• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1161-1164
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• 2002

We propose a simple method that can recognize human emotion from monocular dance image sequences. The method only exploits the information within image sequences and does not require cumbersome attachments like sensors. This makes the method a simple, human-friendly one. Moreover, the method is more robust and efficient by taking into account the statistical property of image sequences based on PCA (Principal Component Analysis). The correct recognition rate in real-time is about 75% in a variety of experiments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.219-225
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• 2006

This paper studies on the visibility of dashboard in forklift. As part of the real setting devised for this study, 1. Important evaluation by males experience in forklift driving, 2. Icon cognition experiment, 3. Gage cognition experiment, subjects were asked to estimate the important evaluation, sketched to icon and gage position on the screen. Subjective evaluations were carried out by semantic differential method, sketch method, sketch method, then analyzed by consistency test, frequency rate and T-test. I gather the results concerning the relationship between consistent answers and cognition rates of dashboard understand the conditions which create a desired instrument panel.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.675-678
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• 1999

본 논문에서는 음소별 코드북 개수의 선택과 벡터 양자화에 따른 음소 인식률과 고립단어 인식률에 대하여 다룬다. 음성모델은 이산 확률 밀도를 갖는 DHMM(Discrete Hidden Markov Model)을 사용하였으며, 코드북 생성과 벡터 양자화 알고리즘으로는 K-means 알고리즘과 LBG(Linde, Buzo, Gray) 알고리즘을 사용하였다 음소별 코드북 개수와 벡터 양자화를 최적화함으로써 음소 인식률을 향상시킬 수 있으며, 그 결과 안정된 고립단어 인식률을 얻을 수 있다.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.619-626
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• 2018

Most publications confirm that an ecological interface is a very efficient tool to supporting operators in recognition of complex and unusual situations and in decision-making. The present article describes the experience of implementation of an ecological interface concept for visualization of material balance in a drum separator of RBMK-type NPPs. Functional analysis of the domain area was carried out and revealed main factors and contributors to the balance. The proposed ecological display was designed to facilitate execution of the most complicated cognitive operations, such as comparison, summarizing, prediction, etc. The experimental series carried out at NPPs demonstrated considerable reduction of operators' mental load, time of reaction, and error rate.

• Laser Solutions
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• v.2 no.3
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• pp.19-31
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• 1999

This paper introduces the monitoring scheme of laser welding quality using neural network. The developed monitoring scheme detects light signal emitting from plasma formed above the weld pool with optic sensor and DSP-based signal processor, and analyzes to give a guidance about the weld quality. It can automatically detect defects of laser weld and further give an information about what kind of defects it is, specially partial penetration and porosity among the interior defects. Those could be detected only by naked eyes or X-ray after welding, which needs more processes and costs in mass production. The monitoring scheme extracts four feature vectors from signal processing results of optical measuring data. In order to classify pattern for extracted feature vectors and to decide defects, it uses single-layer neural network with perceptron learning. The monitoring result using only the first feature vector shows confidence rate in recognition of 90%($\pm$5) and decides whether normal status or defects status in real time.

• Childhood Kidney Diseases
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• v.3 no.1
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• pp.104-108
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• 1999

Atypical hemolytic uremic syndrome associated with neuraminidase-producing Streptococcus pneumoniae usually associated with invasive infection such as fulminant pneumonia, sepsis, and meningitis and may occur earlier in lift and has a higher mortality rate than typical hemolytic uremic syndrome. We have experienced a 22-month-old female patient with hemolytic uremic syndrome associated with S. pneumoniae pneumonia and empyema. The patient was treated with ceftriaxone and washed red blood cell transfusion. As the disese course could be aggravated by the use of blood products containing anti-Tomsen-Friedenreich antigen, early recognition and sensible use of blood products such as washed RBC might lead to the improved outcome.

• Speech Sciences
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• v.15 no.2
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• pp.79-88
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• 2008

Recently demands for the speech technology-based products targeted for the mobile terminals such as cellular phones and PDA are rapidly increasing. And voting-based speaker identification algorithm is known to have a good performance in the mobile environment, since it works well with small amount of speaker training data. In this paper, we proposed a method to improve the performance of this voting based speaker identification system by using the observation confidence value which is derived from the function of SNR each frame. The proposed method is evaluated with ETRI cellular phone DB which is made for the speaker recognition task. The experimental results show that the proposed method has better performance of 2-3% identification rate than the conventional GMM method.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.127-130
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• 2000

Classification of Electroencephalogram(EEG) makes one of key roles in the field of clinical diagnosis, such as detection for epilepsy. Spectrum analysis using the fourier transform(FT) uses the same window to signals, so classification rate decreases for nonstationary signals such as EEG's. In this paper, wavelet power spectrum method using wavelet transform which is excellent in detection of transient components of time-varying signals is applied to the classification of three types of Event Related Potential(EP) and compared with the result by fourier transform. In the experiments, two types of photic stimulation, which are caused by eye opening/closing and artificial light, are used to collect the data to be classified. After choosing a specific range of scales, scale-averaged wavelet spectrums extracted from the wavelet power spectrum is used to find features by Back-Propagation(13P) algorithm. As a result, wavelet analysis shows superiority to fourier transform for nonstationary EEG signal classification.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.2
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• pp.87-92
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• 2006

This paper supplements shortcoming of radioactivity check by detecting defect of SWP weld zone using ultrasonic wave. Manufacture 2 stage robot detection systems that can follow weld bead of SWP by method to detect weld defects of SWP that shape of weld bead is complex for this as quantitative. Also, through signal processing ultrasonic wave defect signal system of GUI environment that can grasp easily existence availability of defect because do videotex compose. Ultrasonic wave signal of weld defects develops artificial intelligence style sightseeing system to enhance pattern recognition of weld defects and the classification rate using neural net. Classification of weld defects that do fan Planar defect and that do volume defect of by classify.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.33-42
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• 2005

In this paper, we propose a new training algorithm for improving pattern classification performance of ART neural network. The proposed train algorithm restricts unnecessary cluster generation and transition, applies the location extraction algorithm, and operates the reset system based on the agreement between the present learning pattern and the initial pattern. As a result, repetitive input of a pattern does not generate a new cluster and mis-recognition rate decreases.