• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4624-4642
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• 2014

Image compression is a popular research issue that focuses on the problems of reducing the size of multimedia files. Vector Quantization (VQ) is a well-known lossy compression method which can significantly reduce the size of a digital image while maintaining acceptable visual quality. A locally adaptive scheme (LAS) was proposed to improve the compression rate of VQ in 1997. However, a LAS needs extra indicators to indicate the sources, consequently the compression rate of LAS will be affected. In this paper, we propose a novel method to eliminate the LAS indicators and so improve the compression rate. The proposed method uses the concept of data hiding to conceal the indicators, thus further improving the compression rate of LAS. From experimental results, it is clearly demonstrated that the proposed method can actually eliminate the extra indicators while successfully improving the compression rate of the LAS.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.87-90
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• 1988

This paper reports a simple posteriori error estimate method for adaptive finite element mesh generation using quadratic shape function especially for the magnetic field problems. The elements of quadratic shape function have more precise solution than those of linear shape function. Therefore, the difference of two solutions gives error quantity. The method uses the magnetic flux density error as a basis for refinement. This estimator is tested on two dimensional problem which has singular points. The estimated error is always under estimated but in same order as exact error, and this method is much simpler and more convenient than other methods. The result shows that the adaptive mesh gives even better rate of convergence in global error than the uniform mesh.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.351-358
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• 1999

The structural responses of underground structures are examined in probability by using the elasto-plastic stochastic finite element method in which the spatial distributions of material properties are assumed to be stochastic fields. In addition, the adaptive importance sampling method using the response surface technique is used to improve simulation efficiency. The method is found to provide appropriate information although the nonlinear Limit State involves a large number of basic random variables and the failure probability is small. The probability of plastic local failures around an excavated area is effectively evaluated and the reliability for the limit displacement of the ground is investigated. It is demonstrated that the adaptive importance sampling method can be very efficiently used to evaluate the reliability of a large scale stochastic finite element model, such as the underground structures located in the multi-layered ground.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.4
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• pp.101-107
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• 1996

This test was performed on the hydraulic automatic gauge control(AGC) system of adaptive mass flow method. Fundamental purpose of this study are performance evaluation of this AGC system under the actual rolling condition. It was concluded that the response of AGC system depends on the dynamic characteristics of a reel motor or roll position. The test results are as follows : 1) The control method of reel motor current is better than than of the roll position as AGC system. 2) The more steel strip thickness of delivery side is thick, the larger the gauge deviation is large, and the more it is thin, the larger the gauge deviation rate is large. 3) Because the gauge deviation is large at acceleration and deceleration speed than steady speed, so AGC system is better to adopt over 50m/min. By applying this AGC system, not only the accurary in strip thickness were improved but also productivity was improved dramatically.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.129-136
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• 1994

In this paper an adaptive moving method of the search region tracking the motion is proposed. The search region in BMA is determined by the capability of hardware implementation and the degree of motion. But once determined nothing can be changed during coding procedure. In this paper we predict the level of motion of the current block using motion vectors of previous frames without overhead information and change the location of the search region according to the level of the motion predicted. In short the proposed method can be archieved the dsirable effect such that the size of search region gets large when the motion is large. Results of experiments show that prediction efficiency has been improved by using adaptive moving method resulting in reduced prediction error in the blocks with large motion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.494-497
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• 2002

In this paper, we proposed a control method of an unknown nonlinear system using a dynamical neural network. The proposed method performs for a nonlinear system with unknown system, identification with using the dynamical neural network, and then a nonlinear adaptive controller is designed with these identified informations. In order to verify the effectiveness of the proposed method, we simulated one-link manipulator. The simulation results showed the effectiveness of using the dynamical neural network in the adaptive control of one-link manipulator.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.4
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• pp.161-167
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• 2012

Energy conversion systems such as power inverters and converters are basically significant in establishing photovoltaic power systems to enhance power effectiveness. This paper proposes a new converter control method by using the Lyapunov redesign approach. We construct the proposed control mechanism linearly composed of nominal control and auxiliary control laws. The former is generally designed through a well-known power electronic technology and the latter is implemented to compensate real-time control error due to uncertain natures of converter systems in practice. For realizing adaptive control capability in the proposed control mechanism, a control parameter vector is estimated by utilizing a steepest descent based optimization method. We carry out numerical simulation with Matlab(c) software to demonstrate reliability of the proposed converter control system and conduct a comparative study to prove its superiority by comparing with a generic converter control methodology.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.7
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• pp.696-705
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• 1991

This paper describes the procedures for pre-tuning and re-tuning the gains of PI controller based on output patterns -output error integral- of the unknown process which may not have any information, for example, system order, deadtime, time constant, etc. The key ideas of the proposed adaptive scheme are as follows. The scheme determines the initial gains by using ZNM (Ziegler-Nichols Method) with relay feedback, and then the adaptive algorithms by pattern recognition are introduced for re-runing the PI gains with on-line scheme whenever control conditions are changed. Because, among the various auto-tuning procedures, ANM with relay feedback has the difficulty in re-tuning with on-line and Bristol method has no comment on initial settings and has variables to pre-determine, which makes the algorithm comples, the proposed methods have the combined scheme with above two procedures to recover those problems. And this paper proposes a simple way to determine adaptive constant in Bristol method. To show the validity of the proposed method, an example is illustrated by computer simulation and a laboratory process, heat exchanger, is experimented.

• Speech Sciences
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• v.7 no.4
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• pp.49-57
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• 2000

This paper proposes an effective decision method focused on evaluating the 'stress position'. Conventional methods usually extract the acoustic parameters and compare them to references in absolute scale, adversely producing unstable results as testing conditions change. To cope with environmental dependency, the proposed method is designed to be model-based and determines the stressed interval by making relative comparison over candidates. The stressed/unstressed models are then induced from normal phone models by adaptive training. The experimental results indicate that the proposed method is promising, and that it is useful for automatic detection of stress positions. The results also show that generating the stressed/unstressed model by adaptive training is effective.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1249-1265
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• 1991

In this paper, a fast and adaptive feature extraction algorithm for textured image segmentation is proposed. First, a conventional algorithm to extract the statistical texture features are described and we obtain the recursive equations from that conventional method and it is used for extraction of sevaral texture features. And also we propose the adaptive algorithm which extract the texture features. To evaluate the performance of proposed algorithm, we apply the proposed method to artificial texture images. From the results of computer simulation, the proposed method is superior to the conventional one.