• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2008.04a
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• pp.276-280
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• 2008

Korean Classical Music, as the abbreviated wording for 'Korean Music', is being used as the indicating phraseology for our traditional music that distinguishing from Western Music, the foreign music or foreign-styled popular music. Since such Korean Classical Music has the different acoustic characteristics from Western Music, it needs its own performance space for the special exclusive-use of Korean Classical Music. Likewise, even though the demand for the performance space of special exclusive-use for Korean Classical Music where Korean Classical Music is rendering, is on increasing tendency due to the increase of national concern about traditional culture art, since it is being planned without any concrete standard or method that gratifies the supreme listening condition, it is the real situation that a securement of the satisfying acoustic condition is very difficult, after the completion of construction. On such viewpoint, in order to evaluate the acoustic characteristics of the performance space of special exclusive-use for Korean Classical Music, based on the subjective response which reflects human being's psychological attribute at first, this Study has attempted to extract the proper evaluation vocabulary for appraisement on Korean Classical Music. The abstracted vocabulary in such way would be used significantly for Subjective Response Evaluation in order for the evaluation on the Acoustic Characteristics of the performance space of special exclusive-use for Korean Classical Music.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.12
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• pp.68-74
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• 1991

This paper proposes a HMM model based on fuzzy, as a method on the speech recognition of speaker-independent. In this recognition method, multi-observation sequences which give proper probabilities by fuzzy rule according to order of short distance from VQ codebook are obtained. Thereafter, the HMM model using this multi-observation sequences is generated, and in case of recognition, a word that has the most highest probability is selected as a recognized word. The vocabularies for recognition experiment are 146 DDD are names, and the feature parameter is 10S0thT LPC cepstrum coefficients. Besides the speech recognition experiments of proposed model, for comparison with it, we perform the experiments by DP, MSVQ and general HMM under same condition and data. Through the experiment results, it is proved that HMM model using fuzzy proposed in this paper is superior to DP method, MSVQ and general HMM model in recognition rate and computational time.

• Korean Journal of Computational Design and Engineering
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• v.17 no.6
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• pp.426-435
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• 2012

This paper starts with an approach to Korean traditional building design using BIM tool as a design methodology where Korean traditional buildings show some difference rather as weaknesses in handling curves and curved members and the construction. BIM design tools, that are adequate in treating modern architectural design vocabularies, show some disadvantages not having necessary elements and components as building libraries. In this paper we build our own libraries adequate to the proper assembling way of Korean traditional buildings. In contrast to the diverse use of straight building members, Korean traditional buildings show rare use of curves and/or curved members in their assemblage. Moreover, in the case of a circular plan, mostly a circle is interpreted in terms of polygons such as square, hexagon or octagon. In this paper, we examine Gwanram-Jung in Changduk Palace, which is probably the only example in Korea showing a use of curves and/or curved members in assemblage. We try to interpret the case as an incomplete prototype and apply in a modern way to complete a circular plan in terms of circular arcade.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.