• Animal Systematics, Evolution and Diversity
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• v.5 no.1
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• pp.25-32
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• 1989

Authors worked on the fauna of Cholla-do leeches and identified 4 species in Hirudinea, of which 2 species, Whitmania acranulata and Whitmania edentula, are first recorded in Korea.

• Journal of architectural history
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• v.5 no.1 s.9
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• pp.18-38
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• 1996

Dosan Sedans was built in 1560, when Toege I Whang(1500-1571) was 60, as a place in which to study and teach disciples. The building was built to a humble 3-kan system which was a popular form of sodang in the 16th century, There found an enlargement of space by attaching outer walls around three sides which was designed by Toege himself. Minimum in space, moderation in form, conrol of embellishment, hermit scholar's aethetics became basic concept of the architecture of Dosan Sodang. After completion of sodang, Toege wrote many poems about pond, walls, flower bed and natural surroundings like sheer cliff, winding river and even rural daily life of villagers around the building. It could be sud that ,for Toege, architecture was cogniged as a whole complex of building and its surrounding natural, artificial and human circumstances.

• Journal of the Korean Society of Food Science and Nutrition
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• v.23 no.4
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• pp.680-685
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• 1994

Total nitrogen content, proline, free amino acids, sugars, invertase and diastase activities in native bee-honey (NBH) and foregin bee-honey (FBH) harvested from our different areas of Kangwon , Korea were determined. The total nitrogen contents of NBH and FBH were 0.077$\pm$0.033mg% and 0.055$\pm$0.022mg%, respectively. Proline content in NBH was 42$\pm$10mg% and waqs found to be much lower than that in FHB. Phenylalanine and proline were major free amino acids both in NBH and FBH . The content of total free amino acid in FBH were twice as much as that in NBH , however isomaltose content in NBH were almost two times more than that in FBH. Other sugars including fructose, glucos , sucrose and maltose were also analyzed. No differences were found between NBH and FBH in invertase activities, but comparing to these of FBH ,lower values of diastase activity in NBH were observed.

• Journal of the Korean Society of Food Science and Nutrition
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• v.20 no.1
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• pp.52-58
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• 1991

Physico-chemical properties including the composition of organic acids and fatty acids in native bee-honey and foreign bee-honey harvested in Kangwon area were studied with the emphasis on the honey which was collected form wild flowers nd mixed flowers sources for honey nectars. the major organic acids were considered as acetic acid formic acid and valeric acid in volatile acids and gluconic acid maleic acid malic acid quinic acid and citric acid in non-volatile fraction in both of native bee-honey and foreigr bee-honey. Some naturally occuring fatty acids({{{{ { C}_14{ } }}}}-{{{{ {C }_{20 } }}}}) were observed with the principal fatty acids of myristic aicd linolenic acid and palmitic acid and palmitic acid in the various honey, The characteristics of moisture content pH viscosity free acidity lactone and total acidity were also analyzed and discussed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.40-43
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• 2000

In this paper, we investigate how the average survival time of listed companies in the Korea Stock Exchange (KSE) are affected by changes in macro-economic environment and covariate vectors which show peculiar financial characteristics of each company. We also apply the survival analysis approach to the dichotomous firm failure prediction and the results show a similar pattern of forecasting performance using the existing dichotomous prediction techniques. These findings suggest that, when we consider a bankruptcy model under a certain economic event, the survival approach can be a useful alternative to the existing dichotomous prediction methods since the approach provides estimation of average survival time as well as simple binary prediction.

• The Korean Journal of Zoology
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• v.7 no.1
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• pp.9-14
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• 1964

1. 1963년 8월 6일부터 8월 22일까지 제주도의 (제주시, 중문, 한림, 서귀포, 고산, 성산포, 관음사, 한라산산정) 각지역에 걸쳐 위생에 관계되는 파리류, 즉, Sarcophagidae(쉬파리), Muscidae(집파리), Anthomyidae(깜정파리), Fannidae (애기집파리), Scatophagidae(똥파리) 3000 여개체를 채집하여 정리한 결과 다음과같은 한국미기록 8종이 밝혀졌다. 1. Sarcophaga erecta HO, 1934. 2. Pyrellia cadaverina LINNE, 1761 3. Orthelia latipalis ZIMIN, 1951 4. Morellia simplicissima ZIMIN ,1951 5. Lispe orientalis WIEDEMANN 1830. 6. Muscina angustifrons(LOU, 1858). 7. Ophyra chalcogaster (WIEDEMANN, 1850). 8.Graphomyia rufitibia STEIN, 1918. 2. 이상으로 한국산 Sarcophagidae는 31 종 , Muscidae 는 15종, Anthomyidae는 6 종이 된다.

• Journal of Plant Biology
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• v.23 no.3_4
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• pp.85-90
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• 1980

The chemical affinities among 12 species of Viola from Jeju Island are investigated by thin-layer chromatography for their MeOH soluble and aglycon parts. They are classified into three groups which are closely related to those of morphological classification: the first allience-Viola hirtipes, V. chaerophylloides, V. meta-japonica, V. keiskei var. okuboi and V. violacea; the second allience-V. xanthopetala, V. ovata-oblonga, V. acuminata var. acuminata and V. grypoceras; and the third allience-V. pachyrhiza, V. phalacrocarpa and V. mandshurica var. ciliata. The first allience consists of the species without stem which have PA value greater than 50% with one another. V. hirtipes and V. chaerophylloides show closer affinity among the taxa of this allience. The second allience consists of the species with stem, of which PA value are about 50%. The third allience consists of the species without stem which have PA values lower than 50% when compared with any other taxa.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.1-16
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• 2008

The purpose of this paper is to propose a new binary classification method for predicting corporate failure based on genetic algorithm, and to validate its prediction power through empirical analysis. Establishing virtual companies representing bankrupt companies and non-bankrupt ones respectively, the proposed method measures the similarity between the virtual companies and the subject for prediction, and classifies the subject into either bankrupt or non-bankrupt one. The values of the classification variables of the virtual companies and the weights of the variables are determined by the proper model to maximize the hit ratio of training data set using genetic algorithm. In order to test the validity of the proposed method, we compare its prediction accuracy with ones of other existing methods such as multi-discriminant analysis, logistic regression, decision tree, and artificial neural network, and it is shown that the binary classification method we propose in this paper can serve as a premising alternative to the existing methods for bankruptcy prediction.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.733-736
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• 1996

Neural Network(NN) is known to be suitable for forecasting corporate bankruptcy because of discriminant capability. Bankruptcy prediciton on NN by now has mostly been studied based on financial indices at specific point of time. However, the financial profile of corporates fluctuates within a certain range with the elapse of time. Besides, we need a lot of data of different bankrupt types in order to apply NN for better bankruptcy prediciton. Therefore, we have decided to focus on textiles and clothing industries for bankruptcy prediction with limited data. One part of the collected data was used for training and calibration, and the other was used for verification. The model makes a learning with extended data from financial indices at specific point of time. The trained model has been tested and we could get a high hitting ratio relatively.

• Korean Management Science Review
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• v.14 no.2
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• pp.91-111
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• 1997

Neural Network(NN) is known to be suitable for forecasting corporate bankruptcy because of discriminant capability. Bandkruptcy prediction on NN by now has mostly been studied based on financial indices at specific point of time. However, the financial profile of corporates fluctuates within a certain range with the elapse of time. Besides, we need a lot of data of different bankrupt types in order to apply NN for better bankruptcy prediction. Therefore, We have decided to focus on textile and clothing industries for bankruptcy prediction with limited data. One part of the collected data was used for training and calibration, and the other was used for verification. The model makes a learning with extended data from financial indices at specific point of time. The trained model has been tested and we could get a high hitting ratio relatively.