• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2448-2450
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• 1998

For the exact classification of the arm motion this paper proposes EMG pattern recognition method with neural network. For this autoregressive coefficient, linear cepstrum coefficient, and adaptive cepstrum coefficient are selected for the feature parameter of EMG signal, and they are extracted from time series EMG signal. For the function recognition of the feature parameter a radial basis function network, a field of neural network is designed. For the improvement of recognition rate, a number of radial basis function network are combined in parallel, comparing with a backpropagation neural network an existing method.

• Journal of Korean Society of Water and Wastewater
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• v.10 no.2
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• pp.88-103
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• 1996

The objective of this study is to develop stochastic and deterministic models which could be used to synthesize water application time series. Adaptive models using mulitivariate ARIMA(Transfer Function Model) are developed for daily urban water use forecasting. The model considers several variables on which water demands is dependent. The dynamic response of water demands to several factors(e.g. weekday, average temperature, minimum temperature, maximum temperature, humidity, cloudiness, rainfall) are characterized in the model by transfer functions. Daily water use data of Kumi city in 1992 are employed for model parameter estimation. Meteorological data of Seonsan station are utilized to input variables because Kumi has no records about the meteorological factor data.To determine the main factors influencing water use, autocorrelogram and cross correlogram analysis are performed. Through the identification, parameter estimation, and diagnostic checking of tentative model, final transfer function models by each month are established. The simulation output by transfer function models are compared to a historical data and shows the good agreement.

• Structural Engineering and Mechanics
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• v.17 no.5
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• pp.691-706
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• 2004

The paper presents shear lag parameters for beam-to-column connections in steel box piers. Previous researches have analyzed beam-to-column connections in steel piers using a shear lag parameter ${\eta}_o$ obtained from a simple beam model, which is not based on a reasonable design assumption. Instead, the current paper proposes a cantilever beam model and has proved the effectiveness through theoretical and experimental studies. The paper examines the inaccuracy of the previous researches by estimating the effective width, the width-span length ratio L/b, and the sectional area ratio S of a cantilever beam. Two different shear lag parameters are defined using the cantilever model and the results are compared each other. The first type of shear lag parameter ${\eta}_c$ of a cantilever beam is derived using additional moments from various stress distribution functions while the other shear lag parameter ${\eta}_{eff}$ of a cantilever beam is defined based on the concept of the effective width. An evaluation method for shear lag stresses has been investigated by comparing analytical stresses with test results. Through the study, it could be observed that the shear lag parameter ${\eta}_{eff}$ agrees with ${\eta}_c$ obtained from the $2^{nd}$ order stress distribution function. Also, it could be observed that the shear lag parameter ${\eta}_c$ using the $4^{th}$ order stress distribution function almost converges to the upper bound of test results.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.233-242
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• 2021

In this paper, as a liberal arts course for non-majors, we proposed a supervised learning artificial neural network parameter optimization method and a basic education method for activation function to design a basic artificial neural network subject curriculum. For this, a method of finding a parameter optimization solution in a spreadsheet without programming was applied. Through this training method, you can focus on the basic principles of artificial neural network operation and implementation. And, it is possible to increase the interest and educational effect of non-majors through the visualized data of the spreadsheet. The proposed contents consisted of artificial neurons with sigmoid and ReLU activation functions, supervised learning data generation, supervised learning artificial neural network configuration and parameter optimization, supervised learning artificial neural network implementation and performance analysis using spreadsheets, and education satisfaction analysis. In this paper, considering the optimization of negative parameters for the sigmoid neural network and the ReLU neuron artificial neural network, we propose a training method for the four performance analysis results on the parameter optimization of the artificial neural network, and conduct a training satisfaction analysis.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1464-1473
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• 1990

Optimal design parameters are estimated from the sensitivity function and performance index variation. Suspension design modification for performance improvement and basic materials for practical applications are presented. The linear quarter model of a vehicle suspension is analyzed in order to represent the utilities of sensitivity analysis, and sensitivity function is determined in the frequency domain. The change of frequency response function is predicted, which depends on the design parameter variation and the property is verified by computer simulation. As an investigation results of sensitivity function for the vibrational amplitude of sprung mass to road profile input, it is shown that the most sensitive parameters are the suspension damping and the suspension stiffness. In order to identify the effects of these two parameters to the performance of suspension system, the performance index variation according to the changes of parameters is considered and then optimal design parameters are determined. It is verified that the system response is improved noticeably in the both of frequency and time domain after the design modification with the optimal parameters.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.4
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• pp.453-461
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• 1999

The estimation of fatigue life at the design stage is very important in order to arrive at feasible and cost effective solutions considering the total lifetime of the structure and machinery compo-nents. In this study the practical procedure of prediction of fatigue life by use of cumulative damage factors based on Miner-Palmgren hypothesis and probability density function is shown with a $135,000m^3$ LNG tank being used as an example. In particular the parameters of Weibull distribution taht determine the stress spectrum are dis-cussed. At the end some of uncertainties associated with fatigue life prediction are discussed. The main results obtained from this study are as follows: 1. The practical procedure of prediction of fatigue life by use of cumulative damage factors expressed in combination of probability density function and S-N data is proposed. 2. The calculated fatigue life is influenced by the shape parameter and stress block. The conser-vative fatigue design can be achieved when using higher value of shape parameter and the stress blocks divded into more stress blocks.

• Journal of the Chungcheong Mathematical Society
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• v.20 no.2
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• pp.97-107
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• 2007

Ramanujan gave six identities involving ${\theta}$-function expansion. We extended these identities by introducing a free parameter. We also give the interpretation of one of the identities using theory of partitions.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.95-104
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• 2007

We study stationary subdivision schemes based on radial basis function interpolation. Each scheme has a tension parameter, say ${\lambda}$, which actually belongs to the radial basis function. In particular, adapted subdivision rules on bounded intervals are developed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.788-792
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• 2010

The problem of delay-dependent and parameter-dependent robust stability condition for discrete-time uncertain singular systems with polytopic uncertainty and interval time-varying delay is considered. A new robust stability condition based on parameter-dependent Lyapunov function is derived in terms of LMI (linear matrix inequality). Moreover, the proposed robust stability condition is a general condition for both singular and non-singular systems. A numerical example is presented to demonstrate the effectiveness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.39-46
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• 1994

In this paper, three types of parameter update law which can be used in model reference adaptive control are suggested based on speed-gradient algorithm which was introduced by Fradkov. It is shown that the parameter update law which was proposed by Narendra is a special from of these laws and that proposed parameter update laws can insure the global stability under some conditions such as attainability and convexity. We also comment that the transfer function of reference model shoud be positive real for the realization of parameter update law.