• 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 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 Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2016-2022
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• 2010

We propose a new algorithm for reconstructing curves with self-intersections from sample points. In general, the result of curve reconstruction depends on how to select and order the representative points to resemble the shape of sample points. Most of the previous point ordering approaches utilize the Euclidean distance to compute the proximity of sample points without directional information, so they can not solve the non-simple curve reconstruction problem. In this paper, we develop a new distance estimating the adjacency between sample points, which is derived from the standard normal distribution of Brownian motion. Experimental results show that this approach is very effective to non-simple curve reconstruction.

• The Korean Journal of Financial Management
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• v.19 no.2
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• pp.159-185
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• 2002

한 시계열이 비정상적과정에 의해 생성될 때 이 시계열의 정상성을 확보하기 위하여 시계열의 차분을 수행한다. 이 시계열에 I(1)을 적용하여도 정상적과정이 되지 못하는 경우가 존재하고 있다. 그러면 이 시계열은 과도한 차분과정을 거치게 된다. 따라서 차분모수 d는 0

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.187-200
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• 2013

In this paper, we deal with the problem of deciding a hedging volatility for ATM plain options when we hedge those options based on geometric Brownian motion. For this, we study the relation between hedging volatility and hedge profit&loss(P&L) as well as perform Monte Carlo simulations and real data analysis to examine how differently hedge P&L is affected by the selection of hedging volatility. In conclusion, using a relatively low hedging volatility is found to be more favorable for hedge P&L when underlying asset prices are expected to be range bound; however, a relatively high volatility is found to be favorable when underlying asset prices are expected to move on a trend.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.51-57
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• 2010

Steganography techniques can be used to hide data within digital images with little or no visible change in the perceived appearance of the image. I propose a steganalysis to detecting hidden message in sequential steganography. This paper presents adjusted technique for detecting abrupt jumps in the statistics of the stego signal during steganalysis. The repeated statistical test based on CUSUM-SPRT runs constantly until it reaches decision. In this paper, I deal with a new and improved statistic $g_t$ by computing $S^{t^*}_j$.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1007-1020
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• 2011

Since the research of Black and Scholes (1973), modeling methods using diffusion processes have performed principal roles in financial engineering. In modern financial theories, various types of diffusion processes were suggested and applied in real situations. An estimation of the model parameters is an indispensible step to analyze financial data using diffusion process models. Many estimation methods were suggested and their properties were investigated. This paper reviews the statistical properties of the, Euler approximation method, New Local Linearization(NLL) method, and Generalized Methods of Moment(GMM) that are known as the most practical methods. From the simulation study, we found the NLL and Euler methods performed better than GMM. GMM is frequently used to estimate the parameters because of its simplicity; however this paper shows the performance of GMM is poorer than the Euler approximation method or the NLL method that are even simpler than GMM. This paper shows the performance of the GMM is extremely poor especially when the parameters in diffusion coefficient are to be estimated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.258-264
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• 2018

This paper presents application of a differential search (DS) meta-heuristic optimization algorithm for optimal operation of a micro grid system. The DS algorithm simulates the Brownian-like random-walk movement used by an organism to migrate. The micro grid system consists of a wind turbine, a diesel generator, a fuel cell, and a photovoltaic system. The wind turbine generator is modeled by considering the characteristics of variable output. Optimization is aimed at minimizing the cost function of the system, including fuel costs and maximizing fuel efficiency to generate electric power. The simulation was applied to a micro grid system only. This study applies the DS algorithm with excellence and efficiency in terms of coding simplicity, fast convergence speed, and accuracy in the optimal operation of micro grids based on renewable energy resources, and we compared its optimum value to other algorithms to prove its superiority.

• 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.