• Title/Summary/Keyword: hyphen

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Automatic Transcription of the Union Symbols in Korean Texts (한국어 텍스트에 사용된 이음표의 자동 전사)

  • 윤애선;권혁철
    • Language and Information
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    • v.7 no.1
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    • pp.23-40
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    • 2003
  • In this paper, we have proposed Auto-TUS, an automatic transcription module of three union symbols-hyphen, dash and tilde (‘­’, ‘―’, ‘∼’)-using their linguistic contexts. Few previous studies have discussed the problems of ambiguities in transcribing symbols into Korean alphabetic letters. We have classified six different reading formulae of the union symbols, analyzed the left and right contexts of the symbols, and investigated selection rules and distributions between the symbols and their contexts. Based on these linguistic features, 86 stereotyped patterns, 78 rules and 8 heuristics determining the types of reading formulae are suggested for Auto-TUS. This module works modularly in three steps. The pilot test was conducted with three test suites, which contains respectively 418, 987 and 1,014 clusters of words containing a union symbol. Encouraging results of 97.36%, 98.48%, 96.55% accuracy were obtained for three test suites. Our next phases are to develop a guessing routine for unknown contexts of the union symbols by using statistical information; to refine the proper nouns and terminology detecting module; and to apply Auto-TUS on a larger scale.

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Effect of Osmolality on the Absorption of Ethanol in the Rabbit (삼투질농도가 Ethanol 흡수(吸收)에 미치는 효과)

  • Kim, Shin-Yoon;Kim, Byoung-Guk;Yoo, Kyoung-Mu;Kim, Hyeong-Jin;Park, Jae-Sik;Hwang, Soo-Kwan
    • The Korean Journal of Physiology
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    • v.15 no.1
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    • pp.53-59
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    • 1981
  • In the present study, an effort was directed to elucidate the effect of osmolality on the absorption of ethanol in rabbits. A single dose of 13.67 ml(2. 16 gm ethanol/kg BW) of hypo-, iso-hyphen and hypertonic ethanol per kg BW was administered into the stomach to albino rabbits and the experiment was performed at 30 th, 60 th and 120 th minute. The blood ethanol level was determined by the method of Williams et al, and hematocrit(Hct) was determined by the conventional Hct centrifuge and reader. The results are summarized as follow. The blood ethanol level showed the highest value at 60 min after the ethanol ingestion in the hypo- and isotonic groups, $171.3{\pm}13.3\;mg%$ and $204.5{\pm}23.0\;mg%$, respectively, but in the hypertonic group, the highest value was observed at 120min after the ingestion. The absorption rate of ethanol between 0 to 30 min after the ingestion of hypo- and isotonic ethanol was $88.54{\pm}12.04$ and $94.73{\pm}8.33\;mg/min$, respectively, but a decreased value of $44.72{\pm}6.69\;mg/min$ was noted after hypertonic ethanol ingestion comparing with hypo- and isotonic groups, The Hct value after hypo- and isotonic ethanol ingestion was decreased at 30 min but returned to the control level at 120 min. In contrast with hypo- and isotonic ethanol ingestion, hypertonic ethanol ingestion produced an increase of the Hct value at 30 min and returned to the control level at 120 min. The heart rate was increased but the respiratory rate was decreased after ethanol ingestion regardless of the osmolality.

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PCA-Based Feature Reduction for Depth Estimation (깊이 추정을 위한 PCA기반의 특징 축소)

  • Shin, Sung-Sik;Gwun, Ou-Bong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.3
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    • pp.29-35
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    • 2010
  • This paper discusses a method that can enhance the exactness of depth estimation of an image by PCA(Principle Component Analysis) based on feature reduction through learning algorithm. In estimation of the depth of an image, hyphen such as energy of pixels and gradient of them are found, those selves and their relationship are used for depth estimation. In such a case, many features are obtained by various filter operations. If all of the obtained features are equally used without considering their contribution for depth estimation, The efficiency of depth estimation goes down. This paper proposes a method that can enhance the exactness of depth estimation of an image and its processing speed is considered as the contribution factor through PCA. The experiment shows that the proposed method(30% of an feature vector) is more exact(average 0.4%, maximum 2.5%) than using all of an image data in depth estimation.