• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.439-442
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• 1997

In our research, we will extract diagnostic parameters by LPC method and wavelet transform. Then, we will design artificial neural network which is based on RBF that can express input features in terms of fuzzy. Because PVC(Premature Ventricular Contraction) has possibility to cause heart attack, the detection of PVC is a very significant problem. To deal with this problem, LPC method which gives different coefficients or different morphologies and wavelet transform which has superior localization nature of time-frequency, are used to extract effective parameters or classification of normal and PVC. Because RBF network can allocate an input feature to the membership degree of each category, total system will be more flexible.

• International Journal of Quality Innovation
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• v.2 no.2
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• pp.58-68
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• 2001

This paper proposes a method for quantifying the types of quality elements proposed by Kano; namely: attractive quality, one-dimensional quality, and must-be quality. Kano's classification of required quality has helped us improve our thinking in product development. However, his classification is conceptual rather than quantitative, and the conventional techniques of questionnaire and group interview cannot provide quantification of the relationship between the degree of customer satisfaction and the degree of sufficiency of required qualities. This paper describes how a quality element under Kano's quality model can be expressed as a utility function, and describes an application to quality design of a cellular phone.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.5
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• pp.269-277
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• 2000

We propose two new types multi-stage blind clustering equalizers for QAM demoulation, which are called a complex classification algorithm(CCA) and a radial basis function algorithm(RBFA). The CCA uses a clustering technique based on the joint gaussian probability function and computes separately the real part and imaginary part for simple implementation as well as less computation. In order to improve the performance of CCA, the Dual-Mode CCA(DMCCA) incorporates the CCA tap-updating mode with the decision-directed(DD) mode. The RBFA reduces the number of cluster centers through three steps using the classification technique of RBF and then updates the equalizer taps for QAM demodulation. Test results on 16-QAM confirm that the proposed algorithms perform better the conventional multi-state equalizers in the senses of SER and MSE under multi-path fading channel.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.1 no.2
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• pp.162-172
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• 1989

The steady one dimensional heat flow method was used for the measurement of thermal conductivity of kaolin. The effects of the classification, density and moisture content on the thermal conductivity were studied experimentally for the 9 classes of kaolin in Korea. As the results of this study, it was found that the classification did not effect the thermal conductivity, and the conductivity increased as the density and moisture content increased. The correlation equation of the thermal conductivity as a function of the density increase rate was found and the values for the thermal conductivity as a function of moisture content were recommended.

• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.1
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• pp.268-272
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• 2006

In this study, when physician make a diagnosis of Sasang constitution of patients, anthropometric data are applied to seek the classification function into Sasang constitution. Data used in the analysis are the anthropometric data of 550 patients who had been treated in nine oriental medical hospital, and our data have no missing value in 12 anthropometric variables. In order to improve the accuracy of classification function into Sasang constitution, we consider one method of variable transformation of anthropometric data based on oriental medicine.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.417-422
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• 1998

This paper presents a method of object classification from dynamic image based on fuzzy inference algorithm which is suitable for low speed such as, conveyor, uninhabited transportation. At first, by using feature parameters of moving object, fuzzy if - then rule that can be able to adapt the wide variety of surroundings is developed. Secondly, implication function for fuzzy inference are compared with respect the proposed algorithm. Simulation results are presented to testify the performance and applicability of the proposed system.

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.96-98
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• 2003

1. Standard and regulations for functional food evaluation cases form overseas (1) Japan For food function indication, Food Nutrition Improvement Act was amended in September 1991 and they managed functional food after setting specific health food in one of classification of special functional foods. For manification of raw material usage, the classification of health functional foods was performed by their application on: the control of internal organ status, cholesterol, blood pressure, mineral absorption, and prevention of dental caries. (omitted)

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.522-526
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• 1993

The first objective of this study is to derive an automated method that minimizes the number of spline regions and optimizes the locations of the knots to provide and adequate fit of a given nonlinear function. This has been accomplished by the development of the Optimal Spline Method discussed herein. The second objective is to apply the derived automated method to an important application. This objective has been accomplished by the successful application of the Optimal Spline Method to ship classification.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.115.3-115
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• 2001

In this paper, discrete-time cellular neural networks are designed in order to function as associative memories by using Hebbian learning rule and non-cloning template. The proposed method has a very simple structure to design and to learn. Weights are updated by the connection between the neuron and its neighborhood. In the simulation, the proposed method is applied to the classification of a traffic sign pattern.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.917-922
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• 1990

Pattern classification is an essential step in automatic robotic assembly which joins together finite number of seperated industrial parts. In this paper, a fast and systematic algorithm for classifying occlusion-free objects is proposed, using the notion of incremental circle transform which describes the boundary contour of an object as a parametric vector function of incremental elements. With similarity transform and line integral, normalized determinant curve of an object classifies each object, independent of position, orientation, scaling of an object and cyclic shift of the stating point for the boundary description.