• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.466-469
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• 1996

In this paper, we present the global minimization condition by an informal analysis of the Langevine competitive learning neural network. From the viewpoint of the stochastic process, it is important that competitive learning guarantees an optimal solution for pattern recognition. By analysis of the Fokker-Plank equation for the proposed neural network, we show that if an energy function has a special pseudo-convexity, Langevine competitive learning can find the global minima. Experimental results for pattern recognition of handwritten numeral data indicate the superiority of the proposed algorithm.

• Korean Institute of Interior Design Journal
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• v.20 no.2
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• pp.64-71
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• 2011

There are a method to analyze reactions or psychological condition and a method to observe visitor's behavioral reaction as methods to measure and evaluate humans' recognition behavior reaction of humans. The measure of the eye movement as a method to living body's reaction and psychological condition has an advantage to measure the information acceptance reaction of view recognition of the stimulus of view composition factors which has been used since a long time ago in other research areas, but almost not studies have been made on the exhibition views in museums. Therefore, on the premise of such recognition, this study aimed at obtaining various types of information through vision angles of visitor in exhibition space of an museum and judging space information, at measuring the condition of information acceptance through attention experiments and observation investigation of and finding out the disposition and characteristics so as to verify the relationship between the exhibition space and exhibition Method.

• Korean Journal of Occupational Health Nursing
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• v.17 no.2
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• pp.155-165
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• 2008

Purpose: The purpose of this study was to investigate the condition, recognition of breast feeding of 273 nurses. Method: Data was collected using a structured questionnaire form April to June 2007. The subjects were 273 nurses in Kyunggido. The data analysis was done with descriptive statistics, $x^2$-test procedures using SPSS/WIN 12.0 PC. Result: There are 23.9% of child day care center, 5.2% of rest room for women, 16.8% of breast feeding room in workplace. Rate of breast-feeding practice was 78.4% of nurses. The reasons why they could not perform the breast-feeding include mother's job(45.4%), lacking breast milk(25.8%). The characteristics of nurses found to be related breast-feeding include age, number of employers. Conclusion: The results showed that the rest supports of the work environment was insufficient to perform breast-feeding in the workplace. These results suggest that nursing intervention for employed mother's breast-feeding practice behavior promotion should focus on characteristics influencing factors on workplace. Also, efficient breast-feeding education program for employed mothers should be developed by continuous qualitative researches based on breast-feeding experiences of employed mothers.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.48-55
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• 2002

This paper deals with the sensing ability of the smart sensor that has the sensing ability to distinguish materials according to the input condition changing. This is a study of dynamic characteristics of sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. Experiments and analysis were executed to estimate ability to recognize objects according to the input condition. First, we developed the advanced smart sensor. Second, we developed the new method, which has the capability sensing of different materials. Dynamic characteristics of the smart sensor were evaluated relatively through a new $R_{SAI}$ method. According to frequency changing, influence of the smart sensor are evaluated through a new recognition index ($R_{SAI}$) that ratio of sensing ability index. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safely diagnosis of structure, etc.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.8
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• pp.568-574
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• 2015

The present study was conducted by using stereo pattern recognition method(SPR method) to measure the displacement and vibration of an airplane wing in flight condition. A SPR based measurement system was developed using two visible light stereo cameras. The visible light stereo images were processed to obtain marker points by adaptive threshold method and marker filtering technique. The marker points were used to reconstruct 3D point, displacement, and vibration data. The SPR system was installed on F-16 fighter. The wing displacement and vibration were measured in flight condition. Therefore, this paper presents a possibility that SPR based measurement system using visible light stereo camera can be very useful for measuring displacement and vibration of an airplane in flight condition.

• MALSORI
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• no.60
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• pp.29-45
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• 2006

We investigated whether the first syllable plays an important role in lexical access in Korean visual word recognition. To do so, one lexical decision task (LDT) and two form primed LDT experiments examined the nature of the syllabic neighborhood effect. In Experiment 1, the syllabic neighborhood density and the syllabic neighborhood frequency was manipulated. The results showed that lexical decision latencies were only influenced by the syllabic neighborhood frequency. The purpose of experiment 2 was to confirm the results of experiment 1 with form-primed LDT task. The lexical decision latency was slower in form-related condition compared to form-unrelated condition. The effect of syllabic neighborhood density was significant only in form-related condition. This means that the first syllable plays an important role in the sub-lexical process. In Experiment 3, we conducted another form-primed LDT task manipulating the number of syllabic neighbors in words with higher frequency neighborhood. The interaction of syllabic neighborhood density and form relation was significant. This result confirmed that the words with higher frequency neighborhood are more inhibited by neighbors sharing the first syllable than words with no higher frequency neighborhood in the lexical level. These findings suggest that the first syllable is the unit of neighborhood and the unit of representation in sub-lexical representation is syllable in Korea.

• Journal of Korea Multimedia Society
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• v.14 no.7
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• pp.866-871
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• 2011

In this paper, an improved method of hand detecting and hand gesture recognition is proposed, it can be applied in different illumination condition and complex background. We use Adaptive Skin Threshold (AST) to detect the areas of hand. Then the result of hand detection is used to hand recognition through the improved HMM algorithm. At last, we design a simple program using the result of hand recognition for recognizing "stone, scissors, cloth" these three kinds of hand gesture. Experimental results had proved that the hand and gesture can be detected and recognized with high average recognition rate (92.41%) and better than some other methods such as syntactical analysis, neural based approach by using our approach.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.57-65
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• 1997

The purpose of this paper is to propose the HMM (hidden markov model) based on multi-observation sequence for the isolated word recognition. The proosed model generates the codebook of MSVQ by dividing each word into several sections followed by dividing training data into several sections. Then, we are to obtain the sequential value of multi-observation per each section by weighting the vectors of distance form lower values to higher ones. Thereafter, this the sequential with high probability value while in recognition. 146 DDD area names are selected as the vocabularies for the target recognition, and 10LPC cepstrum coefficients are used as the feature parameters. Besides the speech recognition experiments by way of the proposed model, for the comparison with it, the experiments by DP, MSVQ, and genral HMM are made with the same data under the same condition. The experiment results have shown that HMM based on multi-observation sequence proposed in this paper is proved superior to any other methods such as the ones using DP, MSVQ and general HMM models in recognition rate and time.

• Speech Sciences
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• v.13 no.2
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• pp.75-84
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• 2006

Various methods have been proposed to overcome the problem of speech recognition in the noisy conditions. Among them, the model compensation methods like the parallel model combination (PMC) and Jacobian adaptation (JA) have been found to perform efficiently. The JA is quite effective when we have hidden Markov models (HMMs) already trained in a similar condition as the target environment. In a previous work, we have proposed an improved method for the JA to make it more robust against the changing environments in recognition. In this paper, we further improved its performance by compensating the delta-mean vectors and covariance matrices of the HMM and investigated its feasibility in the multi-model structure for the noisy speech recognition. From the experimental results, we could find that the proposed improved the robustness of the JA and the multi-model approach could be a viable solution in the noisy speech recognition.

• ETRI Journal
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• v.30 no.6
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• pp.865-867
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• 2008

A conventional environment adaptation for robust speech recognition is usually conducted using transform-based techniques. Here, we present a discriminative adaptation strategy based on a multi-condition-trained model, and propose a new method to provide universal application to a new environment using the environment's specific conditions. Experimental results show that a speech recognition system adapted using the proposed method works successfully for other conditions as well as for those of the new environment.