• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1495-1500
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• 2015

We obtain means and variances of max {X, Y} and min {X, Y} in the underlying Morgenstern type bivariate uniform variables X and Y with same scale parameters and different scale parameters respectively. And we obtain the conditional expectations in the underlying Morgenstern type bivariate uniform variables. Here, we shall consider the conditional expectations to know the dependence of one variable on the other variable and we consider the behaviors of means and variances of max {X, Y} and min {X, Y} with respect to changes in means, variances, and the correlation coeffcient of the underlying Morgenstern type bivariate uniform variables.

• Computers and Concrete
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• v.3 no.2_3
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• pp.177-195
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• 2006

Slipforming is a construction method in which the forms move continuously during the placement of concrete. This paper presents the development of a computer aided program designated as "CADSLIPFORM" for slipforming operations. The program incorporates maturity methods for the prediction of initial setting times of slipform concrete layers using laboratory data (time-temperature histories and setting times of concrete mixtures at different temperatures) and generates slipform mock-up times. The performance of CADSLIPFORM is validated by comparing simulated mock-up times with those estimated in the field through conventional hard front by rod (R) method. Moreover, the program versatility is demonstrated by illustrating mock-up simulations for different cases with variable slipform parameters such as: number and thickness of concrete layers, concrete temperature (simulating variable setting times) and slipform speed. The program also incorporates the choice of Freiesleben Hansen & Pederson (FHP) and Carino & Tank (CT) maturity functions. CADSLIPFORM can assist user to develop reliable schedule of slipforming operation suitable for a specific project by optimizing various slipform parameters.

• Structural Engineering and Mechanics
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• v.28 no.3
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• pp.263-280
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• 2008

Information on the distribution of the basic random variable is essential for the accurate analysis of structural reliability. The usual method for determining the distributions is to fit a candidate distribution to the histogram of available statistical data of the variable and perform approximate goodness-of-fit tests. Generally, such candidate distribution would have parameters that may be evaluated from the statistical moments of the statistical data. In the present paper, a cubic normal distribution, whose parameters are determined using the first four moments of available sample data, is investigated. A parameter table based on the first four moments, which simplifies parameter estimation, is given. The simplicity, generality, flexibility and advantages of this distribution in statistical data analysis and its significance in structural reliability evaluation are discussed. Numerical examples are presented to demonstrate these advantages.

• ETRI Journal
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• v.32 no.4
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• pp.548-554
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• 2010

The transcutaneous energy transmission system (TETS) composed of a Class-E amplifier may operate at a state away from the optimum power transmission due to the load variation. By introducing the feedback-loop technique, the TETS can keep the optimum state with constant output voltage by adjusting the important design parameters, that is, the duty ratio and frequency of the driving signal and the supply voltage. The relations between these adjusted parameters and the load are investigated. The effectiveness of the feedback technique is validated through a design example with a variable load parameter. The experimental results show that the Class-E amplifier in the feedback loop can keep operating at the optimum state under the condition of up to 50 percent variation of the load value.

• Speech Sciences
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• v.11 no.4
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• pp.75-88
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• 2004

In this paper, we propose a new approach to sequential linear regression adaptation of continuous density hidden Markov models (CDHMMs) based on transformation space model (TSM). The proposed TSM which characterizes the a priori knowledge of the training speakers associated with maximum likelihood linear regression (MLLR) matrix parameters is effectively described in terms of the latent variable models. The TSM provides various sources of information such as the correlation information, the prior distribution, and the prior knowledge of the regression parameters that are very useful for rapid adaptation. The quasi-Bayes (QB) estimation algorithm is formulated to incrementally update the hyperparameters of the TSM and regression matrices simultaneously. Experimental results showed that the proposed TSM approach is better than that of the conventional quasi-Bayes linear regression (QBLR) algorithm for a small amount of adaptation data.

• Proceedings of the KIEE Conference
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• 1983.07a
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• pp.135-138
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• 1983

This paper studies a variable structure adaptive model following control system which can control a plant in which the parameters of the controlled plant can not be estimated because they vary with time and in which the controlled plant has noise. The values of the feedback gain matrices for given states are obtained the equivalent control law, and the adaptive controller has been designed using the adaptive mechanism which switches the matrices. The adaptive controller minimizes the state error vector, that is, the difference between the state vector of the model and the state vector of the controlled plant. A controlled plant which has time varying parameters, a controlled plant which has only noise, and a controlled plant which has both have been controlled by the designed adaptive controller. The continuous single input-output system has been analysed by computer. This control system may be used to control practical systems by the addition of a microcomputer.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1476-1478
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• 1999

A musculotendon model is proposed to predict muscle force during muscle fatigue due to the continuous functional electrical stimulation(FES). Muscle fatigue dynamics can be modeled as the electrical admittance of muscle fibers and included in activation dynamics based on the{{{{ { Ca}^{2+ } }}}} kinetics. The admittance depends on the fatigue variable that monotonically increase or decrease if electrical pulse exists or not, and on the stimulation parameters and the number of applied pulses. In the response of the change in activation the normalized Hill-type contraction dynamics connected with activation dynamics decline the muscle shortening velocity and thus its force under muscle fatigue. The computer simulation shows that the proposed model can express the muscle fatigue and its recovery without changing any stimulation parameters.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.654-657
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• 2000

In the winding system, the constant tension control is too important. In this study, we've used a variable PID system as a function of a radius of winding roll. As a result, it was possible to measure a winding roll radius in the real time by making a mathematical model for measuring a winding roll radius. Finally, we've compared PID parameters as a function of winding roll radius after getting PID parameters in terms of the Ziegler & Nichols(ZN) method.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.12
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• pp.691-696
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for induction motor speed control. When induction motor is continuously used long time, its electrical and mechanical Parameters will change, which degrade the Performance of PID controller considerably. This Paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using dSPACE(DS1102) board are performed to verify the effectiveness of the proposed scheme.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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• pp.142-147
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• 1998

Recently, 8 kb/s CS-ACELP coder of G.729 is atandardized by ITU-T SG15 and it has been reported that the speech quality of G729 is better than or equal to that of 32kb/s ADPCM. However G.729 is the fixed rate speech coder, and it does not consider the property of voice activity in mutual conversation. If we use the voice activity, we can reduce the average bit rate in half without any degradations of the speech quality. In this paper, we propose an efficient variable rate algorithm for G.729. The variable rate algorithm consists of two main subjects, the rate determination algorithm and algorithm, we combine the energy-thresholding method, the phonetic segmentation method by integration of various feature parameters obtained through the analysis procedure, and the variable hangover period method. Through the analysis of noise features, the 1 kb/s sub rate coder is designed for coding the background noise signal. So, we design the 4 kb/s sub rate coder for the unvoiced parts. The performance of the variable rate algorithm is evaluated by the comparison of speed quality and average bit rate with G.729. Subjective quality test is also done by MOS test. Conclusively, it is verified that the proposed variable rate CS-ACELP coder produced the same speech quality as G.729, at the average bit rate of 4.4 kb/s.