• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.163-171
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• 2009

Classical linear models have been generally used to analyze and forecast hydrologic time series. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. In recent, the BDS (Brock-Dechert-Scheinkman) statistic instead of conventional techniques has been used for detecting nonlinearity of time series. The BDS statistic was derived from the statistical properties of the correlation integral which is used to analyze chaotic system and has been effectively used for distinguishing nonlinear structure in dynamic system from random structures. DVS (Deterministic Versus Stochastic) algorithm has been used for detecting chaos and stochastic systems and for forecasting of chaotic system. This study showed the DVS algorithm can be also used for detecting nonlinearity of the time series. In this study, the stochastic and hydrologic time series are analyzed to detect their nonlinearity. The linear and nonlinear stochastic time series generated from ARMA and TAR (Threshold Auto Regressive) models, a daily streamflow at St. Johns river near Cocoa, Florida, USA and Great Salt Lake Volume (GSL) data, Utah, USA are analyzed, daily inflow series of Soyang dam and the results are compared. The results showed the BDS statistic is a powerful tool for distinguishing between linearity and nonlinearity of the time series and DVS plot can be also effectively used for distinguishing the nonlinearity of the time series.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.3 s.309
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• pp.10-19
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• 2006

In this paper, we propose 128-bit chaotic block encryption scheme using a PLCM(Piecewise Linear Chaotic Map) having a good dynamical property. The proposed scheme has a block size of 12n-bit and a key size of 125-bit. The encrypted code is generated from the output of PLCM. We show the proposed scheme is very secure against statistical attacks and have very good avalanche effect and randomness properties.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.67-75
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• 1999

The sensing and communication abilities of a mobile robot are essential to cooperative behavior in distributed autonomous robotic systems. In general, as the number of robot goes on increasing, the limitation of communication capacity and information overflow occur in global communication capacity and information overflow occur in global communication system. Therefore a local communication is more effective than global one. In this paper, we analyze information propagation mechanism based on local communication. To find an optimal communication radius, we propose three methods with different conditions. Also, to avoid chaotic behavior which occurs when a robot obtains and loses information, we find stable condition of information propagation.

• 한국정보통신설비학회:학술대회논문집
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• 2005.08a
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• pp.406-414
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• 2005

In this paper, we propose 128bits chaotic block encryption scheme using a PLCM(Piece-wise Linear Chaotic Map) having a good dynamical property. The proposed scheme has a block size of 128 bits and a key size of 128 bits. In proposed scheme we use four 32bi1s sub-keys of session key and four 32bit sub-blocks of block to decide the initial value and the number of iteration of PLCM. The encrypted code is generated from the output of PLCM. With results of test and analyses of security we show the proposed scheme is very secure against statistical attacks and have very good Avalanche Effect and Randomness properties.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1844-1847
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• 1997

Assuming that EEG(electroencephalogram), which is generated by a nonlinear electrical of billions of neurons in the brain, has chaotic characteristics, it is confirmend by frequency spectrum analysis, log frequency spectrum analysis, correlation dimension analysis and Lyapunov exponents analysis. Some chaotic characteristics are related to the degree of brain activity. The slope of log frequency spectrum increases and the correlation dimension decreasess with respect to the activities, while the largest Lyapunov exponent has only a rough correlation.

• Journal of Biomedical Engineering Research
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• v.14 no.4
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• pp.379-386
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• 1993

This paper describes design of a Chaos analyser and its applications to analysis of nonlinear characteristirs of ECG. The proposed system can easily distinguish chaotic system among the various dynamical systems by chaotic quantitative and qualitative analysis and also chaotic characteristics which represents states of nonlinear dynamical system. And we have also proposed new possibilities to recognize abnormal state of ECG signal using the chaotic characteristics.

• Journal of the Korea Society for Simulation
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• v.3 no.1
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• pp.65-74
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• 1994

In the steady-state simulation, it is important to identify initialization bias for the correct estimates of the simulation model under study. In this paper, the methods from chaos theory are applied to the determination of truncation points in the simulation data for controlling the initial bias. Two methods are proposed and evaluated based on their effectiveness for estimation the average waiting time in M/M/1($\infty$) queueing model.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.65-82
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• 1996

This paper proposes a sequential procedure which can be used to determine a truncation point and run length to reduce or remove bias owing to artificial startup conditions in simulations aimed at estimating steady-state behavior. It is based on the idea of Lyapunov exponent in chaos theory. The performance measures considered are relative bias, coverage, estimated relative half-width of the confidence interval, and mean amount of deleted data.

• Proceedings of the SAREK Conference
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• 2007.06a
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• pp.36-36
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• 2007

• Journal of Biomedical Engineering Research
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• v.15 no.3
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• pp.347-354
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• 1994

This paper describes a diagnostic protocol of nonlinear dynamic characteristics of biological system using chaos theory. An integrated chaos analysis system for the diagnosis of biological system was designed. We suggest a procedure of attractor reconstruction for reliable qualitative and quantitative analysis. The effect of autonomic nervous system activity on heart rate variability with power spectral analysis and its characteristics of chaotic attractors are investigated. The results show the applicability to evaluate the mental and physical conditions using nonlinear characteristics of biological signal.