• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.53-60
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• 2021

LOD-based recommender systems usually leverage the data available within LOD datasets, such as DBpedia, in order to recommend items(movies, books, music) to the end users. These systems use a semantic similarity algorithm that calculates the degree of matching between pairs of Linked Data resources. In this paper, we proposed a new approach to measuring semantic distance in an LOD-based recommender system by assigning weights converted from user ratings to links in the LOD graph. The semantic distance measurement model proposed in this paper is based on a processing step in which a graph is personalized to a user through weight calculation and a method of applying these weights to LDSD. The Experimental results showed that the proposed method showed higher accuracy compared to other similar methods, and it contributed to the improvement of similarity by expanding the range of semantic distance measurement of the recommender system. As future work, we aim to analyze the impact on the model using different methods of LOD-based similarity measurement.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.572-587
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• 2008

The Self-organizing Feature Map(SOFM) that is one of unsupervised neural networks is a very powerful tool for data clustering and visualization in high-dimensional data sets. Although the SOFM has been applied in many engineering problems, it needs to cluster similar weights into one class on the trained SOFM as a post-processing, which is manually performed in many cases. The traditional clustering algorithms, such as t-means, on the trained SOFM however do not yield satisfactory results, especially when clusters have arbitrary shapes. This paper proposes automatic clustering on trained SOFM, which can deal with arbitrary cluster shapes and be globally optimized by graph cuts. When using the graph cuts, the graph must have two additional vertices, called terminals, and weights between the terminals and vertices of the graph are generally set based on data manually obtained by users. The Proposed method automatically sets the weights based on mode-seeking on a distance matrix. Experimental results demonstrated the effectiveness of the proposed method in texture segmentation. In the experimental results, the proposed method improved precision rates compared with previous traditional clustering algorithm, as the method can deal with arbitrary cluster shapes based on the graph-theoretic clustering.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.590-590
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• 2015

본 연구는 집중호우에 의한 홍수예측 및 소유역의 유출거동에 대한 수문학적 민감성(susceptibility) 규명을 목적으로 강우강도, 지속기간 및 토양포화도 변화에 따른 홍수유출특성을 분석하여 유역의 유출거동 민감성을 표출할 수 있는 노모그래프를 개발하였다. 개별 홍수사상에 대한 유출거동 특성 분석을 위하여 한국건설기술연구원의 대표 시험유역인 설마천 유역의 과거 17년간(1996 ~ 2012)의 10분 간격의 강우량 및 유출량 자료를 수집하여 홍수유출해석을 수행하였다. 설마천 시험유역의 일누가강우량 100mm 이상, 50개 홍수사상에 대한 홍수유출해석은 유역 물순환 해석모형인 CAT(Catchment hydrological cycle Assessment Tool)을 이용하였으며 모의결과를 바탕으로 홍수사상별 지체시간, 강우강도, 지속기간 및 토양포화도 변화에 따른 홍수유출특성을 상세히 분석하였다. 이 중에서도 지체시간은 유역반응을 나타내는 시간변수로서 수문모델링 및 홍수량예측에 매우 중요한 요소이다. 특히, 강우량에 대한 홍수량의 반응이 빠른 소유역의 경우에 홍수량예측에 큰 영향을 미친다. 따라서 강우강도, 지속기간, 토양포화도의 변화량에 대한 지체시간의 거동을 R 프로그래밍 언어 및 3D Surfer를 이용하여 분석한 후 최종적으로 소유역의 홍수유출 특성을 나타내는 3차원 홍수 유출특성 노모그래프를 개발하였다. 분석에 사용된 R 프로그래밍 언어는 통계 계산과 그래픽을 위한 프로그래밍 언어이자 소프트웨어 환경으로 데이터의 조작 및 수치연산, 시각화를 수행할 수 있는 기능을 여러 패키지를 통해 구현할 수 있다. 따라서 본 연구에서는 R을 이용하여 10분 단위의 강우 및 유출량 자료를 1시간 및 1일 자료로 구축하고 17년간의 과거 홍수사상을 분리하여 추출하는 R 홍수유출해석 시스템을 개발하였으며 추출된 홍수사상을 관측 유출량 및 관측 토양수분을 포함하여 시각화함으로써 강우 및 토양수분 변화에 따른 소유역의 유출거동 민감성을 확인할 수 있었다. 분석 결과, 지체시간은 강우지속기간 및 토양포화도에 민감한 거동특성을 나타냈으며 토양포화도는 첨두홍수량의 변화에 민감한 영향을 주는 것으로 확인되었다. 개발된 3차원 홍수유출특성 노모그래프는 유역의 규모 및 지형물리학적 특성에 따라 다양하게 나타날 것으로 판단되며 여러 계측유역에 적용함으로써 유역별 홍수유출 반응특성을 정량화할 필요가 있다. 즉, 강우강도, 지속기간, 지체시간, 포화도 등의 변화에 따른 유역의 홍수유출 반응특성을 규명함으로써 미계측 유역의 홍수량예측 실무에 활용할 수 있을 것으로 판단된다.

• The KIPS Transactions:PartA
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• v.16A no.6
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• pp.453-462
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• 2009

Studies on software plagiarism detection, prevention and judgement have become widespread due to the growing of interest and importance for the protection and authentication of software intellectual property. Many previous studies focused on comparing all pairs of submitted codes by using attribute counting, token pattern, program parse tree, and similarity measuring algorithm. It is important to provide a clear-cut model for distinguishing plagiarism and collaboration. This paper proposes a source code clustering algorithm using a probability model on extreme value distribution. First, we propose an asymmetric distance measure pdist($P_a$, $P_b$) to measure the similarity of $P_a$ and $P_b$ Then, we construct the Plagiarism Direction Graph (PDG) for a given program set using pdist($P_a$, $P_b$) as edge weights. And, we transform the PDG into a Gumbel Distance Graph (GDG) model, since we found that the pdist($P_a$, $P_b$) score distribution is similar to a well-known Gumbel distribution. Second, we newly define pseudo-plagiarism which is a sort of virtual plagiarism forced by a very strong functional requirement in the specification. We conducted experiments with 18 groups of programs (more than 700 source codes) collected from the ICPC (International Collegiate Programming Contest) and KOI (Korean Olympiad for Informatics) programming contests. The experiments showed that most plagiarized codes could be detected with high sensitivity and that our algorithm successfully separated real plagiarism from pseudo plagiarism.

• Journal of KIISE:Software and Applications
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• v.28 no.3
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• pp.224-238
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• 2001

본 논문은 ATM(Abstract Timed Machine)으로 명세된 실시간 시스템을 검증하기 위한 방법을 기술한다. ATM은 임무 위급 시스템인 실시간 시스템을 명세, 분석, 검증하기 위한 정형기법이다. ATM은 모드와 전이, 포트로 구성되어 있으며 모드는 머신의 압축된 상태를 표현한다. 전이는 하나의 모드에서 다른 모드로의 전환을 나타내며 조건과 이벤트로 구성되어 있다. 포트는 ATM간의 상호작용을 위한 진입을 표현한다. 다른 정형기법과 비교하여 ATM은 소프트웨어의 순환공학 과정에서 사용하기 위해 설계되었다. 역공학 측면에서 볼 때 ATM은 계산 논리뿐만 아니라 실시간 시스템의 실제 소스코드에 있는 설계나 환경정보를 표현할 수 있다. 이러한 목적을 위해 ATM의 모드는 계산모드, 추상화 모드, 주제모드로 구분된다. 계산 모드는 코드 상에서의 논리와 계산을 나타내며 추상화 모드는 모드와 전이의 블록을 하나의 ATM으로써 표현한다. 대개의 경우, 이것은 코드 상에서의 블록을 ATM내 하나의 모드로 나타낼 때 사용한다. 주제 모드는 예외나 주기적 동작 등과 같은 다수의 ATM의 주제를 표현한다. 실시간 시스템을 검증하기 위해 시스템의 소스 코드는 역명세 과정을 통하여 ATM으로 표현된다. 검증은 ATM에 대한 도달성 그래프를 생성하는 것에 의해 수행된다. 도달성 그래프는 상태와 시간을 추상화되고 압축된 형태로 표현할 수 있으며 그 결과 시간 속성을 지닌 상태 공간을 감소시킬 수 있다. 또한 시스템의 교착상태를 쉽게 발견할 수 있다. 본 논문은 ATM과 실행 모델, 도달성 그래프, 검증을 위한 속성 등을 기술하며 이들을 다른 정형 방법들과 예제를 통하여 비교한다.수 있다. 모피우스는 헤더나 광고와 같은 불필요한 정보들을 제거하는 별도의 단계를 거치지 않으므로 wrapper를 빠르게 생성한다. 궁극적으로 모피우스는 새로운 웹 상점을 사용자가 자유롭게 추가, 삭제할 수 있는 환경을 제공한다.X>와 반응시킬 경우에는 반응식 c에 의거 진행됨을 예측할 수 있었다.의거 진행됨을 예측할 수 있었다.이 거의 산화되지 않았고, $700^{\circ}C$에서도 ZnS와 ZnO 상이 공존한 것으로 보아 SnO$_2$코팅이 ZnS의 산화를 억제하는 것으로 나타났다.pplied not only to the strike system in the RSC circle, but also to the logistics system in the SLC circle. Thus, the RSLC model can maximize combat synergy effects by integrating the RSC and the SLC. With a similar logic, this paper develops "A Revised System of Systems with Logistics (RSSL)" which combines "A New system of Systems" and logistics. These tow models proposed here help explain several issues such as logistics environment in future warfare, MOE(Measure of Effectiveness( on logistics performance, and COA(Course of Actions)

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.431-440
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• 2017

This study surveyed pre-service early childhood teachers' level of concern about software education on the assumption that software education will be introduced into early childhood education in the future. It was shown that the pre-service early childhood teachers' level of concern about software education is the highest at stage 0(95%) and that they have a high level of informative, personal and managerial concern. Thus, a non-user pattern was mostly indicated. However, compared to the typical non-user pattern, their personal and informative level of concern is slightly higher. A 'tailing up' phenomenon to stage 6(refocusing) was shown. Hence, a pattern aspect close to critical non-user appeared to some extent. A difference in the significant level of concern was shown at all stages, except for managerial concern, according to the need for awareness, the appearance of a future implementation plan, and technology efficacy level. Based on this outcome, it was proposed that teacher training in early childhood software education should be made available as part of the educational activity connected with the Nuri Curriculum, since this would be more suitable for young children's developmental level than the early childhood software education, including coding education, etc., currently found in private institutions.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.495-504
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• 2008

Aspect Oriented Programming(AOP) is a relatively new programming paradigm and has properties that other programming paradigms don't have. This new programming paradigm provides new modularization of software systems by cross-cutting concerns. In this paper, we propose a regression test method for program evolution by AOP. By using JoinPoint, we can catch a pointcut-name which makes it possible to test the incorrect pointcut strength fault and the incorrect aspect precedence fault. Through extending proof rules to aspect, we can recognize failures to establish expected postconditions faults. We can also trace variables using set() and get() pointcut and test failures to preserve state invariant fault. Using control flow graph, we can test incorrect changes in control dependencies faults. In order to show the correctness of our proposed method, channel management system is implemented and tested by using proposed methods.

• Communications of Mathematical Education
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• v.38 no.2
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• pp.263-286
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• 2024

With the introduction of AI digital textbooks, interest in the use of technology tools in mathematics education is increasing. Technology tools have the advantage of visualizing mathematical concepts and discovering mathematical principles through experimentation and inquiry. The 2015 revised mathematics curriculum in Korea already mentions the use of technology tools, and accordingly, various teaching and learning activities using technology tools are presented in mathematics textbooks. However, there is still a lack of systematic analysis on the types and utilization methods of technology tools presented in textbooks. Therefore, this study analyzed the current status of the use of technology tools presented in high school mathematics textbooks based on the 2015 revised curriculum. To this end, the types of technology tools presented in mathematics textbooks were categorized, and the utilization ratio of each category was investigated. In addition, the utilization patterns of technology tools were analyzed by subject and content area, and the utilization ratio of technology tools according to the type of teaching and learning activities was examined. The results showed that technology tools were used in various types and ratios according to the subject and content area. In particular, technology tools in the symbol-manipulation graphing software category accounted for 58% of the total usage cases, showing the highest proportion. By subject, the use of symbol-manipulation graphing software was prominent in subjects dealing with the analysis area, while the use of dynamic geometry software was relatively high in the geometry area. In terms of teaching and learning activity types, the utilization ratio of auxiliary tool type (49%) and intended inquiry induction type (37%) was high. The results of this study show that technology tools play various roles in mathematics textbooks and provide useful implications for improving mathematics teaching and learning methods using technology tools in the future. Furthermore, it can contribute to the establishment of educational policies related to AI digital textbooks and the development of teacher training programs.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2041-2049
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• 1998

This paper suggests a technique for program segmentation and maintenance using PSDG(Post-State Dependency Graph) that improves the quality of a software by identifying and detecting defects in already fixed source code. A program segmentation is performed by utilizing source code analysis which combines the measures of static, dynamic and semantic slicing when we need understandability of defect in programs for corrective maintanence. It provides users with a segmental principle to split a program by tracing state dependency of a source code with the graph, and clustering and highlighting, Through a modeling of the PSDG, elimination of ineffective program deadcode and generalization of related program segments arc possible, Additionally, it can be correlated with other design modeb as STD(State Transition Diagram), also be used as design documents.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.27-37
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• 2021

Highly informative heuristics in AI planning can help to a more efficient search a solutions. However, in general, to obtain informative heuristics from planning problem specifications requires a lot of computational effort. To address this problem, we propose a Partial Planning Graph(PPG) and Mixed Heuristics for solving planning problems more efficiently. The PPG is an improved graph to be applied to can find a partial heuristic value for each goal condition from the relaxed planning graph which is a means to get heuristics to solve planning problems. Mixed Heuristics using PPG requires size of each graph is relatively small and less computational effort as a partial plan generated for each goal condition compared to the existing planning graph. Mixed Heuristics using PPG can find partial interactions for each goal conditions in an effective way, then consider them in order to estimate the goal state heuristics. Therefore Mixed Heuristics can not only find interactions for each goal conditions more less computational effort, but also have high accuracy of heuristics than the existing max and additive heuristics. In this paper, we present the PPG and the algorithm for computing Mixed Heuristics, and then explain analysis to accuracy and the efficiency of the Mixed Heuristics.