• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.328-330
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• 2004

컴포넌트의 합성을 통하여 신뢰성 있는 시스템을 구축하려면 명시된 품질 속성을 만족해야 한다. 이를 위해서는 잘 정의된 상호작용을 바탕으로 하여 비기능적 속성이 명세되어야 한다. 그러나 기존의 컴포넌트 명세 방법들은 컴포넌트의 기능 속성에 주로 초점을 맞추어 왔으며 비기능적 속성에 대한 지원이 미약하다. 본 논문에서는 비기능적 속성들을 명세하는 방법에 초점을 둔다. 구체적으로, 비기능적 속성들 중에서 시간제악 속성을 상호작용 컨트랙트에 정의하고 UML 다이어그램으로 표현하는 방법을 제시한다. 정형화 된 구조물 가진 컨트랙트에서 시간제약 속성들은 보다 명확한 의미를 가지며, 다양한 형태의 컴포넌트 합성에서 검증이 가능하다.

• The Journal of Information Technology
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• v.6 no.4
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• pp.113-123
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• 2003

This paper is the study for code generation using attribute grammar without cycle. For the purpose of this study, we designed metalanguage SDL which describes an attribute grammar and, represented attribute grammar to SDL. This attribute grammar is based on L-attributed grammar without cycle. This system consists of attributed-grammar analyzer and attribute evaluator. Attributed grammar analyzer takes a semantic description language and then generates useful informations that are needed by attribute evaluator. The evaluator calculates an attribute values using these information.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.70-76
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• 2020

This study examines whether there is a moderating effect of corporate social responsibility(CSR) on the relation between sales, general, and administrative(SG&A) expenditures and future corporate performance. SG&A expenditures are decomposed into maintenance and investment components and the latter component is focused. Using 968 Korean firm-year observations with CSR scores in the KOSPI market for the period of 2012-2017, this study investigates the relation between SG&A investment component and future corporate performance and then the moderate effect of CSR on its relation. Main results show that the SG&A investment component increases the future corporate performance and the moderate effect of CSR on its relation is more positively explicit. This finding implies that the effect of SG&A investment component on corporate performance is differentiated according to the level of CSR.

• Journal of Educational Research in Mathematics
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• v.19 no.4
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• pp.531-543
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• 2009

This study identified what cognitive attributes are required of eighth graders to solve geometrical problems such as 'Recall,' 'Analyze,' 'Justify,' 'Synthesize/Integrate,' and 'Solve Non-routine Problems' by using the cognitive diagnostic theory. The five attributes are proved as the skills for solving the geometric problems. Many students have not fully mastered the attributes of 'Justify' and 'Synthesize/Integrate'. There was high correlation between these attributes. 'Analyze' best predicted the changes in the geometric achievement. And while students with high levels of geometrical achievement have mastered all the five attributes, those in the mid- and low-level range of performance have mastered fewer attributes.

• Korean Journal of Optics and Photonics
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• v.30 no.3
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• pp.106-113
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• 2019

When elemental images are remapped to solve the depth conversion in integral imaging, the integrated image is inevitably accompanied by discontinuity. This paper analyzes the discontinuity factor caused by elemental-image remapping, to validate the reduction of the discontinuity through converging pick-up and reconstruction of the three-dimensional image in real and virtual modes simultaneously. The validity of the proposed method is quantitatively verified when compared with the conventional parallel pick-up.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.362-365
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• 2004

This study suggests an attribute code system for earned value management system (EVMS). The attribute code system can be used for integrating various EYM data from construction schedule and cost. If the suggested attribute code is used in EVM, sorting and typical classifying of EVM data is possible in the computerized system. Those functions are an effective management tool for construction manager comparing with other EVM tools.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.87-89
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• 2013

이 논문에서는 비침윤성 방광암 환자의 재발 예측을 위해 마이크로어레이 데이터에서 최적의 속성 부분 집합을 찾고 이를 비교 평가한다. 정보 이득(information gain)을 통해 구한 상위 40개, 80개, 100개의 속성 집합과 FCBF(fast correlation based filter) 알고리즘을 적용하여 구한 최적의 속성 부분집합을 SVM 분류 모델에 적용하여 정확도를 비교 평가한 결과 정보 이득을 적용한 상위 100개 속성 부분집합의 분류 정확도가 가장 높게 나왔으며, FCBF 알고리즘을 적용한 속성 집합은 비교적 적은 속성을 사용하면서 이와 비슷한 분류 정확도를 보임을 확인할 수 있었다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.47-54
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• 2014

Based on the indiscernible relation of rough set, the inevitability of superposition and inconsistency of data makes the reduction of attributes very important in information system. Rough set has difficulty in the difference of attribute reduction between consistent and inconsistent information system. In this paper, we propose the new uncertainty measure and attribute reduction algorithm by Bayesian posterior probability for correlation analysis between condition and decision attributes. We compare the proposed method and the conditional information entropy to address the uncertainty of inconsistent information system. As the result, our method has more accuracy than conditional information entropy in dealing with uncertainty via mutual information of condition and decision attributes of information system.

• Korean Journal of Cognitive Science
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• v.12 no.4
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• pp.29-39
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• 2001

Kaplan(2000) reported that instances were categorized more accurate in the aligned condition than in the non-aligned condition irrespective of similarity between instances[16]. This study investigated wether Kaplan(2000)\\`s results could be explained by stimulus types she used and alignment effects in categorization were due to selective attention to aligned attributes. In Experiment 1. I examined whether attribute alignment produced significant effects on similarity and categorization and aligned attributes were recalled more than non-aligned ones. Results showed that instances were rated more similar and categories were learned more rapidly in the aligned condition than in the non-aligned condition. It can be explained that categories are learned rapidly in the aligned condition because attribute alignment increases within-category similarity. But. the result that aligned attributes were recalled more than non-aliened ones in the attribute recall test implies that alignment effects in categorization can be independent of similarity between instances partially. In Experiment 2. I used equal numbed of attributes defining two categories and instructed subjects to pay their attention to categorization-relevant dimensions only. Results showed that dimension instruction facilitated category learning in the non-aligned condition only but categories were learned more rapidly in the aligned condition than in the non-aliened condition irrespective of instruction types. In conclusion. attribute alignment in categorization may facilitate paying selective attention to categorization-relevant attributes.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.411-419
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• 1997

본 연구에서는 확률화응답모형이 가지는 두가지 한계에 대하여 고찰하였다. 첫째 민감한 속성을 갖는 모비율의 추정시 모비율 $\pi_A$가 매우 작은 값일 경우, 즉 희귀속성일 경우 확률화응답모형을 적용하게 되면 비밀보장의 효과를 감안한다고 해도 직접질문법에 비해 비효율적일 수 있음을 지적하였다. 둘째로 비밀보장에서 오는 이점과 그로 인한 효율의 손실이라는 서로 상충되는 면을 객관적으로 고려하는데 있어서 한계가 있음을 지적하였다.