• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Journal of the Korean Society for Marine Environment & Energy
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• v.8 no.4
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• pp.227-235
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• 2005

This study aimed at suggesting management policy directions for the uninhabited islands of Korea which are national land resources with economic potential for tourism and development and strategic value for boundary delineation of territorial waters and exclusive economic zone as well as their unique ecological status. Review of existing management arrangements related to the uninhabited islands revealed six management issues to be addressed: insufficient data and their low reliability, lack of management policy directions, increase in ecosystem deterioration and perturbation by human activities, lack of policy measures for meeting utilization and development demands, weak management base with insufficient personnel and budget, and legal measures not taking Into account their unique ecological and socioeconomic characteristics. The management policy directions to improve the management of the uninhabited islands of Korea include management directions and strategies, and suggestions for legal improvement. Considering the unique ecological value of the uninhabited islands, management directions suggested are anti-degradation in which current and future demands for their utilization and development do not degrade the ecological potential of the uninhabited islands and integration in which land and sea areas are managed as an integrated management unit. Four strategies proposed to follow the management directions are enhancement of the knowledge base through a comprehensive survey, development and legislation of guidelines for the rational management of utilization and development demands, establishment of the comprehensive island debris collection and disposal system, and enhancement of management capacity. Legal improvement for the effective implementation of the management policy directions should include comprehensive uninhabited islands survey, legal utilization restraints and management guidelines based on classification of the islands, management boundary, and improvement of regulations on designated islands.

• Korean Journal of Animal Reproduction
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• v.6 no.1
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• pp.19-30
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• 1982

1. The cows slaughtered at age of 3, 4, 6, 7, 8, and 9 years old were 1.5, 1.5, 15.0, 62.5 and 4.4% respectively. 2. The cows slaughtered at 351-450kg and more than 500kg were 60 and 28% respectively. 3. Best, very good, good and bad cows in nutritional condition were 1.6, 25.8, 62.9, and 9.7% respectively. Among the six cows which were bad nutrition, the two were with severe endometritis, the three were normal in genital function and one was on 70 days of pregnancy. 4. Holstein cows(55.2%) showed higher reproductive failure than the Korean cows(33.3%). 5. The slaughted ratio of the Korean cattle and Holstein cows was 36 and 64% respectively. 6. Pregnant cows were about 16% among the slaughtered one. 7. Reproductive failures were composed of 46% in uterus, 32% in ovaries, 8% in udder, 6% in oviduct, 4% in cervix of uterine, 2% in vagina and 2% inmummified fetus. 8. Forty six percentages of uterine diseases were as follows; horn, 13%, body of uterus, 32% and ovary diseases were 32%, that is, 12% of ovary atrophy, 8% of ovarycyst and 6% of lutealcyst. 9. The cows of reproductive failures were commonly infected with 1.6 kinds of diseases. 10. According to classification, six type of ovaries were as follows; normal, 58%, ovary-cyst, 11%, luteum cyst, 4%, coexistence of follicles and corpus luteum, 16%, weak function of ovaries, 10% and ovarian atrophy, 1%. 11. Major axis, minor axis and thickness of right ovary were larger than those of left one both in Korean cattle and Holstein cows. Holstein cow had generally larger size of ovary than these of the Korean cattle.. 12. The left and right oviducts showed no difference in length, but Holstein had longer oviduct than Korean cow. 13. There was no difference in the length of uterine horn between right and left in the Korean cows, but the right was longer than the left in Holstein cows. 14. Holstein had longer horn and body of uterine than the Korean cows. 15. The weight of right ovary was heavier than that of left in both breeds, but there was no differences in weight of left ovary between two breeds and right ovary of Holstein breed was heavier than that of the Korean cow. 16. The weight of right oviduct and uterine born was heavier than that of the left, and Holstein had heavier oviducts and uterine horns than the Korean cows. 17. Holstein had heavier uterine body and cervix of uterine than the Korean cows. 18. The length of reproductive systems of Korean cow is as follows; Major and minor diameter and thickness ofovary are 3.6${\pm}$0.7, 2.3${\pm}$0.4 and 1.6${\pm}$1.4 cm in left and 3.7${\pm}$0.6, 2.5${\pm}$0.5 and 1.8${\pm}$0.5 cm in right. Oviduct is 28.4${\pm}$3.1 cm in left and 27.8${\pm}$3.3 cm in right. Uterine horn is 27.4${\pm}$4.5 cm in left and 27.7${\pm}$4.9 cm in right. Uterine body and cervix are 3.4${\pm}$1.1 and 6.5${\pm}$1.7 cm. 19. The length of female reproductive systems ofHolstein cow is as follows; Major and minor diameter and thickness of ovary are 3.9${\pm}$1.3, 2.3${\pm}$0.5, and 1.5${\pm}$0.6 cm in left and 4.0${\pm}$0.8, 2.8${\pm}$0.6 and 1.8${\pm}$0.6 cm in right. Oviduct is 29.4${\pm}$4.2 cm in left and 29.3${\pm}$4.1 cm in right. Uterine horn is 30.2${\pm}$7.4 cm in left and 32.6${\pm}$8.4 cm in right. Uterine body and cervix are 4.5${\pm}$2.5 and 7.8${\pm}$2.9 cm. 20. The weight of reproductive systems of Korean cow is as follows; Ovary is 8.4${\pm}$4.1 g in left and 9.3${\pm}$3.6g in right. Oviduct is 1.5${\pm}$0.5 g in left and 1.6${\pm}$0.5 g in right. Uterine horn is 109${\pm}$27 g left and 118${\pm}$32 g in right. Uterine body and cervix are 30.4${\pm}$14.1 and 76.7${\pm}$38.4g. 21. The weight of reproductive systems of Holstein cow is as follows; Ovary is 8.2${\pm}$3.1 g in left and 12.5${\pm}$5.6 g in right. Oviduct is 1.7${\pm}$0.6 g in left and 1.9${\pm}$0.9 g in right. Uterine horn is 199${\pm}$14.2 g in left and 221${\pm}$111.2g in right. Uterine body and cervix are 58.2${\pm}$46.5 and 126.7${\pm}$103.3 g.

• Korean Journal of Heritage: History & Science
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• v.34
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• pp.20-58
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• 2001

In order to unravel the characteristics of arms used in the 'Three Kingdoms,' Kokuryo, Silla and Paikje. the classification and the developing procedures of the arms should be first discussed. At first, the basic arms of the soldiers of Three Kingdoms were iron swords, iron spearheads, and bows. During that period, swords attached a ring pommel were commonly used. But after 5A. D. a sword with a decoration pommel appeared. Infantry generally used iron spearheads. From the late 4A. D. the long spearheads were broadly used in cavalry battles. In the late 6A. D. infantry mainly used long spearheads, and this resulted in the foundation of long spearheads units. There were two kinds of bows: Short Bow whose arch is small and Long Bow whose arch is long. It is known that the Short Bow was widely used in Kokuryo and Paikje up to 5A. D. In the early era, infantry used Long Bow, yet it was vastly used after 6A. D. when a castle's strategical value was great and defending a castle was. significant. Above mentioned, as basic combat weapons, iron spearhead and bow were fundamental. In particular, the spearhead was the essential weapon to a soldier. Yet, arrow gun and hook-shape cutters were important weapons. Especially, after 6A.D., when a castle became strategically pivotal in military, the arrow gun became the important weapon. This resulted in the foundation of arrow gun units. Hook-shape cutters were used to snatch horsemen or to climb up to fall the castle. Yet, the cutter was not the Three Kingodoms' basic weapon. In addition, the three stages of arms development in the Three Kingdoms are formation stage, development stage, and settlement stage. The formation stage was the period when premitive military unit appeared in the Three Kingdoms. It ranged from 1B. C. to the mid 3A. D. At that time according to regions. there were two weapon systems operating: North area including Kokuryo and the northern part of Paikje and South area including Silla, Kaya and the southern part of Paikje. ln North area a sword with a ring attached at the end of the holder, iron spear with neck and mid-size flat holder and iron arrowhead with an extension to fix, were used. In this period, during a war calvary units were mostly used and their weapon systems seemed possibly to succeed in that of Kochosun. In the development stage, when LoLang's influence on surroundings became weak, Koguryo, Paikjae and Silla had directly contacted each other. In the late 3A.D. to the early 6A.D., Silla achieved a drastic improvement in weapon system. This was the period when Kokuryo played a leading role in arms race. Kokuryo's arms manufacturing techniques passed onto Silla, Kaya and Paikje. In combat strategy a joint operation between infantry and calvary prevailed even if their military tactics were different. In a calvary battle heavily armed horsemen played import roles at this period. The horsemen and even horses were heavily guarded with iron armors. After all, the appearance of fully armed horsemen implies the very need of powerful destructive forces in weapon system. At that time, basic weapons were a big sword with a ring attached at the end of the holder, swallow's tail-shape spear with neck, and iron spearhead with neck and an extension. The settlement stage began at the mid 6A.D., when it was the revolutionary period in the arms development history. Of course, actual proofs and picture documents were not sufficient enough to penetrate full scale of the weapon system. But, according to historical circumstances and historic records, it is very certain that this period was the peak in arms development. In this period special military units, such as infantry-calvary companies, Archery units and Long spear units, that executed particular duties with special weapons, were founded. This became the characteristics of the settlement stage.