• 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.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.95-126
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• 2003

This paper introduces multifractal processes and presents the empirical investigation of the multifractal asset pricing. The multifractal stock price process contains long-tails which focus on Levy-Stable distributions. The process also contains long-dependence, which is the characteristic feature of fractional Brownian motion. Multifractality introduces a new source of heterogeneity through time-varying local reqularity in the price path. This paper investigates multifractality in stock prices. After finding evidence of multifractal scaling, the multifractal spectrum is estimated via the Legendre transform. The distinguishing feature of the multifractal process is multiscaling of the return distribution's moments under time-resealing. More intensive study is required of estimation techniques and inference procedures.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.9 no.3
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• pp.115-124
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• 1997

We measured the variance of eddy diffusion and associated ‘diffusion coefficients’ in coastal regions of Korea by observing the separation distances among multiple drifters deployed simultaneously at the same initial position. The variance of eddy diffusion was found to be proportional to $t^m$, where t is the time and m is a non-integer scaling exponent between 1.5 and 3.5. The observed scaling exponent of eddy diffusion cannot be reproduced by diffusion models employing constant eddy diffusivity. In this study, we applied fractal theory in simulating exponential increase of variance of eddy diffusion. We employed the fGn(fractional Gaussian noise) as a ‘modified’ random walks corresponding to the oceanic eddy diffusion. The variance of eddy diffusion, which corresponds to the fBm(fractional Brown motion) of our diffusion model, is proportional to $t^{2H}$, where H is Hurst scaling exponent. The temporal increase of the variance. with scaling exponent between 1 and 2, was successfully reproduced by our fractal diffusion model. However, our model cannot reproduce scaling exponent greater than 2. The scaling exponents greater than 2 are associated with the velocity shear of the mean flow.

• Journal of Navigation and Port Research
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• v.35 no.1
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• pp.51-56
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• 2011

In this paper, we presents an algorithm which restores lost data or increases resolution of a DTM(Digital terrain model) using fractal theory. Terrain information(fractal dimension and standard deviation) around the patch to be restored is extracted and then with this information and original data, the elevations of cells are interpolated using the random midpoint displacement method. The results of the proposed algorithm are compared with those of the bilinear and bicubic methods on a fractal terrain map.

• Journal of the Korean association of regional geographers
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• v.11 no.6
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• pp.530-542
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• 2005

In this study, GIS method has been used to get fractal characteristics. Using the projected area and surface area, 2 dimensional fractal characteristic of terrain was found out. Correlation of fractal dimension and mean slope were also checked over. Results are as below. 1) To get a fractal dimension, the method which is using the surface area is also directly proportional to complexity of the terrain as other fractal dimension. 2) Fractal dimensions using the surface area, that is proposed in this thesis are carried out as below : Uiseong : $2.02{\sim}2.15$ Yeongcheon : $2.10{\sim}2.24$. These values are in a range of fractal $2.10{\sim}2.20$ dimensions which has known. 3) Correlation of mean slope and fractal dimension is diminished about 30% in a region which is more than $25^{\circ}$ of mean slope. So, in this region using the fractal dimension method is better than using the mean slope. From this study, on formula using the projected area and surface area is still good to get a fractal dimension that has been found. But to confirm this method the region of research should be wider and be set up the correlation of mean slope, surface area and fractal dimension. It can be applicable to restoration of terrain and traffic flow analysis in the future research.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.87-87
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• 2019

흔히 진흙으로 대표되는 점착성 유사는 모래와 같은 비점착성 유사와 달리 응집 현상으로 인해 지속적으로 유사 입자의 크기가 변화한다. 응집 현상은 점착성 유사 입자의 응집 과정과 파괴과정으로 구성된다. 응집 현상 중 응집 과정은 유사 입자 간의 충돌로 인해 발생하는 것으로 이해되며, 충돌을 야기하는 메커니즘으로는 브라운 운동(Brownian Motion), 차등침강(Differential Settling), 난류 전단 (Turbulent Flow Shear)이 있다. 파괴 과정은 입자간 충돌로 인해 깨지는 것이 아닌 난류 전단(Turbulent Shear)로 인한 덩어리 분리(Massive Splitting)가 발생하는 것으로 이해한다. 이러한 유체의 특성, 흐름 특성 (난류 거동) 뿐만 아니라 유사 입자의 특성 모두의 영향을 받으며 지속적인 응집 현상을 겪는 점착성 유사 입자들은 하나의 커다란 덩어리인 플럭(Floc)을 형성한다. 형성된 플럭의 구조는 프랙탈 기하학을 따르는 것으로 이해된다. 따라서 플럭의 구조는 자기 유사성을 띠며, 플럭의 밀도는 형성된 플럭 크기의 함수가 된다. 플럭의 크기가 증가할수록 플럭의 프랙탈 차원이 감소하며, 플럭의 밀도는 감소한다. 많은 이전의 연구에서 플럭의 침강 속도를 농도에 따른 함수로 가정하고 경험식을 이용하여 산정하나, 유사 입자의 침강 속도는 크기와 밀도의 함수임을 Stokes Law를 통해 생각해 볼 수 있다. 이에 본 연구에서는 응집 현상의 결과물로 형성된 응집물의 크기와 밀도를 각각 산정하고, Stokes Law를 이용하여 침강 속도와 응집물 크기의 관계에 대한 연구를 수행하고자 한다. 보다 심도 있는 연구를 위해서는 응집 현상을 야기하는 메커니즘에 대한 이해가 필수적이다. 간소화된 응집 모형으로부터 얻어진 플럭 크기를 이용하여 프랙탈 차원, 플럭의 밀도를 산정한다. 형성된 응집물의 크기와 침강 속도의 관계에 대한 이해를 통해 보다 정확한 플럭의 침강 속도 산정이 가능할 것으로 생각된다.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.605-611
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• 2001

A numerical technique for simulating the aggregation of charged particles was presented with a Brownian dynamic simulation in the free molecular regime. The Langevin equation was used for tracking each particle making up an aggregate. A periodic boundary condition was used for calculation of the aggregation process in each cell with 500 primary particles of 16 nm in diameter. We considered the thermal force and the electrostatic force for the calculation of the particle motion. The morphological shape of aggregates was described in terms of the fractal dimension. The fractal dimension for the uncharged aggregate was $D_{f}=1.761$. The fractal dimension changed slightly for the various amounts of bipolar charge. However, in case of unipolar charge, the fractal dimension decreased from 1.641 to 1.537 with the increase of the average number of charges on the particles from 0.2 to 0.3 in initial states.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.2
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• pp.173-180
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• 2003

Effects of the electric conductivity of particles were studied for the aggregation process of charged particles with a Brownian dynamic simulation in the free molecular regime. A periodic boundary condition was used for the calculation of the aggregation process in each cell with 500 primary particles of 16 nm in diameter. We considered two extreme cases, a perfect conductor and a perfect nonconductor. The electrostatic force on a particle in the simulation cell was considered as a sum of electrostatic forces from other particles in the original cell and its replicate cells. We assumed that aggregates were only charged with pre-charged primary particles. The morphological shape of aggregates was described in terms of the fractal dimension. The fractal dimension for the uncharged aggregate was D$_{f}$= 1.761. However, the fractal dimension decreased from 1.694 to 1.360 for the case of the perfect conductor, and from 1.610 to 1.476 for the case of the perfect nonconductor, with the increase of the average number of charges on the primary particle from 0.2 to 0.3. These values were smaller than that of the centered charge case.e.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.357-365
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• 2009

To effectively exploit the underlying network bandwidth while maximizing user perceivable QoS, mandatory to make proper estimation on packet loss and queuing delay of the underling network. This issue is further emphasized in wireless network environment where network bandwidth is scarce resource. In this work, we focus our effort on developing performance model for wireless network. We collect packet trace from actually wireless network environment. We find that packet count process and bandwidth process in wireless environment exhibits long range property. We extract key performance parameters of the underlying network traffic. We develop an analytical model for buffer overflow probability and waiting time. We obtain the tail probability of the queueing system using Fractional Brown Motion (FBM). We represent average queuing delay from queue length model. Through our study based upon empirical data, it is found that our performance model well represent the physical characteristics of the IEEE 802.11b network traffic.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.2
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• pp.227-237
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• 2002

A numerical technique for simulating the aggregation of charged particles was presented with a Brownian dynamic simulation in the free molecular regime. The Langevin equation was used for tracking each particle making up an aggregate. A periodic boundary condition was used for calculation of the aggregation process in each cell with 500 primary particles of 16 nm in diameter. We considered the thermal force and the electrostatic force for the calculation of the particle motion. The electrostatic force on a particle in the simulation cell was considered as a sum of electrostatic forces from other particles in the original cell and its replicate cells. We assumed that the electric charges accumulated on an aggregate were located on its center of mass, and aggregates were only charged with pre-charged primary particles. The morphological shape of aggregates was described in terms of the fractal dimension. In the simulation, the fractal dimension for the uncharged aggregate was D$\_$f/ = 1.761. The fractal dimension changed slightly for the various amounts of bipolar charge. However, in case of unipolar charge, the fractal dimension decreased from 1.641 to 1.537 with the increase of the average number of charges on the particles from 0.2 to 0.3 in initial states. In the bipolar charge state, the average sizes of aggregates were larger than that of the uncharged state in the early and middle stages of aggregation process, but were almost the same as the case of the uncharged state in the final stage. On the other hand, in the unipolar charge state, the average size of aggregates and the dispersion of particle volume decreased with the increasing of the charge quantities.