• 한국전자통신학회논문지
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• 제15권5호
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• pp.873-880
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• 2020

본 논문에서는 영상의 픽셀 고유의 값을 변환하고 위치를 섞는 높은 보안성을 지닌 암호화 알고리즘을 제안한다. Wolfram 규칙으로 생성된 상태 전이 행렬로 최대 길이를 가지는 여원 CA 수열을 만든다. 이를 2차원 기저 영상으로 변환하여 원 영상과 XOR 연산을 한 후, 층밀리기 변형 및 재배열 과정을 통하여 암호화된 영상을 만든다. 영상의 안정성 분석을 통하여 제안하는 암호화 기법이 높은 보안성을 가졌음을 검증한다.

• Wind and Structures
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• 제26권4호
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• pp.231-251
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• 2018

The objective of the investigation is the analysis of wind-tunnel experimental errors, associated with the measurement of aeroelastic coefficients of bridge decks (Scanlan flutter derivatives). A two-degree-of-freedom experimental apparatus is used for the measurement of flutter derivatives. A section model of a closed-box bridge deck is considered in this investigation. Identification is based on free-vibration aeroelastic tests and the Iterative Least Squares method. Experimental error investigation is carried out by repeating the measurements and acquisitions thirty times for each wind tunnel speed and configuration of the model. This operational procedure is proposed for analyzing the experimental variability of flutter derivatives. Several statistical quantities are examined; these quantities include the standard deviation and the empirical probability density function of the flutter derivatives at each wind speed. Moreover, the critical flutter speed of the setup is evaluated according to standard flutter theory by accounting for experimental variability. Since the probability distribution of flutter derivatives and critical flutter speed does not seem to obey a standard theoretical model, polynomial chaos expansion is proposed and used to represent the experimental variability.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2002년도 Proceedings of the International Welding/Joining Conference-Korea
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• pp.600-605
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• 2002

The keyhole formed by high energy density laser-material interaction periodically collapses due to surface tension of the molten metal in partial penetration welds. The collapse sometimes traps a void at the bottom of the keyhole, and it remains as welding defects. This phenomenon is seen as one cause of the instability of the keyhole during laser beam welding. Thus, it seems likely that improving the stability of the keyhole can reduce voids and uniform the penetration depth. The goal of this work is to develop techniques for controlling laser weld keyhole dynamics to reduce weld defects such as voids and inconsistent penetration. Statistical analysis of the penetration depth signals in glycerin determined that keyhole dynamics are chaotic. The chaotic nature of keyhole fluctuations and the ability of laser power modulation to control them have been demonstrated by high-speed video images of laser welds in glycerin. Additionally, an incident leading beam angle is applied to enhance the stability of the keyhole. The quasi-sinusoidal laser beam power of 400Hz frequency and 15$^{\circ}$ incident leading beam angle were determined to be the optimum parameters for the reduction of voids. Finally, chaos analyses of uncontrolled signals and controlled signals were done to show the effectiveness of modulation on the keyhole dynamics. Three-dimensional phase plots for uncontrolled system and controlled system are produced to demonstrate that the chaotic keyhole dynamics is converted to regular periodic behavior by control methods: power modulation and incident leading beam angle.

• Annals of Clinical Neurophysiology
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• 제4권1호
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• pp.28-33
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• 2002

Backgrounds and objective : EEG reflect dynamic changes of continuous neuronal activities by internal and external stimuli. The aim of this study is to quantify nonlinearly the local dynamic differences among EEG data corresponding to different states of brain. Methods : EEG was recorded from twelve healthy normal subjects(mean age, 29.7 years; 8 men and 4 women) using digital EEG machine. 18-channel EEG data were selected during eyes closed(EC), eyes open(EO), and mental arithmetic(MA) in each subject. Correlation dimension(D2) and largest Lyapunov exponent(LLE) were calculated from three states and average value was mapped 2 dimensionally and compared with each other. Results : The distribution of D2 was relatively symmetric and its value was higher in frontal than in parieto-occipital region during EC. These findings were reversed during EO. Bilateral centro-temporo-parietal region showed high D2 value in MA compared with those in EC, which was more prominent in left side. LLE was larger than zero in all state and showed significant differences among EC, EO and MA(p=0.000). Conclusion : These results suggest that nonlinear analysis of EEG can quantify dynamic state of brain.

• Smart Structures and Systems
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• 제22권4호
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• pp.399-411
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• 2018

The difficulty in modeling complex nonlinear structures lies in the presence of significant sources of uncertainties mainly attributed to sudden changes in the structure's behavior caused by regular aging factors or extreme events. Quantifying these uncertainties and accurately representing them within the complex mathematical framework of Structural Health Monitoring (SHM) are significantly essential for system identification and damage detection purposes. This study highlights the importance of uncertainty quantification in SHM frameworks, and presents a comparative analysis between intrusive and non-intrusive techniques in quantifying uncertainties for SHM purposes through two different variations of the Kalman Filter (KF) method, the Ensemble Kalman filter (EnKF) and the Polynomial Chaos Kalman Filter (PCKF). The comparative analysis is based on a numerical example that consists of a four degrees-of-freedom (DOF) system, comprising Bouc-Wen hysteretic behavior and subjected to El-Centro earthquake excitation. The comparison is based on the ability of each technique to quantify the different sources of uncertainty for SHM purposes and to accurately approximate the system state and parameters when compared to the true state with the least computational burden. While the results show that both filters are able to locate the damage in space and time and to accurately estimate the system responses and unknown parameters, the computational cost of PCKF is shown to be less than that of EnKF for a similar level of numerical accuracy.

• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.57-65
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• 2000

In this paper, a model reference adaptive control for the atomic force microscope (AFM) of tapping mode is investigated. The dynamics between the AFM system and al sample is mathematically modeled as a second order spring-mass-damper system with oscillatory inputs. The attractive and repulsive forces between the tip of the AFM system and the sample are derived using the Lennard-Jones potential energy. By non-dimensionalizing the displacement of the tip and the input frequency, the chaotic behavior near a resonance frequency is better depicted through the non-dimensionalized equations. Four nonlinear analysis techniques, a phase portrait, sensitive dependence on initial conditions, a power spectral density function, and a Pomcare map are investigated. Because the equations of motion derived in this paper involve unknown parameter values such as the damping effect of the air and the interaction constants between materials, the standard model reference adaptive control is adopted. Two control objectives, the prevention of chaos and the tracking of reference signal, are pursued. Simulation results are included.

• Smart Structures and Systems
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• 제29권2호
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.282-282
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• 2000

The analysis of the radiation effect on matter has been performed using stochastic methods. Recently, It was discovered that the detector pulses of radiation can be analysed using deterministic method that utilizes the chaotic behaviour with an attractor found in a noise region. We acquired a time series for pulse tram of Am-241 using scintillation detector and reconstructed a phase space, then performed new analysis for the radiation detection signal by applying embedding theory, Lyapunov exponent, correlation dimension, autocorrelation dimension, and power spectrum.

• Transactions on Control, Automation and Systems Engineering
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• 제4권2호
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• pp.124-129
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• 2002

This paper demonstrates that the largest Lyapunov exponent λ of recurrent neural networks can be controlled efficiently by a stochastic gradient method. An essential core of the proposed method is a novel stochastic approximate formulation of the Lyapunov exponent λ as a function of the network parameters such as connection weights and thresholds of neural activation functions. By a gradient method, a direct calculation to minimize a square error (λ - λ$\^$obj/)$^2$, where λ$\^$obj/ is a desired exponent value, needs gradients collection through time which are given by a recursive calculation from past to present values. The collection is computationally expensive and causes unstable control of the exponent for networks with chaotic dynamics because of chaotic instability. The stochastic formulation derived in this paper gives us an approximation of the gradients collection in a fashion without the recursive calculation. This approximation can realize not only a faster calculation of the gradient, but also stable control for chaotic dynamics. Due to the non-recursive calculation. without respect to the time evolutions, the running times of this approximation grow only about as N$^2$ compared to as N$\^$5/T that is of the direct calculation method. It is also shown by simulation studies that the approximation is a robust formulation for the network size and that proposed method can control the chaos dynamics in recurrent neural networks efficiently.

• Smart Structures and Systems
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• 제31권2호
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• pp.113-130
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• 2023

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.