• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2029-2032
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• 2004

The quantity of data were rapidly increased recently and caused the data overwhelming. This led to be difficult in searching the required data. The method of eliminating redundant data was needed. One of the efficient methods was Knowledge Discovery in Database (KDD). Generally data can be separate into 2 cases, continuous data and discrete data. This paper describes algorithm that transforms continuous attributes into discrete ones. We present an Improved Class Attribute Interdependence Maximization (ICAIM), which designed to work with supervised data, for discretized process. The algorithm does not require user to predefine the number of intervals. ICAIM improved CAIM by using significant test to determine which interval should be merged to one interval. Our goal is to generate a minimal number of discrete intervals and improve accuracy for classified class. We used iris plant dataset (IRIS) to test this algorithm compare with CAIM algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2082-2086
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• 2003

This paper presents the analysis of satellite received signal by focus on the new prediction method for amplitude scintillation expression. A predict method based in the relationship of standard deviation values and the peak to peak values of amplitude scintillation in various of time period and various of sampling rate of signal variation. The principal techniques finding, the proper sampling rate and time interval, for the best expression method. The experiment has been performed in Bangkok of Thailand, at King Mongkut's Institute of Technology, Ladkrabang, data collected in C-Band and Ku-Band on high elevation angles. The result of analysis shows the relationship between two methods is given by ${\sigma}_x={\alpha}(P-P)+{\beta}$. The value of ${\alpha}$ depends on sampling rate by closely with three-minute maximum time interval.

• Journal of the Korea Society for Simulation
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• v.3 no.1
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• pp.17-28
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• 1994

A statistical procedure is developed to estimate the relative difference between two parameters each obtained from either true model or approximate model. Double sample procedure is applied to find the additional number of simulation runs satisfying the preassigned absolute precision of the confidence interval. Two types of parameters, mean and standard deviation, are considered as the performance measures and tried to show the validity of the model by examining both queues and inventory systems. In each system it is assumed that there are three distinct means and their own standard deviations and they form the simultaneous confidence intervals but with control in the sense that the absolute precision for each confidence interval is bounded on the limits with preassigned confidence level. The results of this study may contribute to some situations, for instance, first, we need a statistical method to compare the effectiveness between two alternatives, second, we find the adquate number of replications with any level of absolute precision to avoid the unrealistic cost of running simulation models, third, we are interested in analyzing the standard deviation of the output measure, ..., etc.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.920-924
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• 2005

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the environment. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.168.3-168
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• 2001

The purpose of this paper is to find the relations between the virtual reality created by the ship´s bridge simulator (simulator) at Radar Navigation Experiment and Research Facility in Kobe University of Mercantile Marine (KUMM) and the observer´s response to it. In short, we analyze the observer´s heart rate variability (R-R interval) in navigational condition seasick impression by simulator occurred, and present the R-R Interval and the stress of observer with SNS and PNS calculated by STFT. In this experiment, rolling of the ship was simulated and presented to the observer. Rolling was simulated only visually not physically or mechanically while the balancing movement and heart beat of the observer were measured and processed to produce the measures for body response to the artificially created visual environment. The results show that even a ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.177.4-177
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• 2001

In this paper, we propose a new type of nonlinear fixed interval smoothing filter which is modified from the existing nonlinear smoothing filter. A nonlinear smoothing filter is derived from two-filter formulas. For the backward filter, the propagation and update equation of error states are derived. Particularly the modified update equation of the backward filter use the estimated error terms from the forward filter. Smoothing algorithm is altered into the compatible form with the new type of the backward fitter. An advantage of the proposed algorithm is more efficient than the existing one because propagation in backward filter is very simple from the implementation point of view. We apply the proposed nonlinear smoothing ...

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.65.4-65
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• 2002

In this paper, RSF+RPP(Random Switching Frequency Ran-domized Pulse Position) PWM for three-phase voltage-controlled inverter is proposed. The LLPWM(Lead-Lag PWM) technique is that three switching pulses are located randomly back and forth in each switching interval But with the restriction of random distribution, the harmonic spectrum cannot be dispersedly and continuously distributed. To tackle this problem , First, the switching frequency is varied randomly. Next, the duty ratio is calculated under the first circumstance. Finally, the switching pulses are located randomly in the switching interval. To verify the validity of the proposed technique, Simulation Study is tried Using Matlab/Si...

• Earthquakes and Structures
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• v.3 no.6
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• pp.805-820
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• 2012

An enhanced and efficient methodology is proposed for evaluating the robustness of an uncertain structure with passive dampers. Although the structural performance for seismic loads is an important design criterion in earthquake-prone countries, the structural parameters such as storey stiffnesses and damping coefficients of passive dampers are uncertain due to various factors or sources, e.g. initial manufacturing errors, material deterioration, temperature dependence. The concept of robust building design under such uncertain structural-parameter environment may be one of the most challenging issues to be tackled recently. By applying the proposed method of interval analysis and robustness evaluation for predicting the response variability accurately, the robustness of a passively controlled structure can be evaluated efficiently in terms of the so-called robustness function. An application is presented of the robustness function to the design and evaluation of passive damper systems.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.181-198
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• 1997

The variable sampling rates scheme is proposed by taking random sample size and sampling interval during the process. The performance of the scheme is measured in terms of the average time to signal adjusted by teh sampling cost when the process is out of control. This measurement evaluates the effectiveness of the scheme in terms of the cost incurred due to nonconformation as well as sampling. The variable sampling rates scheme is shown to be effective especially for small and moderate shifts of the mean when compared to the standard scheme.

• Journal of Biomedical Engineering Research
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• v.12 no.4
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• pp.277-284
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• 1991

This study describes the ambulatory ECG monitoring system for the remote autom atic diagnosis. System: tlardware is based on one chip microcomputer(80c31) and its peripherals which consists of A/D, EPROM, RAM, LCD display and two preamplifiers, Power circuits, control logic circuits. A/D converted data were differentiated and low pass filtered. The detection of QRS complex and R point were accomplished by software algorithm based on adaptive threshold computed on low pass fi:leered signal. Rhythm analysis is performed by RR interval and average RR interval. The performance of QRS detection algorithm is evaluated by using MIT/BIH data base. Using this system, the trends of the arrythmia during the long term could be saved and displayed.