• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.65-75
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• 2003

In these days, public transportation has become important because of serious traffic congestion. But. there are few researches in public transportation compared with researches in auto. Accordingly, the purpose of paper is development of transit assignment model, which considers features of public transportation, time table, transfer capacity of vehicle, common line, etc. The transit assignment model developed in this paper is composed of two parts. One part is search for optimum path, the other part is network loading. A Genetic algorithm has been developed in order to search for alternative shortest path set. After the shortest paths have been obtained in the genetic algorithm, Logit-base stochastic loading model has been used to obtain the assigned volumes.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.127-134
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• 2010

In continuous vocabulary recognition system by probability distribution of clustering method has used model parameters of an advance estimate to generated each contexts for phoneme data surely needed but it has it's bad points of gaussian model the accuracy unsecure of composed model for phoneme data. To improve suggested probability distribution mixed gaussian model to optimized that phoneme data search supported configuration thread system. This paper of configuration thread system has used extension facet classification user phoneme configuration thread information offered gaussian model the accuracy secure. System performance as a result of represent vocabulary dependence recognition rate of 98.31%, vocabulary independence recognition rate of 97.63%.

• Journal of the Korean association of regional geographers
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• v.13 no.6
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• pp.712-723
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• 2007

The objective of this paper is to search the factors inducing the visitors to revisit in Bangeo Festival of Jeju region. To get this objective, this study analyzed the data with the Multinomial Logit Model applied dependent variable to intention of revisit. As a result, 'festival program' factor is the most important thing and if the factor increases by 1 unit, the probability of 'revisit' can be increased by 5.255 times than the probability of 'no revisit'. Secondly, the next significant factors are 'festival convenience' and 'festival recognition in advance'. So the providers of the festival will intend to prepare the festival focused on the important factor proposed by this results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6A
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• pp.586-592
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• 2006

In this paper, a novel detection method called the joint multiple frequency cell (JMFC) detection is addressed for spread spectrum code acquisition in the presence of residual Doppler frequency offset (RDFO). When the RDFO exists, the correlation peak used for detection during the acquisition process is split into several lower neighboring peaks, resulting in severe degradation in the detection performance, and consequently, in the overall acquisition performance. In the JMFC detection, a decision variable for detection is formed by combining several consecutive correlator outputs, so that the reduction in the correlation value due to the RDFO can be alleviated. Numerical results show that the proposed scheme can offer better detection performance over the conventional scheme based on the cell-by-cell detection.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.125-132
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• 2010

In vocabulary recognition has unseen tri-phone appeared when recognition training. This system has not been created beginning estimation figure of model parameter. It's bad points could not be created that model for phoneme data. Therefore it's could not be secured accuracy of Gaussian model. To improve suggested Gaussian model to optimized method of model parameter using probability distribution. To improved of confidence that Gaussian model to optimized of probability distribution to offer by accuracy and to support searching of phoneme data. This paper suggested system performance comparison as a result of recognition improve represent 1.7% by out-of vocabulary rejection algorithm using normalization confidence.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.387-391
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• 2008

For the detection of moving objects, background subtraction methods are widely used. In case the background has variation, we need to update the background in real-time for the reliable detection of foreground objects. Gaussian mixture model (GMM) combined with probabilistic learning is one of the most popular methods for the real-time update of the background. However, it does not work well in the complex and dynamic backgrounds with high traffic regions. In this paper, we propose a new method for modelling and updating more reliably the complex and dynamic backgrounds based on the probabilistic learning and the layered processing.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.565-570
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• 2021

A soft-decision decoding scheme of a channel code for correcting an error occurring in a receiver of a digital communication systems is proposed. A method for efficiently decoding by use of the linear and arithmetic structure of linear block codes is presented. In this way, the probability of decoding errors has been reduced. In addition, it is possible to reduce the complexity of decoding as well. Sufficient conditions for achieving optimal decoding has been derived. As a result, the sufficient conditions enable efficient search for candidate codewords. With the proposed decoding scheme, we can effectively perform the decoding while lowering the block error probability.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.530-536
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• 2021

Recently, due to the development of deep learning, end-to-end speech recognition, which directly maps graphemes to speech signals, shows good performance. Especially, among the end-to-end models, conformer shows the best performance. However end-to-end models only focuses on the probability of which grapheme will appear at the time. The decoding process uses a greedy search or beam search. This decoding method is easily affected by the final probability output by the model. In addition, the end-to-end models cannot use external pronunciation and language information due to structual problem. Therefore, in this paper conformer with lexicon transducer is proposed. We compare phoneme-based model with lexicon transducer and grapheme-based model with beam search. Test set is consist of words that do not appear in training data. The grapheme-based conformer with beam search shows 3.8 % of CER. The phoneme-based conformer with lexicon transducer shows 3.4 % of CER.

• Korean Journal of School Psychology
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• v.17 no.2
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• pp.223-241
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• 2020

The purpose of this study was to explore the latent profiles of social achievement goals and to investigate the differences in peer status (perceived popularity, social preference) and aggression (overt, relational, cyber) among those profile groups. Social achievement goals and cyber aggression data was acquired through self-reporting, and perceived popularity, social preference, and overt and relational aggression were assessed through peer nomination. Applying the latent profile analysis(LPA) to 1,239 elementary school students, three distinct groups of social achievement goals were identified: a development-oriented achievement goal group, an average social goal group, and a overall-high social achievement goal group. Using logistic regression analysis, the relationships between the latent group, peer status, and aggression were examined. The result indicated that the higher the social preference, the lower the probability of belonging to the 'overall-high social achievement goal group'. And the higher the cyber aggression, the lower the probability of belonging to the 'development-oriented achievement goal group'. In addition, the higher the relational aggression of the second time, the higher the probability of belonging to the 'overall-high social achievement goal group' as compared to the 'average social goal group'.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.161-174
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• 1996

Addressed in this paper is performance analysis of the maximum-likelihood code acquisition technique for slotted-mode preamble search in the CDMA reverse link. The probabilities of detection, miss, and false alarm are derived analytically for a multiple $H_{1}$ cell case in a frequency-selective Rayleigh fading channel, based on the statics of the CDMA noncoherent demodulator output. the probability density function of the decision variable consisting of successive demodulator outputs is also derived by considering the fading characteristics of the received signal for both single and dual antenna cases. The performance of the code acquisition technique is evaluated numerically with an emphasis on investigating the effects of post-detection integration, fading rate, and antenna diversity on the detection performance.