• Journal of the Korean Society for information Management
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• v.36 no.2
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• pp.175-199
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• 2019

Uncertainty means incomplete stages of knowledge of propositions due to the lack of consensus of information and existing knowledge. As the amount of academic literature increases exponentially over time, new knowledge is discovered as research develops. Although the flow of time may be an important factor to identify patterns of uncertainty in scientific knowledge, existing studies have only identified the nature of uncertainty based on the frequency in a particular discipline, and they did not take into consideration of the flow of time. Therefore, in this study, we identify and analyze the uncertainty words that indicate uncertainty in the scientific literature and investigate the stream of knowledge. We examine the pattern of biomedical knowledge such as representative entity pairs, predicate types, and entities over time. We also perform the significance testing using linear regression analysis. Seven pairs out of 17 entity pairs show the significant decrease pattern statistically and all 10 representative predicates decrease significantly over time. We analyze the relative importance of representative entities by year and identify entities that display a significant rising and falling pattern.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10b
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• pp.989-992
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• 2001

인터넷의 지속적인 보급/발전과 더불어, 네트워크 상에서의 침입시도는 해가 지날수록 기하급수적으로 증가되고, 그 기법 또한 다변화되고 있다. 이는 침입탐지시스템의 적용환경에도 많은 영향을 끼치게 되었다. 일반적인 네트워크 기반 침입탐지시스템은 네트워크 디바이스를 통해 유입되는 패킷에 대해 Signature 기반 침입탐지 모듈을 통하여 침입을 탐지하게 된다. 대게의 경우 새로운 침입탐지 패턴이 생성되었을 경우, 사용자에 의해 추가되거나 또는 소스코드의 재컴파일을 통하여 시스템이 재구동되기도 한다. 본 논문이 제시하는 바는 이에 반해 AS 내에 존재하는 네트워크의 유입점인 게이트웨이 장치에 침입탐지 시스템을 설치하며, 이를 보안정책서버에 의해 정의된 정책에 의해 침입탐지 및 게이트웨이 장치로서 동작하게 한다. 이를 통해 보안정책서버에 추가되는 침입탐지 패턴 등의 정책정보가 각 침입탐지시스템에 실시간으로 반영되어 처리된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.143-144
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• 2016

빅 데이터 분석은 기존 데이터베이스 관리 도구로부터 데이터를 수집, 저장, 관리, 분석할 수 있는 역량을 말한다. 또한, 대량의 정형 또는 비정형 데이터 집합으로부터 가치를 추출하고 결과를 분석하는 기술을 의미한다. 대부분의 빅 데이터 분석 기술 방법들은 기존 통계학과 전산학에서 사용되던 데이터 마이닝, 기계 학습, 자연 언어 처리, 패턴 인식 등이 해당된다. 글로벌 리서치 기관들은 빅 데이터를 2011년 이래로 최근 가장 주목받는 신기술로 지목해오고 있다. 따라서 대부분의 산업에서 기업들은 빅 데이터의 적용을 통해 가치 창출을 위한 노력을 기하고 있다. 본 연구에서는 다음 커뮤니케이션의 빅 데이터 분석도구인 소셜 매트릭스를 활용하여 키워드 분석을 통해 창조경제 키워드 의미를 분석하고자 한다. 또한, 분석결과를 바탕으로 이론적 실무적 시사점을 제시하고자 한다.

• Journal of the Korean Geophysical Society
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• v.7 no.4
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• pp.247-253
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• 2004

In this paper, 3D recognizing algorithm which is based on the external shape feature is presented. Since many objects have the regular shape, if we posses the database of pattern and we recognize the object using the database of the object's pattern, it is possible to inspect and/or recognize the objects of many fields. This paper handles on the 3D object recognition algorithm using the geometrical pattern matching by 3D database.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.147-152
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• 2007

Face detection is a crucial part of the face recognition system. It determines the performance of the whole recognition system. Hausdorff distance metric has been used in face detection and recognition with good results. It defines the distance metric based only on the geometric similarity between two sets or points. However, not only the geometry but also the local patterns around the points are available in most cases. In this paper a new Hausdorff distance measure is proposed that makes hybrid use of the similarity of the geometry and the local patterns around the points. Several experiments shows that the new method outperforms the conventional method.

• The Journal of Engineering Geology
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• v.31 no.1
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• pp.1-17
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• 2021

It is important to evaluate the fracture network in a rock volume because fractures control the ground conditions and fluid flow characteristics. Therefore, various attempts have been made to quantify fracture networks to better understand ground and flow conditions. The use of fracture density alone (a quantitative parameter based on geometric analysis) does not fully explain the evolution of fracture networks, or quantify the spatial relationship (e.g. connectivity) of fractures in a rock mass. Therefore, the need for fracture network characterization based on topological analysis has recently emerged. In Korea however, the topological analysis of fracture networks within a rock mass has rarely been studied. As such, the definition of the topological analysis of fracture networks and the graph theory related to the topological analysis are briefly summarized in this study. We also introduce an application method for these analyses to fracture characterization. If the topological method is used for the analysis of fracture networks, it can also be adopted to analyze fluid flow characteristics of groundwater, characterize petroleum reservoirs, and analyze the evolution of a fracture network. In addition, topological analysis can be useful for site selection of major facilities such as nuclear waste disposal sites because it can be used to evaluate the stability of the potential sites.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.327-339
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• 2004

In this paper, we propose a new watermark algorithm for halftone images using iterative error minimizing method. In the proposed method, watermark bits are hidden at pseudo-random locations within a halftone image. To remove the distortions due to the inserted watermark bits and increase the invisibility of watermark, an iterative error minimizing technique is used. We define the halftoning error is defined as the difference between the original grayscale image and HVS-filtered printed halftone image. Then we iteratively find the pixel pattern with minimum halftoning error and displace the original pixel pattern with it. In order to be robust to geometrical modification like cropping or rotation, we insert the same watermark periodically into halftone images. Experiments using printed and scanned images show that the proposed method is a robust method to the geometrical modification and to hide the large amount of data within a halftone image without noticeable distortion.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.56-64
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• 2016

With the development of information technologies and the wide spread of smart devices, the number of users of social network services has increased exponentially. Studies that identify user preferences and recommend similar users in these social network services have been actively done. In this paper, we propose a new scheme to recommend social network friends with similar preferences through the moving pattern analysis of mobile users. The proposed scheme removes the meaningless trajectories via companions, short time trajectories, and repeated trajectories to determine the correct user preference. The proposed scheme calculates user similarity using the meaningful trajectories and recommends users with similar preferences as friends. It is shown through performance evaluation that the proposed scheme outperforms the existing schemes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1479-1486
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• 2011

In this paper, a simple and robust algorithm is proposed for detecting straight line segments in a steel plate image. Line detection from a steel plate image is a fundamental task for analyzing and understanding of the image. The proposed algorithm is based on small eigenvalue analysis. The proposed approach scans an input edge image from the top left comer to the bottom right comer with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Before calculating the eigenvalue, each line segment is separated from the edge image where several line segments are overlapped to increase the accuracy of the line detection. Additionally, unnecessary line segments are eliminated by the number of pixels and the directional information of the detected line edges. The respects of the experiments emphasize that the proposed algorithm outperforms the existing algorithm which uses small eigenvalue analysis.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.1
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• pp.124-129
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• 2010

When a phenolic resin is carbonized by the leakage current flowing along its surface, the carbonization pattern is one of the most important factors to determine its carbonization characteristics. However, the typical carbonization pattern of a phenolic resin is too complicated to be analyzed by conventional Euclidean geometry. In most cases, such a complicated shape shows a fractal structure. It is possible, therefore, to examine the characteristics of the carbonization pattern regarding a given phenolic resin. In order to quantitatively investigate the carbonization pattern of the phenolic resin carbonized by a leakage current, in this paper, the fractal dimension of the carbonization pattern has been calculated as a function of the magnitude of a leakage current and the distance between two electrodes. For reliability of calculation, the correlation function as well as the box counting method has been used to calculate the fractal dimension. According to the result of calculation, the fractal dimension increases as the current increases at the constant electrode gap distance. However, there is no significant relation between the fractal dimension and the electrode gap distance at a constant current.