• 한국해양학회지
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• v.29 no.4
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• pp.392-401
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• 1994

We examined the temporal characteristics of the oceanic eddy diffusion at 5 coastal regions of Korea by measuring the separation distances of multiple drifters released simultaneously at the same by the GPS and Decca transponder system. The observed variance of separation distance, for the time scales from minutes to hours, is proportional to t/SUP m/ with scaling exponent m between 1.2 and 2.0. The observed Lagrangian trajectories of drifters show fractal characteristics instead of random walk or Brown motion. As an effort toward a development of a realistic model of the oceanic eddy diffusion, we simulated the Lagrangian trajectories of drifters by fractional Brown motion (FBM) model. The observed variances of drifter separations can be generated by the FBM process provided the Hurst exponent is the same as the observed one. We further showed that the observed power law in the variance of drifter separations cannot be simulated with an ordinary Brown motion or random walk process.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.315-319
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• 2001

A diagnosis system that provides early warnings regarding machine malfunction is very important for rolling mill so as to avoid great losses resulting from unexpected shutdown of the production line. But it is very difficult to provide e8rly w, ul1ings in rolling mill. Because dynamics of rolling mill is non-linear. This paper shows a chaotic behaviour of vibration signal in rolling mill using embedding method. Phase plane and Poincare map, FFT and histogram of vibration signal in rolling mill are implemented by qualitative analysis and Fractal dimension, Lyapunov exponent are presented by quantitative analysis.

• Clinical and Experimental Pediatrics
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• v.45 no.9
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• pp.1114-1119
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• 2002

Purpose : The purposes of this study were to determine short- and long-term fractal correlation behavior of heart rates during daily activity in patients with neurocardiogenic syncope. Methods : Twenty five patients with histories of neurocardiogenic syncope episodes were included. Their analogue 24h ambulatory Holter electrocardiograms were analyzed. The tape was digitized and the digitized electrocardiograms were partioned into sections of one hour. Then their RR intervals were measured and 20,000 points of RRI were used. To quantify the fractal correlation behavior, we employed the detrended fluctuation analysis, and short-term($n{\leq}16$, ${\alpha}_1$) and long-term(n>16, ${\alpha}_2$) fractal scaling exponents were calculated. Results : When compared to control, 24-hour average values of ${\alpha}_1$ and all ${\alpha}_1$ values at quarters of each day were significantly higher in patients with syncope. On the contrary, their 24-hour average value of ${\alpha}_2$ and all ${\alpha}_2$ values at quarters of each day were lower in patients with syncope. However, statistical significances were found in 24-hour average value of ${\alpha}_2$ and in ${\alpha}_2$ value at MN-6AM. Conclusion : In the syncope patients with neurocardiogenic syncope, short-term fractal scaling exponents of RR interval was significantly high throughout the day. Therefore, their RR intervals were smoother in the short term scale and had a tendency to continue in the same direction of increase or decrease, which may contribute to persistent decrease in heart rate during a syncopal attack.

• The Journal of Engineering Geology
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• v.9 no.2
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• pp.119-134
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• 1999

Joints developed around the Moryang fault were investigated by traverse and inventory methods in order to characterize their orientation, spacing and density. The results of the traverse method show that the orientation of the dominant joint sets of the study area is NNE and EW, and that joint spacing distribution is a negative exponential distribution to the center of the fault and a log-normal distribution to the margin of the fault. The results of the inventory method show that the orientation of the dominant joint sets on joint map is NW and NE, and that joint density tends to increase toward the center of the fault. Fractal dimension was determined by using Box-counting method and Cantor's dust method to quantify the distribution of joint network and to evaluate the dimension around the fault. The dimension determined by Box-counting method ranges from 1.31 to 1.70 and shows the tendency of increasing value toward the center of the fault. Comparing fractal dimension by Box-counting method with joint density, fractal dimension is directly proportional to joint density. Nevertheless, fractal dimension could be varied due to the different distribution patterns of the joints with same density. The dimensions determined by Cantor's dust method show different values with respect to the orientation of scan lines. This results form the anisotropy of joint distribution.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.39-43
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• 2008

경관을 구성하는 다양한 요소들의 공간적 분포 패턴과 상호 관계를 정량적으로 분석하기 위하여 다양한 경관지수가 개발되어 사용되고 있다. 경관구조 및 변화특성을 정량적으로 해석하기 위한 노력은 1950년대 후반부터 기하학적 이론을 기초로 하여 제기되어 왔으며, 최근에는 원격탐사, GIS, 정보이론, 프랙탈 이론에 근거한 지표 등이 도입되어 사용되고 있다. 본 연구에서는 연안습지 식생의 발달과 분포 특성을 공간적으로 해석하기 위해 Landsat 영상에 분광혼합분석 기법을 적용하여 선정한 지표면 식생비율을 10개 클래스로 구분한 후 각 클래스에 대해 경관지수를 적용하여 식생비율의 시-공간적 변동 특성을 분석하였다. 새만금방조제를 비롯한 많은 연안습지에 생성되는 습지식생의 공간적 분포를 변화탐지 하고 이들의 시-공간적 분포에 영향을 미치는 요인을 해석하여 연안습지의 보존과 개발에 대한 기초 정보를 위성자료를 통해 추출 분석하였다.

• Spatial Information Research
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• v.8 no.2
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• pp.243-255
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• 2000

The spatial distribution characteristics and patterns of geographic features in space can be understood through a variety of analysis techniques. The scale is one of most important factors in spatial analysis techniques. This study is aimed at identifying the characteristics of spatial data with a coarser spatial resolution and finding procedures for spatial resolution in operational scale. To achieve these objectives, this study selected LANSAT TM imagery for Sunchon Bay, a coastal wetland for a study site, applied the indices for representing scale characteristics with resolution, and compared those indices. Local variance and fractal dimension developed by previous studies were applied to measure the textual characteristics. In this study, Moran s I was applied to measure spatial pattern change of variance data which were generated from the process of coarser resolution. Drawing upon the Moran s I of variancedata was optimum technique for analysing spatial structure than those of previous studies (local variance and fractal dimension). When the variance data represents maximum Moran´s I at certainly resolution, spatial data reveals maximum change at that resolution. The optimum resolution for spatial data can be explored by applying these results.

• The Korean Journal of Financial Management
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• v.21 no.1
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• pp.149-181
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• 2004

In this study we perform empirical tests using KOSPI return to investigate the existence of nonlinear characteristics in the generating process of stock returns. There are three categories in empirical tests; the test of nonlinear dependence, nonlinear stochastic process and nonlinear deterministic chaos. According to the analysis of nonlinearity, stock returns are not normally distributed but leptokurtic, and appear to have nonlinear dependence. And it's decided that the nonlinear structure of stock returns can not be completely explained using nonlinear stochastic models of ARCH-type. Nonlinear deterministic chaos system is the feedback system, which the past incidents influence the present, and it is the fractal structure with self-similarity and has the sensitive dependence on initial conditions. To summarize the results of chaos analysis for KOSPI return, it is the persistent time series, which is not IID and has long memory, takes biased random walk, and is estimated to be fractal distribution. Also correlation dimension, as the approximation of fractal dimension, converged stably within 3 and 4, and maximum Lyapunov exponent has positive value. This suggests that chaotic attractor and the sensitive dependence on initial conditions exist in stock returns. These results fit into the characteristics of chaos system. Therefore it's decided that the generating process of stock returns has nonlinear deterministic structure and follow chaotic process.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.96-100
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• 1996

So far the analysis and modeling of cutting process is studied commonly assumed as being linear stochastic or chaotic without experimental verification. So we verified force signals of cutting process(ball end-milling) is low-dimensional chaos by calculating Lyapunov Exponents. reconstructing attractor using time delay coordinates and calcula-ting it's fractal dimension.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.430-435
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• 2005

조화가진력이 작용하는 고정경계를 가진 완전원판의 비선형 진동에 대한 응답특성을 연구하였다. 원판의 비대칭모드의 고유진동수 근처에 가진주파수가 작용하는 주공진에서의 응답은 정상파(standing wave)뿐만 아니라 진행파(traveling wave)가 존재한다고 알려져 있다. 주공진 근처의 정상상태 응답곡선에서 최대한 5개의 안정한 응답이 존재하는 것으로 밝혀졌으며, 이들은 1개의 정상파와 4개의 진행파로 나타난다. 이 진행파중 2개는 Hope분기에 의해 안정성을 잃은 후 주기배가운동을 거쳐 혼돈운동에 이르게 된다. Lyaponov 지수를 사용하여 혼돈운동을 정량적으로 평가하였으며, 주평면의 개념을 이용하여 이 혼돈운동의 흡인영역이 Fractal임을 확인하였다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3866-3873
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• 2000

In this paper, we investigates the long-term memory and the Correct answer rate of the foreign exchange data (Yen/Dollar) that is one of economic time series, There are many cases where two kinds of fractal dimensions exist in time series generated from dynamical systems such as AR models that are typical models having a short terrr memory, The sample interval separating from these two dimensions are denoted by kcrossover. Let the fractal dimension be $D_1$ in K < $k^{crossover}$,and $D_2$ in K > $k^{crossover}$ from the statistics mode. In usual, Statistic models have dimensions D1 and D2 such that $D_1$ < $D_2$ and $D_2\cong2$ But it showed a result contrary to this in the real time series such as NIKKEL The exchange data that is one of real time series have relation of $D_1$ > $D_2$ When the interval between data increases, the correlation between data increases, which is quite a peculiar phenomenon, We predict exchange data by neural networks, We confirm that $\beta$ obrained from prediction errors and D calculated from time series data precisely satisfy the relationship $\beta$ = 2-2D which is provided from a non-linear model having fractal dimension, And We identified that the difference of fractal dimension appeaed in the Correct answer rate.