• Annual Conference on Human and Language Technology
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• 2005.10a
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• pp.97-104
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• 2005

교차언어 검색 과정에서는 질의나 문서의 언어를 일치시키기 위한 변환 과정이 필수적이며, 이런 변환 과정에서 어휘의 중의성으로 인해 하나의 어휘에 대응하는 다수의 대역어가 생성됨으로써 사용자의 정보 욕구를 왜곡시켜 검색의 성능을 저하시킬 수 있다. 본 논문에서는 어휘 중의성 문제를 해결하기 위해서 질의의 문맥 정보를 이용하여 변환 질의의 확률을 구함으로써 중의성을 해소하는 방식을 제시하고, 질의의 길이, 중의도, 중의성을 가진 어휘의 비율 등에 따라서 성능이 어떻게 변하는지 비교함으로써 이 방법의 장점과 단점을 분석한다. 또한 현재의 단점을 보완하기 위한 차후 연구 방향을 제시한다.

• Communications of Mathematical Education
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• v.27 no.3
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• pp.205-220
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• 2013

In this research, in order to investigate the principles for the development of mathematics textbook for decision-making based on storytelling, we conceptualized the educational meaning of decision-making and specified the principles and the methods for the textbook based on decision-making. We illustrated the principles and the methods by the cases from the model textbook for the conditional probability that we have developed. We discussed the implication for the future development and implementation of mathematics textbook for decision-making based on storytelling.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.369-372
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• 1998

본 논문은 어휘독립(Vocabulary-Independent) 환경에서 별도의 훈련과정 없이 인식대상 어휘를 추가 및 변경할 수 있는 가변어휘(Variable Vocabulary) 음성인식에 관한 연구를 다룬다. 가변어휘 인식은 처음에 대용량 음성 데이터베이스(DB)로 음소모델을 훈련하고 인식대상 어휘가 결정되면 발음사전에 의거하여 음소모델을 연결함으로써 별도의 훈련과정 없이 인식대상 어휘를 변경 및 추가할 수 있다. 문맥 종속형(Context-Dependent) 음소 모델인 triphone을 사용하여 인식실험을 하였고, 인식성능의 비교를 위해 어휘종속 모델을 별도로 구성하여 인식실험을 하였다. Unseen triphone 문제와 훈련 DB의 부족으로 인한 모델 파라메터의 신뢰성 저하를 방지하기 위해 state-tying 방법 중 음성학적 지식에 기반을 둔 tree-based clustering(TBC) 기법[1]을 도입하였다. Mel Frequency Cepstrum Coefficient(MFCC)와 대수에너지에 기반을 둔 3 가지 음성특징 벡터를 사용하여 인식 실험을 병행하였고, 연속 확률분포를 가지는 Hidden Markov Model(HMM) 기반의 고립단어 인식시스템을 구현하였다. 인식 실험에는 22 개 부서명 DB[3]를 사용하였다. 실험결과 어휘독립 환경에서 최고 98.4%의 인식률이 얻어졌으며, 어휘종속 환경에서의 인식률 99.7%에 근접한 성능을 보였다.

• Journal of the Korean Society of Propulsion Engineers
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• v.16 no.4
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• pp.33-41
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• 2012

The aim of the study is to investigate the method to estimate a shelf life of KM6 single base propellant by stochastic gamma process model. The state failure level is assumed that the degradation content of stabilizer is below 0.8%. The constant of time dependent shape function and the scale parameter of stationary gamma process are estimated by moment method. The state distribution at each storage time can be shown from probability density function of deterioration. It is estimated that the $B_{10}$ life, a time at which the cumulative failure probability is 10%, is 25 years and the $B_{50}$ life is 36 years from cumulative failure distribution function curve. The $B_{50}$ life can be treated as the average shelf life from the practical viewpoint and the lifetime can be expressed as distribution curve by using stochastic process theory.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.167-172
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• 2012

In vocabulary recognition using HMM(Hidden Markov Model) by model for the observation of a discrete probability distribution indicates the advantages of low computational complexity, but relatively low recognition rate has the disadvantage that require sophisticated smoothing process. Gaussian mixtures in order to improve them with a continuous probability density CHMM (Continuous Hidden Markov Model) model is proposed for the optimization of the library system. In this paper is system configuration thread control in recognition Gaussian mixtures model provides a model to optimize of the CHMM vocabulary recognition. The result of applying the proposed system, the recognition rate of 98.1% in vocabulary recognition, respectively.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.32-36
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• 1999

본 연구에서는 대공 무기체계의 성능평가를 위한 시뮬레이션 모델의 개발로서 능력추정을 위한 수식의 전개와 전산프로그램을 개발하고 예제를 통하여 능력산출 예를 보였다. 본 연구에서 고려된 시뮬레이션 방법으로 Mon Carlo 시뮬레이션과 Karman Filtering을 사용하였다. 본 모델의 주요 단계로서 1) 가장 최단 경로에서의 표적과 탄두간의 상대 속도와 위치를 결정하고, 2) 표적의 탄두에 대한 취약면적을 산출하고 3) 마지막으로 표적살상 확률을 산정하는 과정의 단계에 따라 개발되었다.

• Journal of the Korean Geotechnical Society
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• v.19 no.6
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• pp.151-160
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• 2003

The stability of the designed rock slope is analysed based on two kinds of shear strength model. Besides the deterministic analysis, a probabilistic approach on Monte Carlo simulation is proposed to deal with the uncertain characteristics of the discontinuity and the results obtained from two models are compared to each other. To carry out the research of characteristics of the discontinuity, BIPS, DOM Scanline survey data and direct shear test data are used, and chi-square test is used for determining the probability distribution function. The rock slope is evaluated to be stable in the deterministic analysis, but in the probabilistic analysis, the probability of failure is more than 5%, so, it is considered that the rock slope is unstable. In the shear strength models, the probability of the failure based on the Mohr-Coulomb model(linear model) is higher than that of the Barton model. It is supported by the fact that the Mohr-Coulomb model is more sensitive to block size than the Barton model. In fact, there is no reliable way to estimate the unit cohesion of the Mohr-Coulomb model except f3r back analysis and in the case of small block failure in the slope, Mohr-Coulomb model may excessively evaluate the factor of the safety. So, the Barton model of which parameters are easily acquired using the geological survey is more reasonable for the stability of the studied slope. Also, the selection of the proper shear strength model is an important factor for slope failure analysis.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.51-61
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• 2009

This paper analyzes the throughput of DCF protocol at the MAC layer in the 802.11a wireless LAN. The throughput of DCF protocol is related on probability of backoff, depends on retransmission of each terminal. This paper applied to nonmarcov discrete model for each terminal BER in the base station versus the packet throughput is progressing with the data rate of 6,12,24,54 Mbps, We find the fact that the less the data rate be the higher the throughput. We also find from the throughput calculation by means of traffic intensity in OFDM wireless LAN.

• The Journal of the Acoustical Society of Korea
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• v.24 no.7
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• pp.410-415
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• 2005

Recently, most of the speaker verification systems are based on the pattern recognition approach method. And performance of the pattern-classifier depends on how to classify a variety of speakers' feature parameters. In order to classify feature parameters efficiently and effectively, it is of great importance to enlarge variations between speakers and effectively measure distances between feature parameters. Therefore, this paper would suggest the positively mixed model scheme that can enlarge inter-speaker variation by searching the individual model with world model at the same time. During decision procedure, we can maximize inter-speaker variation by using the proposed mixed model scheme. We also make use of a symbol probability weighting function in this system so as to reduce vector quantization errors by measuring symbol probability derived from the distance rate of between the world codebook and individual codebook. As the result of our experiment using this method, we could halve the Detection Cost Function (DCF) of the system from $2.37\%\;to\;1.16\%$.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.358-371
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• 2003

Automatic word spacing is a process of deciding correct boundaries between words in a sentence including spacing errors. It is very important to increase the readability and to communicate the accurate meaning of text to the reader. The previous statistical approaches for automatic word spacing do not consider the previous spacing state, and thus can not help estimating inaccurate probabilities. In this paper, we propose two statistical word spacing models which can solve the problem of the previous statistical approaches. The proposed models are based on the observation that the automatic word spacing is regarded as a classification problem such as the POS tagging. The models can consider broader context and estimate more accurate probabilities by generalizing hidden Markov models. We have experimented the proposed models under a wide range of experimental conditions in order to compare them with the current state of the art, and also provided detailed error analysis of our models. The experimental results show that the proposed models have a syllable-unit accuracy of 98.33% and Eojeol-unit precision of 93.06% by the evaluation method considering compound nouns.