• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.4
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• pp.356-365
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• 1988

In this paper, we describe an isolated words recognition system for Korean isolated digits based on a voiced -unvoiced decision algorithm and a frequency domain analysis. The algorithm first performs a voiced-unvoiced decision procedure for the begtinning part of each uttered work using the normalized log energy and zero crossing rate as decision parameters. Based on this decision,. each word is assigned to one of two classes. In order to identify the uttered word within each class, a dynamic time warping algorithm is applied using formant frequencies as the basis for the distance measure. We exploit a pole-zero analysis to measure formant frequencies in each frame. We have observed that pole-zero analysis can provide more accurate estimation of formant frequencies than analysis based on poles only. Experimental recognition rates of 97.3% illustrating the performance of the recognition system was achieved.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.22-28
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• 2017

With the recent development of technologies to manage vast amounts of data, data mining technology has had a major impact on all industries.. Data mining is the process of discovering useful correlations hidden in data, extracting executable information for the future, and using it for decision making. In other words, it is a core process of Knowledge Discovery in data base(KDD) that transforms input data and derives useful information. It extracts information that we did not know until now from a large data base. In the decision tree, c4.5 algorithm was used. In addition, the C4.5 algorithm was used in the decision tree to analyze the difference between frequency and mortality in the region. In this paper, the frequency and mortality of percutaneous coronary intervention for patients with heart disease were divided into regions.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.04a
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• pp.135-138
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• 2008

Many Victims and property damage are caused in fires. In this paper, an flame detection algorithm is proposed to early alarm fires. The proposed flame detection algorithm is based on 2-stage decision strategy of video processing. The first decision is to check with color distribution of input vidoe. In the second, the candidated region is settled as fire region with activity. As a result of simulation, it is shown that the proposed algorithm is useful for fire recognition.

• Journal of Power Electronics
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• v.8 no.1
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• pp.101-107
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• 2008

In this paper, the features extracted from vibration time signals are used to detect the bearing fault condition. The decision tree is applied to diagnose the bearing status, which has the benefits of being an expert system that is based on knowledge history and is simple to understand. This paper also suggests a genetic algorithm (GA) as a method to reduce the number of features. In order to show the potentials of this method in both aspects of accuracy and simplicity, the reduced-feature decision tree is compared with the non reduced-feature decision tree and the PCA-based decision tree.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.787-790
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• 2017

Data quality is the main issue in the classification problems; generally, the presence of noisy instances in the training dataset will not lead to robust classification performance. Such instances may cause the generated decision tree to suffer from over-fitting and its accuracy may decrease. Decision trees are useful, efficient, and commonly used for solving various real world classification problems in data mining. In this paper, we introduce a preprocessing technique to improve the classification accuracy rates of the C4.5 decision tree algorithm. In the proposed preprocessing method, we applied the naive Bayes classifier to remove the noisy instances from the training dataset. We applied our proposed method to a real e-commerce sales dataset to test the performance of the proposed algorithm against the existing C4.5 decision tree classifier. As the experimental results, the proposed method improved the classification accuracy by 8.5% and 14.32% using training dataset and 10-fold crossvalidation, respectively.

• Journal of the Korea Computer Industry Society
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• v.2 no.2
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• pp.195-202
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• 2001

In this paper, we show a study on how to model a phoneme of which acoustic feature is changed according to both left-hand and right-hand phonemes. For this purpose, we make a comparative study on two kinds of algorithms; a unit reduction algorithm and decision tree modeling. The unit reduction algorithm uses only statistical information while the decision tree modeling uses statistical information and Korean acoustical information simultaneously. Especially, we focus on how to model context-dependent phonemes based on decision tree modeling. Finally, we show the recognition rate when context-dependent phonemes are obtained by the decision tree modeling.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.15-31
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• 2002

This research suggests an interactive methodology for multiple objective linear programming problems to help the group select a compromising solution in the World Wide Web environment. Our methodology lessens the burden of group decision makers, which is one of necessary conditions of the web environment. Only the partial weak order of variables and objectives from the group decision makers are enough for searching the best compromising solution. For such a purpose, we expand the Dror and Gass algorithm to the group decision context. And we suggest the system architecture of a web-based GDSS for the Implementation of our methodology.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1447-1452
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• 1996

In this papre, a complex fuzzy adaptive decision feedback equalizer using the RLS algorithm is proposed. The proposed equalizer is based on the complex fuzzy adaptive equalizer. The 'IF'-part of the complex fuzzy adaptive decision feedback equalizer has membership functions which are characterized by the sate of decision feedback. The role of decision feedback is to reduce the computational complexity. Computer simulation shows that the proposed equalizer not only reduces the computational complexity but also improves the performance compared with the conventional complex fuzzy adaptive equalizers under the assumption of perfect knowledge of the linear and nonlinear channels. The effects of error propagation due to wrong decision feedback is also shown.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.271-274
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• 1996

In this paper a new determination scheme of linear decision function is proposed. In this scheme, the weights in linear decision function is obtained by genetic algorithm. The result considering balance between clusters as well as classification error can be obtained by properly selecting the fitness function of genetic algorithm in determination of linear decision function and this has the merit in applying this scheme to the construction of binary decision tree. The proposed scheme is applied to the artificial two dimensional data and real multi dimensional data. Experimental results show the usefulness of the proposed scheme.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.11-19
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• 2006

The recent video coding standard H.264 employs the rate-distortion optimization (RDO) method for choosing the best coding mode; however, it causes a large amount of encoding time. Thus, in order to reduce the encoding time, we need a fast mode decision algorithm. In this paper, we propose a fast inter mode decision algorithm considering quantization parameter (QP). The occurrence of best modes depends on QP. In order to reflect these characteristics, we consider the coded block pattern (CBP) which has 0 value when all quantized discrete cosine transform (DCT) coefficients are zero. We also use the early SKIP mode decision and early $16{\times}16$ mode decision methods. By computer simulations, we have verified that the proposed algorithm requires less encoding time than the fast inter mode decision method of the H.264 reference software for the Baseline and Main profiles by 19.6% and 18.8%, respectively.