• Proceedings of the KSR Conference
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• 2005.11a
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• pp.1-6
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• 2005

To improve safety management of railway and cope with the factors to threat technical and social safety, we need to establish railway safety management system based on analysis of hazards and assessment of risk for railway system. So we have to conduct PHA(Preliminary Hazard Analysis) first to understand weak points and factors to possibly threat safety using analysis of related data such as past accident/incident data and safety regulation and classification standards of hazards/causes of railway accidents. Therefore in this research, we led types/dangerous events/causes of risks/factors of risks from hazard log developed based on railway accident classification and hazards of railway accident. PHA model for domestic railway system will be used in risk analysis and risk assessment of railway accident.

• Journal of Korean Society of Rural Planning
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• v.1 no.1
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• pp.65-74
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• 1995

As a initial methodological approach to rational land use planning in the county-level area, three types of land suitability classification techniques were examined from the viewpoint of their practical applicability through the case study of Seungju-gun area, Chonnam-province, Korea : major factors' criteria(method I ), principal component analysis( I ), and local monitoring( R( ). Each method has its strong and weak points as shown in Tab.-5. Therefore, when its practical application, there seem to be wide-range methodological selectivities from exclusive use of the best one to intermethodological combination of related ones In the beginning stage, intermethodological combination of all three types were tried to formulate the best solution possible. However, because of reliability problem of method R accrued from non- uniformity of evaluators'quality, only two methods( 1 , E ) were combined into a new evaluation method The applied results of the new combined method to case study area are shown in Fig.-2, 3 and 4.

• Journal of Environmental Health Sciences
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• v.14 no.1
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• pp.33-38
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• 1988

Natural mineral water is generally quite different from ordinary drinking water due to its original nature and various properties. The complexity of natural mineral water requires, therefore, not only to identify its nature and proper characteristics, but also to classify them by a reasonable scientific basis of comparison. The study was concentrated on a possible classification technique to natural mineral waters by their constitutions and physico-ehemical properties. The classification was carried out by the computation of such numerical parameters as ionic equivalent percentage, electrolytic conductance or mobility, ionic molecular weight, molecular concentration, equivalent conductivity and degree of ionization in consideration of the determinative criteria as follows -particular single element or molecule -major components of natural waters as bicarbonate, sulphate, chloride,caloride, calcium, magnesium, and sodium -moleculat concentration related to blood osmotic pressure -water temperature at emergence from spring -contents of free carbon dioxide (CO2) -pH value of water -total dissolved solids or salts (NaCl) The results obtained proved out to be clearly distinguhhable from ordinary drinking water as far as concern natural mineral water as an example on the subject -simple water -bicarbonate-predominating water -cold spring -carbonated-non gaseous water -weak alkaline water -non saline water Putting these various results together, the sample turned out to be a kind of natural mineral water that can be used as a drinking water if microbiologically safe.

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.449-458
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• 2010

As occasion demands to obtain efficient information from many documents and reviews on the Internet in many kinds of fields, automatic classification of opinion or thought is required. These automatic classification is called sentiment classification, which can be divided into three steps, such as subjective expression classification to extract subjective sentences from documents, sentiment classification to classify whether the polarity of documents is positive or negative, and strength classification to classify whether the documents have weak polarity or strong polarity. The latest studies in Opinion Mining have used N-gram words, lexical phrase pattern, and syntactic phrase pattern, etc. They have not used single word as feature for classification. Especially, patterns have been used frequently as feature because they are more flexible than N-gram words and are also more deterministic than single word. Theses studies are mainly concerned with English, other studies using patterns for Korean are still at an early stage. Although Korean has a slight difference in the meaning between predicates by the change of endings, which is 'Eomi' in Korean, of declinable words, the earlier studies about Korean opinion classification removed endings from predicates only to extract stems. Finally, this study introduces the earlier studies and methods using pattern for English, uses extracted sentimental patterns from Korean documents, and classifies polarities of these documents. In this paper, it also analyses the influence of the change of endings on performances of opinion classification.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.192-197
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• 2012

With the advent of DNA microarray technologies, researches for disease diagnosis has been actively in progress. In typical experiments using microarray data, problems such as the large number of genes and the relatively small number of samples, the inherent measurement noise and the heterogeneity across different samples are the cause of the performance decrease. To overcome these problems, a new method using functional modules (e.g. signaling pathways) used as markers was proposed. They use the method using an activity of pathway summarizing values of a member gene's expression values. It showed better classification performance than the existing methods based on individual genes. The activity calculation, however, used in the method has some drawbacks such as a correlation between individual genes and each phenotype is ignored and characteristics of individual genes are removed. In this paper, we propose a method based on the ensemble classifier. It makes weak classifiers based on feature vectors using subsets of genes in selected pathways, and then infers the final classification result by combining the results of each weak classifier. In this process, we improved the performance by minimize the search space through a filtering process using gene-gene interaction information and the mRMR filter. We applied the proposed method to a classifying the lung cancer, it showed competitive classification performance compared to existing methods.

• The korean journal of orthodontics
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• v.47 no.3
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• pp.151-157
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• 2017

Objective: The objective of this study was to investigate the differences in masticatory efficiency among patients with different Angle's classes of malocclusion and to assess the correlation between masticatory efficiency and the occlusal contact area. Methods: The mixing ability index (MAI) was calculated for measuring masticatory efficiency of 61 adult patients according to Angle's classifications of malocclusion. The study included 25, 15, and 21 patients with Angle's Class I, II, and III malocclusions, respectively. Silicone interocclusal recording material was used to measure the occlusal contact area. Results: Both the MAI and occlusal contact area showed the highest average values in the Class I malocclusion group, followed by the Class II and Class III malocclusion groups. No significant difference was observed in the MAI values between the Class I and Class II malocclusion groups (p > 0.05), whereas a significant difference was observed between the Class I and Class III malocclusion groups (p < 0.01) and between the Class II and Class III malocclusion groups (p < 0.05). A weak positive correlation was also observed between the MAI and occlusal contact area (p < 0.01, $r^2=0.13$). Conclusions: The results of this study indicated that masticatory efficiency was the highest in patients with Angle's Class I malocclusion, followed by those with Angle's Class II and Angle's Class III malocclusions. Moreover, a weak positive correlation was observed between masticatory efficiency and the occlusal contact area.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.33.3-33.3
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• 2019

Automatic, yet reliable methods to find and classify barred galaxies are going to be more important in the era of large galaxy surveys. Here, we introduce a new approach to classify barred galaxies by analyzing the butterfly pattern that Buta & Block (2001) reported as a bar signature on the potential map. We make it easy to find the pattern by moving the ratio map from a Cartesian coordinate to a polar coordinate. Our volume-limited sample consists of 1698 spiral galaxies brighter than Mr = -15.2 with z < 0.01 from the Sloan Digital Sky Survey/DR7 visually classified by Ann et al. (2015). We compared the results of the classification obtained by four different methods: visual inspection, ellipse fitting, Fourier analysis, and our new method. We obtain, for the same sample, different bar fractions of 63%, 48%, 36%, and 56% by visual inspection, ellipse fitting, Fourier analysis, and our new approach, respectively. Although automatic classifications detect visually determined, strongly barred galaxies with the concordance of 74% to 86%, automatically selected barred galaxies contain different amount of weak bars. We find a different dependence of bar fraction on the Hubble type for strong and weak bars: SBs are preponderant in early-type spirals, whereas SABs are in late-type spirals. Moreover, the ellipse fitting method often misses strongly barred galaxies in the bulge-dominated galaxies. These explain why previous works showed the contradictory dependence of the bar fraction on the host galaxy properties. Our new method has the highest agreement with visual inspection in terms of the individual classification and the overall bar fraction. In addition, we find another signature on the ratio map to classify barred galaxies into new two classes that are probably related to the age of the bar.

• Journal of Science Education
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• v.36 no.1
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• pp.153-165
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• 2012

This study investigated the frequent mistakes and the causes of the alternative conceptions in the animal classification by using the questionnaire and interview with the middle school students (N=300). As results, some students have difficulties classifying suggested animals into vertebrates or invertebrates : snakes (31.7%), shrimps (28.3%), turtles (25.6%), frogs (24.7%), and starfish (10.7%) in order of precedence. These errors seemed to be caused by intuitive thinking over characteristics of physical motions and appearance of suggested animals, wrong inference from comparing to features of familiar animals and the lack of observation experience of the vertebrate backbone. Furthermore, the results showed that relatively many students made a mistake classifying subgroup members of vertebrates such as classifying salamanders into the class Reptilia (45.3%) and turtles into Amphibia (40.3%). It is likely that those errors are affected by ambiguousness of classification terminology (e.g. the term of Amphibia) and weak ability in relating the physiological and ecological feature to standard of classification feature. In addition, sociocultural factors could influence animal classification as 'bat in birds', 'whale in fish, and 'penguin in mammals'. The present study implied that teaching and learning animal classification may require an appropriate guide focused on activities to explore major characteristics used for the animal classification standard through providing more chances of animal observation rather than the cramming method of learning induced by technical memorizing.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.149-154
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• 2017

The MCT-Adaboost algorithm chooses an optimal set of features in each rounds. On each round, it chooses the best feature by calculate minimizing error rate using feature index and MCT kernel distribution. The involved process of weak classification executed by a hard decision. This decision occurs some problems when it chooses ambiguous kernel feature. In this paper, we propose the modified MCT-Adaboost classification using soft decision. The typical MCT-Adaboost assigns a same initial weights to each datum. This is because, they assume that all information of database is blind. We assign different initial weights with our propose new algorithm using some statistical properties of involved features. In experimental results, we confirm that our method shows better performance than the traditional one.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.1
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• pp.101-126
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• 2023

Photographic archives of universities are one of the most valuable types of records that establish the university's identity and provide historical evidence. Unlike text records, however, they are weak in conveying meanings. Therefore, it is difficult to support users' search and utilization unless the information of photo records is comprehensively described. In this study, for the university photo archives, we tried to structure the classification system of photo archives and develop a metadata set that reflects the category characteristics in the classification. To this end, the photo archives classification system and metadata elements of domestic and American university archives were analyzed and based on this, the model of information structure was proposed. The information structure model presented in this study can help university archives improve the data quality of their photo archives and support users with the abundant discovery of photo archives.