facial Image features. The previous research efforts in facial image processing have been mainly focused on the recognition of human face and facial expression analysis, using front face images. Not much research has been carried out Into image-based detection of face direction. Moreover, the existing approaches to detect face direction, which normally use the sequential Images captured by a single camera, have limitations that the frontal image must be given first before any other images. In this paper, we propose a method to detect face direction by using facial features such as facial trapezoid which is defined by two eyes and the lower lip. Specifically, the proposed method forms a facial direction formula, which is defined with statistical data about the ratio of the right and left area in the facial trapezoid, to identify whether the face is directed toward the right or the left. The proposed method can be effectively used for automatic photo arrangement systems that will often need to set the different left or right margin of a photo according to the face direction of a person in the photo.

• 한국IT서비스학회:학술대회논문집
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• 2006.11a
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• pp.80-85
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• 2006

현재 많은 인터넷 콘텐츠 서비스가 다양한 방식의 유료 서비스로 제공되고 있지만 다양하고 복잡한 콘텐츠 서비스의 특성상 가격 책정에는 많은 어려움이 있다. 본 연구는 인터넷 영화관을 대상으로 하여 사용자들이 서비스를 선택할 때 가장 고려하는 속성을 분석하고 속성과 속성 수준을 설정한 프로파일들의 가격반응함수를 구하였다. 또한, 선형${\cdot}$곱셈${\cdot}$유인${\cdot}$구텐베르그 모델 중 가장 적합한 모델을 추정하고 독점 영역과의 관계를 살펴봄으로써 각 기업들이 서비스의 가격을 책정함에 있어서 가장 수익성 높고 적합한 전략을 설정할 수 있도록 방향을 제시하였다.

• Tunnel and Underground Space
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• v.17 no.2 s.67
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• pp.119-127
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• 2007

Based on the critical plane approach, a methodology far predicting the anisotropic strength ot transversely isotropic rock is Proposed. It is assumed that the rock failure is governed by Hoek-Brown failure criterion. In order to establish an anisotropic failure function, Mohr envelope equivalent to the original Hoek-Brown criterion is used and the strength parameters m, s are expressed as scalar functions of orientation. The conjugate gradient method, which is one of the robust optimization techniques, is applied to the failure function for searching the orientation giving the maximum value of the anisotropic function. While most of the existing anisotropic strength models can be applied only when the stress condition is the same as that of conventional triaxial compression test, the proposed model can be applied to the general 3-dimensional stress conditions. Through the simulation of triaxial compression tests for transversely isotropic rock sample, the validity of the proposed method is investigated by comparing the predicted triaxial strengths and inclinations of failure plane.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.84-92
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• 1998

In this paper, we propose the novel cost functions for finding the disparity between the left and the right images in the stereo matching problem. The dynamic programming method is used in solving the stereo matching problem by Cox et al[10]. In the reference[10], only the intensity of the pixels in the epipolar line is used as the cost functions to find the corresponding pixels. We propose the two new cost functions. The information of the slope of the pixel is introduced to the constraints in determining the weights of intensity and direction(the historical information). The pixels with the higher slope are matched mainly by the intensity of pixels. As the slope becomes lower, the matching is performed mainly by the direction. Secondly, the disparity information of the previous epipolar line the pixel is used to find the disparity of the current epipolar line. If the pixel in the left epipolar line, $p-i$ and the pixel in the right epipolar line, $p-j$ satisfy the following conditions, the higher matching probability is given to the pixels, $p-i$ and $p-j$. i) The pixels, $p-i$ and $p-j$ are the pixles on the edges in the left and the right images, respectively. ⅱ) For the pixels $p-k$ and $p-l$ in the previous epipolar line, $p-k$and $p-l$ are matched and are the pixels on the same edge with $p-i$ and $p-j$, respectively. The proposed method compared with the original method[10] finds the better matching results for the test images.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.335-335
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• 2012

III-V 족 반도체 물질 중, GaN는 넓은 밴드갭을 가지고 있어 발광 다이오드나 레이저 다이오드, 트랜지스터, 스핀트로닉스 등의 응용에 유용한 물질이다 [1]. 실시간 성장 제어 및 최적화된 특정 소자 응용을 위해서는 GaN의 다양한 온도에 대한 유전율 함수 정보가 필수적이다. 편광분석법을 이용한 상온에서의 hexagonal GaN 유전율 함수는 이미 여러 연구에서 보고되었고, 80~650 K 사이의 온도 범위에 대한 언구도 수행되었다 [2,3]. 그러나, 온도변화에 대한 GaN 유전율 함수와 $E_0$ 전이점에 대한 해석은 부정확하다. 따라서 본 연구에서는 사파이어 기판 위에 분자살박막증착장치를 이용하여 c-축 방향 (0001)으로 성장 시킨 hexagonal GaN를 0.74~6.42 eV 에너지 구간에서 보다 확장된 온도 영역(26~693 K)의 유전율 함수를 편광분석법을 이용하여 측정하였다. 측정된 GaN의 유전율 함수를 회기분석법을 통한 2차 미분 표준해석법을 이용해 분석 하였고, 그 결과 $E_0$와 excitonic $E_0$ 전이점을 명확히 얻을 수 있었다. 온도가 감소함에 따라 격자상수 및 전자-포논 상호작용이 감소하여 전자 전이점이 청색천이 하고, 그 구조가 명확해 지는 결과를 얻었다. 본 연구의 결과는 GaN 유전율 함수의 온도 의존성에 대한 데이터베이스를 제공함은 물론, 실시간 모니터링과 GaN를 기반으로 하는 광소자 제작 등에 유용할 것이다.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.899-902
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• 1998

임상진단에 있어서 종종 문제가 되고 있는 호흡에 따른 두뇌부분의 가상적인 상하이동을 고려해서 위상 엔코드 축인 Y 방향만의 강체의 평행이동을 취급한다. 종래의 발견적인 축차 근사 반복처리에 의한 제거방법과는 달리, 본 연구에서는 MRI 촬상과정과 화상특성의 해석에 근거한 MRI 신호중의 체동성분과 화상성분을 단순한 대수연산에 의해 분리할 수 있는 새로운 구속조건을 도출한다. MRI 신호에 대해서 X 방향의 1차원 푸리에 변환을 행한 후의 Y 방향의 스펙트럼 위상값은 화상자신의 성분과 체동성분의 합이 되고 있다. 한편, 두뇌부위 등의 단층상에 있어서 주위의 피하지방 부분의 밀도는 거의 균일한 것 알려져 있어 이 부분위의 Y 방향의 1 라인 밀도분포를 대칭이라고 간주할 수 있다. 밀도함수가 대칭인 경우 스펙트럼의 위상은 그 위치에 대하여 선형적으로 변화한다. 따라서 이 선형함수로부터 벗어난 성분을 체동성분으로 분리할 수 있다. 이러한 구속조건에 기초를 둔 근거가 명확한 아티팩트의 제거방법을 제안한다. 아울러 본 방법의 유효성을 확인하기 위해 호흡에 의한 주기성의 체동을 가진 MRI 화상에 대해서 시뮬레이션을 행하였다.