• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.666-674
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• 2001

Classical methods to find a minimal set of rules based on the rough set theory are known to be ineffective in dealing with new instances added to the universe. This paper introduces an inductive learning algorithm for incrementally retrieving a minimal set of rules from a given decision table. Then, the algorithm is validated via simulations with two sets of data, in comparison with a classical non-incremental algorithm. The simulation results show that the proposed algorithm is effective in dealing with new instances, especially in practical use.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.135-139
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• 2001

There has been a study about the effective multimedia education using a computer following the appearance of a virtual space. Also, there has been an effort to connect the information & communication technology with education. The popular on-line lecture systems are mostly on English lecture sites. However, they just offer the VOD(Video On Demand) services ignoring students' convenience. To improve these week points, we design and implement the multimedia leaching system focusing on an efficient repeat-effect in order that students can control the Media Player by clicking a sentence on a web page. This paper presents the Editor and Player considering students' interest and the effective learning fruits. So users can easily make multimedia materials and use them to improve their English listening skill.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.594-596
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• 1997

This paper presents the speaker-dependent Korean isolated digit recognition system using advanced competitive learning. Since competitive learning algorithms are easy and simple to implement, they are used in various fields. The proposed recognition algorithm consists of three procedures: comparing winning number of codebook vectors, selecting the representative vector out of codebook vectors, and generating a new codebook with the representative vectors. In this paper, we use a sound blaster 16 for obtaining speech data. Speech data are sampled by 16 bits and 11 kHz sampling rate.

• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.441-449
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• 2018

Deep learning has been used for various processing centered on image recognition. One core algorithms of the deep learning, convolutional neural network is an deep neural network that specialized in image recognition. In this paper, we use a convolutional neural network to classify forest insects and propose an optimization method. Experiments were carried out by combining two weight initialization and six parameter update methods. As a result, the Xavier-SGD method showed the highest performance with an accuracy of 82.53% in the 12 different combinations of experiments. Through this, the latest learning algorithms, which complement the disadvantages of the previous parameter update method, we conclude that it can not lead to higher performance than existing methods in all application environments.

• School Mathematics
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• v.7 no.3
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• pp.303-318
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• 2005

If students can use mathematics to solve their problems and learn the mathematical knowledge through it, they may think mathematics useful and valuable. This study is for the teaching through problem solving in mathematics education, which I consider in terms of the problem-based learning and mathematical modeling. 1 think mathematical modeling is applied to teaching mathematics as a problem-based learning. So I developed the teaching model, and showed the example that students learn the formal and hierarchic mathematics through mathematical modeling.

• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.161-168
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• 2000

In the 21st century, we need to educate students who can perform their learning activity by themselves through free investigation and gathering information instead of providing a piece of knowledge to them directly. It is suggested that we should use Internet to bring up students who have the ability to study self-directedly. In this study, we designed a virtual English conversation class and implemented it using Web and DBMS to improve the students' self-directed learning ability who study English conversation in high school.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.107-119
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• 1996

In this paper, we propose multiple component neural network(MCNN) which learn partitioned patterns in each multiple component neural networks by reducing dimensions of input pattern vector using PCA (principal component analysis). Procesed neural network use Oja's rule that has a role of PCA, output patterns are used a slearning patterns on small component neural networks and we call it CBP. For simply not solved patterns in a network, we solves it by regenerating new CBP neural networks and by performing dynamic partitioned pattern learning. Simulation results shows that proposed MCNN neural networks are very small size networks and have very fast learning speed compared with multilayer neural network EBP.

• English Language & Literature Teaching
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• v.7 no.2
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• pp.77-102
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• 2002

Factors affecting foreign language learning task are diverse in nature due to the different social and cultural backgrounds so that learners have to somehow use strategies and expressions to adjust diverse factors to their learning environments. The main purpose of this paper is to show how important NNS vs. NNs interaction through CCDL can be in their enhancement of English proficiency by giving examples from their chatting conversation(written conversation) data collected for over two semesters. Chatting as a means of synchronous communication interaction between students from two different cultural backgrounds can act as a predictor of foreign language achievement. Chatting and Telemeet activities have their own advantages in enhancing communicative competence when learning English. By engaging in these synchronous communication activities learners of English from different cultural backgrounds can acquire unique strategies and expressions from which they learn from each other. In short, this study advocates the importance of strategies and patterns foreign language learners can acquire from interaction among culturally different peer groups.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.1
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• pp.42-50
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• 1997

Vector quantization has shown to be useful for compressing data related with a wide rnage of applications such as image processing, speech processing, and weather satellite. Neural networks of images this paper propses a efficient neural network learning algorithm, called learning count control algorithm based on the frquency sensitive learning algorithm. This algorithm can train a results more codewords can be assigned to the sensitive region of the human visual system and the quality of the reconstructed imate can be improved. We use a human visual systrem model that is a cascade of a nonlinear intensity mapping function and a modulation transfer function with a bandpass characteristic.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.721-727
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• 2003

This study designed and implemented a system to extract of vowel from a word. The system is comprised of a voice feature extraction module and a neutral network module. The voice feature extraction module use a LPC(Linear Prediction Coefficient) model to extract a voice feature from a word. The neutral network module is comprised of a learning module and voice recognition module. The learning module sets up a learning pattern and builds up a neutral network to learn. Using the information of a learned neutral network, a voice recognition module extracts a vowel from a word. A neutral network was made to learn selected vowels(a, eo, o, e, i) to test the performance of a implemented vowel extraction recognition machine. Through this experiment, could confirm that speech recognition module extract of vowel from 4 words.