• The Journal of the Korea institute of electronic communication sciences
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• v.2 no.1
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• pp.10-18
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• 2007

In this paper, we extend the multiple time scale control framework to window-based congestion control, in particular, TCP. This is performed by interfacing TCP with a large time scale control module which adjusts the aggressiveness of bandwidth consumption behavior exhibited by TCP as a function of "large time scale" network state. i.e., conformation that exceeds the horizon of the feedback loop as determined by RTT. Performance evaluation of multiple time scale TCP is facilitated by a simulation bench-mark environment which is based on physical modeling of self-similar traffic. If source traffic is not extended exceeding, when RTT is 450ms, in self similar burst environment, performance gain of TCP-SSC is up to 45% for ${\alpha}$=1.05. However, its is acquired only 20% performance gain for ${\alpha}$=1.95 relatively. Therefore we showed that by TCP-MTS at large time scale into a rate-based feedback congestion control, we are able to improve two times performance significantly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6B
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• pp.575-583
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• 2004

In this paper, we extend the multiple time scale control framework to the window-based congestion control, in particular, such as the TCP. This is performed by interfacing the TCP with a large time scale control module which adjusts the aggressiveness of the bandwidth consumption behavior exhibited by the TCP as a function of large time scale Self-Similar network state. i.e., conformation that exceeds the horizon of the feedback loop as determined by the RTT. How to effectively utilize such an information-due to its probabilistic nature, dispersion over the multiple time scales, and affection on the top of the existing window-based congestion controls-is a non-trivial problem. The evaluation performance of the multiple time scale TCP is facilitated by a simulation of the bench-mark environment which is based on the physical modeling of a self-similar traffic. We explicate our methodology for discerning and evaluating the impact of changes in transport protocols in the protocol stack under the self-similar traffic conditions. We discuss issues arising in the comparative performance evaluation under heavy-tailed workloads.

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.358-366
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• 2002

Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the high speed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps(SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space and generates a topological feature map. A topological feature map preserves the mutual relations (similarities) in feature spaces of input data, and clusters mutually similar feature vectors in a neighboring nodes. Therefore each node of the topological feature map holds a node vector and similar images that is closest to each node vector. We implemented a k-NN search for similar image classification as to (1) access to topological feature map, and (2) apply to pruning strategy of high speed search. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

• Journal of the Chungcheong Mathematical Society
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• v.26 no.2
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• pp.411-420
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• 2013

We consider fractional Gussian noise and FARIMA sequence with Gaussian innovations and show that the suitably scaled distributions of the FARIMA sequences converge to fractional Gaussian noise in the sense of finite dimensional distributions. Finally, we figure out ACF function and estimate the self-similarity parameter H of FARIMA(0, $d$, 0) by using R/S method.

• Journal of the Korean Vacuum Society
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• v.5 no.2
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• pp.99-106
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• 1996

Two types of regularization method (singular system and HMP approaches) for generating depth-concentration profiles from angle-resolved XPS data were evaluated. Both approaches showed qualitatively similar results although they employed different numerical algorithms. The application of the regularization method to simulated data demonhstrates its excellent utility for the complex depth profile system . It includes the stable restoration of depth-concentration profiles from the data with considerable random error and the self choice of smoothing parameter that is imperative for the successful application of the regularization method. The self choice of smoothing parameter is based on generalized cross-validation method which lets the data themselves choose the optimal value of the parameter.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.96.3-96
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• 2001

In this paper the self-organized and fuzzy inference used stochastic gradient ascent method is proposed. Fuzzy rule and fuzzy set increase as occasion demands autonomously according to the observation information. And two rules(or two fuzzy sets)becoming to be similar each other as progress of learning are unified. This unification causes the reduction of a number of parameters and learning time. Using fuzzy inference and making a rule with an appropriate state division, our proposed method makes it possible to construct a robust reinforcement learning system.

• Publications of The Korean Astronomical Society
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• v.18 no.1
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• pp.21-24
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• 2003

The problem of the collapse of a self gravitating disk is here considered. We show self-similar solutions for the above problem under a modified viscous parameter. Surface density depends on r$^m$ in the inner region, where m is -1.6. Therefore growing central mass goes on without mass inflow to the system.

• Journal of applied mathematics & informatics
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• v.33 no.1_2
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• pp.203-210
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• 2015

We consider fractional Brownian motion and FARIMA process with Gaussian innovations and show that the suitably scaled distributions of the FARIMA processes converge to fractional Brownian motion in the sense of finite dimensional distributions. We figure out ACF function and estimate the self-similarity parameter H of FARIMA(0, d, 0) by using R/S method. Finally, we display power spectrum density of FARIMA process.

• Journal of the Korean Mathematical Society
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• v.47 no.5
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• pp.1055-1075
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• 2010

In presented paper there were studied some properties of Benford's law. The existence of this law in not necessary large sets of numbers is a very interesting example that can show how the complex phenomena can appear in the positional number systems. Such systems seem to be very simple and intuitive and help us proceed with numbers. However, their simplicity in the case of usage in our lifetime is not necessary connected with the simplicity in the case of laws that govern them. Even if this laws indicate the existence of self-similar properties.

• Korean Journal of Mathematics
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• v.26 no.2
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• pp.155-166
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• 2018

Consider FARIMA time series with innovations that have infinite variances. We are interested in the estimation of self-similarities $H_n$ of FARIMA(0, d, 0) by using modified R/S statistic. We can confirm that the $H_n$ converges to Hurst parameter $H=d+\frac{1}{2}$. Finally, we figure out ARMA and minimum variance power spectrum density of FARIMA processes.