• Journal of the Korean Chemical Society
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• v.48 no.3
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• pp.261-265
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• 2004

We investigated the order of local movement of functional groups (-C(=O)O) in a liquid crystalline (LC) oligomer (12-4) using 2D Raman correlation spectroscopy. The results suggest that the free carbonyl near the ethyl terminal group moved first, followed by the hydrogen-bonded group. The free carbonyl group between the biphenyl groups rarely moved. Interestingly, 2D sample-to-sample correlation spectroscopy (2D STSCS) revealed that some of the carbonyl modes started to move at far below (50$^{\circ}C$) the LC temperature (135$^{\circ}C$), countering conventional beliefs.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.614-618
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• 2005

수문시계열 분석과 예측은 대부분 ARMA(AutoRegressive Moving Average) 형태의 선형적인 추계학적인 모형을 이용하였으나 자현현상이 복잡해지고 비선형적인 특성을 가짐에 따라 선형적인 해석은 수문시계열의 분석과 예측에 있어서 많은 오류를 내포하고 있다. 이와 같은 문제를 해결하기 위한 시도로 Chaos이론이란 개념이 사용되기 시작하였으며, 수자원분야에서는 1980년대 후반부터 물수지 방정식 및 강우유출에 대한 카오스적 특성분석 등 많은 연구가 진행되었다. 본 연구에서는 영산강유역의 본류를 대표하는 나주지점을 대상으로 2003년 1월 1일 00시부터 2004년 12월 31일 23시까지 17,544개의 시수위 자료에 대하여 해당 년도의 Rating-Curve식을 적용 환산한 유출량자료에 데한 카오스적 특성을 분석하였다. 카오스적 특성을 분석하기에 앞서 원자료에 대하여 이동평균법과 Savitzky-Golay Filter를 적용하여 잡음을 제거하였으며, 1차원의 단일변량의 자료에 대한 상태공간(Phase Space)의 재건을 통하여 비교검토 하였다. 이러한 일련의 과정을 거친 자료에 대하여 상관차원법을 이용하여 영산강 유역의 나주지점의 시유출량 자료에 대한 카오스적 특성을 분석한 결과 저차원의 수렴으로 카오스 특성을 가졌다.

• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.52-60
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• 1999

Objectives: With the object of finding the appropriate conditions and algorithms for dimensional analysis of human EEG, we calculated correlation dimensions in the various condition of sampling rate and data aquisition time and improved the computation algorithm by taking advantage of bit operation instead of log operation. Methods: EEG signals from 13 scalp lead of a man were digitized with A-D converter under the condition of 12 bit resolution and 1000 Hertz of sampling rate during 32 seconds. From the original data, we made 15 time series data which have different sampling rate of 62.5, 125, 250, 500, 1000 hertz and data acqusition time of 10, 20, 30 second, respectively. New algorithm to shorten the calculation time using bit operation and the Least Trimmed Squares(LTS) estimator to get the optimal slope was applied to these data. Results: The values of the correlation dimension showed the increasing pattern as the data acquisition time becomes longer. The data with sampling rate of 62.5 Hz showed the highest value of correlation dimension regardless of sampling time but the correlation dimension at other sampling rates revealed similar values. The computation with bit operation instead of log operation had a statistically significant effect of shortening of calculation time and LTS method estimated more stably the slope of correlation dimension than the Least Squares estimator. Conclusion: The bit operation and LTS methods were successfully utilized to time-saving and efficient calculation of correlation dimension. In addition, time series of 20-sec length with sampling rate of 125 Hz was adequate to estimate the dimensional complexity of human EEG.

• Journal of the Korean Geotechnical Society
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• v.17 no.1
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• pp.85-97
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• 2001

Tse와 Cruden(1979)에 의해 암석 절리면 거칠기 정량화에 대한 연구가 시작된 이후 통계적인 정량화방법, 프랙탈 차원을 이용하는 방법 그리고 스펙트럼 분석을 이용하는 방법이 제안되었다. 이러한 통계적 정량화방법은 치수의존적이라는 단점이 있으며, 프랙탈 차원을 이용하는 방법은 크로스오버 차원이라는 문제점이 있는 것으로 평가되고 있다. 이 문제점들을 보완하는 방법으로 스펙트럼 분석법이 제시되어 많은 연구가 이루어졌다. 본 연구에서는 Barton과 Choubey(1977)가 제안한 10개의 절리면 프로파일을 수치화하고 통계적 분석, 프랙탈 차원 분석 그리고 스펙트럼 분석을 실시하여 이들 문제점을 살펴보고 스펙트럼 분석법이 위상이 변조된 프로파일에 대하여 문제가 있음을 확인하였다. 이들 문제점을 해결하기 위하여 측정간격과 프로파일의 기울기를 의미하는 통계적 파라미터의 관계를 선형으로 회귀분석하였다. 이렇게 구한 10개의 1차식의 기울기와 절편은 JRC와 매우 상관성이 높게 나타났다. 이 기울기와 절편을 거칠기 정량화의 변수로 사용함으로서 통계적 분석법에서의 치수의존적인 문제와 스펙트럼 분석에서의 위상변조의 문제를 해결하였다.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.931-940
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• 2011

Classification is to generate a rule of classifying objects into several categories based on the learning sample. Good classification model should classify new objects with low misclassification error. Many types of classification methods have been developed including logistic regression, discriminant analysis and tree. This paper presents a new classification method using penalized partial least squares. Penalized partial least squares can make the model more robust and remedy multicollinearity problem. This paper compares the proposed method with logistic regression and PCA based discriminant analysis by some real and artificial data. It is concluded that the new method has better power as compared with other methods.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.81-85
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• 2000

EEG(electroencephalogram)는 주로 전문가의 판독에 따른 주관적 판단에 의존하여 임상에서 사용되어져 왔다. 그러나 비선형 동역학 분석을 이용한 해석학적인 정량화 연구가 진행 되어짐에 따라 특이 패턴을 이용한 환자의 질병진단 이외에도 정상인의 뇌 활동 및 인지기능 둥을 이해하기 위한 도구로써 그 활용범위가 넓어지고 있다. 본 논문에서는 정상인에게 다양한 자극을 준 후 측정한 EEG를 상관차원 분석법을 이용하여 다양한 자극에 대한 뇌파의 특징을 분석하였다. 그 결과 각 자극에 따른 뇌 활동도의 차이를 정량적으로 분석할 수 있었으며, 뇌 활동 부위와 자극과의 관계도 정량적으로 분석할 수 있었다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.9 no.1
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• pp.47-54
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• 1991

In this study, the accuracy of three dimensional location was improved by self calibration bundle method with additional parameter, which is to correct systematic error through detection and elimination of the gross error from updated reference variance for observation values in photogram-metry. In this study, with the result of comparing accuracy of each method, correcting systematic error is more effective after gross error detection and when observation values are contained more than two gross error the point with maximum correlation value is detected by masking effect of least square adjustment.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.537-546
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• 2014

Surface image velocimetry was introduced as an efficient and sage alternative to conventional river flow measurement methods during floods. The conventional surface image velocimetry uses a pair of images to estimate velocity fields using cross-correlation analysis. This method is appropriate to analyzing images taken with a short time interval. It, however, has some drawbacks; it takes a while to analyze images for the verage velocity of long time intervals and is prone to include errors or uncertainties due to flow characteristics and/or image taking conditions. Methods using spatio-temporal images, called STIV, were developed to overcome the drawbacks of conventional surface image velocimetry. The grayscale-gradient tensor method, one of various STIVs, has shown to be effectively reducing the analysis time and is fairly insusceptible to any measurement noise. It, unfortunately, can only be applied to the main flow direction. This means that it can not measure any two-dimensional flow field, e.g. flow in the vicinity of river structures and flow around river bends. The present study aimed to develop a new method of analyzing spatio-temporal images in two-dimension using cross-correlation analysis. Unlike the conventional STIV, the developed method can be used to measure two-dimensional flow substantially. The method also has very high spatial resolution and reduces the analysis time. A verification test using artificial images with lid-driven cavity flow showed that the maximum error of the method is less than 10 % and the average error is less than 5 %. This means that the developed scheme seems to be fairly accurate, even for two-dimensional flow.

• Journal of Korean Society of Steel Construction
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• v.14 no.2
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• pp.339-348
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• 2002

The study developed an automatic design method of steel frames which uses nonlinear analysis. The geometric nonlinearity was considered using stability functions. Likewise, the transverse shear deformation effect in a beam-column was explained. A direct search method was used as an automatic design technique. The unit value of each part was evaluated using LRFD interaction equation. The member with the largest unit value was replaced one by one with an adjacent larger member selected from the database. The weight of the steel frame was considered as an objective function. On the other hand, load-carrying capacities, deflections, inter-story drifts, and ductility requirement were used as constraint functions. Case studies of a two-dimensional and a three-dimensional two-story frames were presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1207-1212
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• 2015

In this paper, we propose three-dimensional (3D) visualization and recognition techniques of micro-objects under photon-starved conditions using photon counting integral imaging microscopy. To capture high resolution 2D images with different perspectives in the proposed method, we use Synthetic Aperture Integral Imaging (SAII). Poisson distribution which is mathematical model of photon counting imaging system is used to extract photons from the images. To estimate 3D images with 2D photon counting images, the statistical estimation is used. Therefore, 3D images can be obtained and visualized without any damage under photon-starved conditions. In addition, 3D object recognition can be implemented using nonlinear correlation filters. To prove the usefulness of our technique, we implemented the optical experiment.