• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.379-380
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• 2008

Molecular Dynamics (MD) simulations have been used to model the dynamics of the charge-compensating sodium ions in the non-stoichiometric hollandite Nax$(Ti_{8-x}Cr_x)O_{16}$. These interstitial ions reside in 'tunnels' in the crystal structure and move under the forces of both the ions making up the cage structure and the many body interactions of the other sodium ions in the tunnel. The Velocity Autocorrelation Function (VAF) of the sodium ions is calculated for a range of temperature from 250K to 1000K and converted into the linear ac-conductivity and ac-susceptibility response via Fourier transformation. A peak is found in the conductivity around $6\times10^{12}$ Hz that has some of the character of a Poley absorption. Here it is shown to be due to an harmonically coupled site vibrations of the sodium atoms, which extend only over a limited range. At frequencies below the peak the conductivity tends towards a constant i.e. dc value corresponding to a constant flow of ions through the simulation cell. At high temperatures the conductivity due to this ion transport process behaves like a metal with an insulator to metal transition occurring around a specific temperature.

• Sleep Medicine and Psychophysiology
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• v.15 no.1
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• pp.5-11
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• 2008

Sleep is an essential process maintaining the life cycle of the human. In parallel with physiological, cognitive, subjective, and behavioral changes that take place during the sleep, there are remarkable changes in the electroencephalogram (EEG) that reflect the underlying electro-physiological activity of the brain. However, analyzing EEG and relating the results to clinical observations is often very hard due to the complexity and a huge data amount. In this article, I introduce several linear and non-linear tools, developed to analyze a huge time series data in many scientific researches, and apply them to EEG to characterize various sleep states. In particular, the spectral analysis, detrended fluctuation analysis (DFA), and synchrony analysis are administered to EEG recorded during nocturnal polysomnography (NPSG) processes and daytime multiple sleep latency tests (MSLT). I report that 1) sleep stages could be differentiated by the spectral analysis and the DFA ; 2) the gradual transition from Wake to Sleep during the sleep onset could be illustrated by the spectral analysis and the DFA ; 3) electrophysiological properties of narcolepsy could be characterized by the DFA ; 4) hypnic jerks (sleep starts) could be quantified by the synchrony analysis.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.69-73
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• 2001

The dynamic characteristics of turning processes are complex, non-linear and time-varying. Consequently, the conventional techniques based on crisp mathematical model may not guarantee surface roughness regulation. This paper presents a fuzzy controller which can regulate surface roughness in milling process using end-mill under varying cutting condition. The fuzzy control rules are established from operator experience and expert knowledge about the process dynamics. regulation which increases productivity and tool life is achieved by adjusting feed-rate according to the variation of cutting conditions. The performance of the proposed controller is evaluated by cutting experiments in the converted CNC milling machine. The result of experiments show that the proposed fuzzy controller has a good surface roughness regulation capability in spite of the variation of cutting conditions.

• Journal of the Korean Institute of Navigation
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• v.19 no.3
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• pp.11-19
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• 1995

When an automatic course keeping is introduced, as is quite popular in modern navigation, the closed-loop control system consists of autopilot device, power unit, steering gear, ship dynamics, and magnetic or gyrocompass. We derive mathematical models of each element of the automatic steering system. We provide a method of theoretical analysis on the propulsive energy loss related to automatic steering of ships in the open seas, taking account of the on-off(non-linear) characteristics of power unit. Also we paid attention to non-linear element installed in autopilot device, which is normally called weather adjuster. Next we make numerical calculation of the effects of autopilot control constants on the propulsive energy loss for two kinds of ship, a fishing boat and an ore carrier. Realistic sea and wind disturbances are employed in the calculation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.990-993
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• 2005

This paper presents new results on designing a robust adaptive direct controller for a class of non-linear first order systems. The designing method based on the use of dead zone in the parameters' update law. It is shown that the size of the dead zone does not depend on the upper bounds of the disturbances. That means that even if the bounds are large, the tracking error will always converge to a set of the dead zone size. However, in the ideal case, when the exogenous signal functions and the function represents un-modeled dynamics of the systems equal to zero, the proposed controller does nt mean the convergence to zero of the tracking error. Computer simulation results show the effectiveness of the controller in dealing with the stated problems.

• Bulletin of the Korean Chemical Society
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• v.24 no.2
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• pp.178-182
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• 2003

The stress and the heat-flux auto-correlation functions in the Green-Kubo formulas for shear viscosity and thermal conductivity have non-decaying long-time tails. This problem can be overcome by improving the statistical accuracy by N (number of particles) times, considering the stress and the heat-flux of the system as properties of each particle. The mean square stress and the heat-flux displacements in the Einstein formulas for shear viscosity and thermal conductivity are non linear functions of time since the quantities in the mean square stress and the heat-flux displacements are not continuous under periodic boundary conditions. An alternative to these quantities is to integrate the stress and the heat-flux with respect to time, but the resulting mean square stress and heat-flux displacements are still not linear versus time. This problem can be also overcome by improving the statistical accuracy. The results for transport coefficients of liquid argon obtained are discussed.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.113-120
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• 1994

The dynamic characteristics of turning processes are complex, non-linear and time-varying. Consequently, the conventional techniques based on crisp mathematical model may not guarantee cutting force regulation. This paper presents a fuzzy controller which can regulate cutting force in turning process under varying cutting conditions. The fuzzy control rules are extablished from operator experience and expert knowledge about the process dynamics. Regulation which increases productivity and tool life is achieved by adjusting feedrate according to the variation of cutting conditions. The performance of the proposed controller is evaluated by cutting experiments in the converted conventional lathe. The results of experiments show that the proposed fuzzy controller has a good cutting force regulation capability in spite of the variation of cutting conditions.

• Earthquakes and Structures
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• v.23 no.4
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• pp.329-338
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• 2022

This work addresses the optimization controller design problem combining the AI evolution bat (EB) optimization algorithm with a fuzzy controller in the practical application of a reinforced concrete frame structure. This article explores the use of an intelligent EB strategy to reduce the dynamic response of Lead Rubber Bearing (LRB) composite reinforced concrete frame structures. Recently developed control units for plant structures, such as hybrid systems and semi-active systems, have inherently non-linear properties. Therefore, it is necessary to develop non-linear control methods. Based on the relaxation method, the nonlinear structural system can be stabilized by properly adjusting the parameters. Therefore, the behavior of a closed-loop system can be accurately predicted by determining the behavior of a closed-loop system. The performance and durability of the proposed control method are demonstrated by numerical simulations. The simulation results show that the proposed method is a viable and feasible control strategy for seismically tuned composite reinforced concrete frame structures.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.92-96
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• 2015

Due to unique characteristics of small construction companies, safety management is comprised of complex problems (e.g., resources constraints, a lack of formalized management structures, low level of management safety commitment etc.). In order to understand causal interdependencies between safety factors at different system levels (regulation, organization, technical and individual), this paper aims to develop a system dynamics (SD) model of safety management in small construction companies. The purpose of the SD model is to better understand why small construction companies have low level of safety performance. A causal loop diagram (CLD) was developed based on literature, with an attempt to map causal relationships between variables. The CLD was then converted into stock and flow diagram for simulation. Various tests were conducted to build confidence in the model's ability to represent the reality. A number of policies were analyzed by changing the value of parameters. The value of a system dynamics approach to safety management in small construction companies is its ability to address joint effects of multiple safety risk factors on safety performance with a systems thinking perspective. By taking into account feedback loops and non-linear relationships, such a system dynamics model provides insights into the complex causes of relatively poor safety performance of small construction companies and improvement strategies.

• Journal of Korea Water Resources Association
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• v.34 no.5
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• pp.473-486
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• 2001

The WGR model was developed to represent meso-scale precipitation. As a conceptual model, this model shows a good link between atmospheric dynamics and statistical description of meso-scale precipitation(Waymire et al., 1984). However, as it has maximum 18 parameters along with its non-linear structure, its parameter estimation has been remained a difficult problem. There have been several cases of its parameter estimation for different fields using non-linear programming techniques(NLP), which were also difficult tasks to hamper its wide applications. In this study, we estimated the WGR model parameters of the Han river basin using the genetic algorithm(GA) and compared them to the NLP results(Yoo and Kwon, 2000). As a result of the study, we can find that the sum of square error from the GA provide more consistent parameters to the seasonal variation of rainfall. Also, we can find that the higher rainfall amount during summer season is closely related with the arrival rate of rain bands, not the rain cell intensity.