• Journal of KIISE:Software and Applications
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• v.28 no.9
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• pp.612-628
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• 2001

This paper presents a methodology to extract classes and inheritance relations from procedural software. The methodology is based on the idea of generating all groups of class candidates, based on the combinatorial groups of object candidates, and their inheritance with all possible combinations and selecting a group of object candidates, and their inheritance with all possible combinations and selecting a group with the best or optimal combination of candidates with respect to the degree of relativity and similarity between class candidates in the group and classes in a domain model. The methodology has innovative features in class candidates in the group and classes in a domain model. The methodology has innovative features in class and inheritance extraction: a clustering method based on both static (attribute) and dynamic (method) clustering, the combinatorial cases of grouping class candidate cases based on abstraction, a signature similarity measurement for inheritance relations among n class candidates or m classes, two-dimensional similarity measurement for inheritance relations among n class candidates or m classes, two-dimensional similarity measurement, that is, the horizontal measurement for overall group similarity between n class candidates and m classes, and the vertical measurement for specific similarity between a set of classes in a group of class candidates and a set of classes with the same class hierarchy in a domain model, etc. This methodology provides reengineering experts with a comprehensive and integrated environment to select the best or optimal group of class candidates.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.118-121
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• 2018

끊김 없는 이동성은 멀티미디어가 풍부한 실시간 서비스를 지원하는 미래의 무선 네트워크에서 필수적이다. SDN (Software Defined Networking)은 중앙 집중식 컨트롤러를 통해 무선 네트워크에서 세밀한 플로우 수준의 이동성 관리를 제공할 수 있지만 핸드오버 지연의 새로운 네트워킹 패러다임이다. 스플릿 포인트 방식은 SDN 무선 네트워크에서 핸드오버 및 종단 간 전송 지연을 줄이는 효과적인 방법이다. 스플릿 포인트는 트래픽이 새로운 AP (Access Point)를 향하여 핸드오버 한 후에 기존 플로우 경로상에 존재하는 스위치이다. 본 논문에서는 MN-CN (Corresponding Node) 경로의 각 스위치의 가중치를 스위치와 후보 AP 사이의 평균 고리(홉)로 계산하고 최소 가중치를 갖는 스위치가 스플릿 포인트로 선택된다. 스플릿 포인트 선택 외에도 이 논문은 SDN 에서 제공하는 제어 및 데이터 플레인 분리를 이용하여 핸드오버 후 플로우에 대한 최적의 경로를 복원한다. 제안 아이디어의 수치 해석은 이전 솔루션과 비교하여 총 비용이 9.6 % ~ 13 % 향상되었음을 보여준다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.401-403
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• 2013

Myopic method which is one of dynamic spectrum access method is an advantage that it maximizes immediate throughput is not complicated, and the simple and effective. The disadvantage of myopic method is that there may become less efficient because of conflicts between users secondary secondary user becomes many. Between the secondary if the secondary all users, select a channel to maximize the throughput of their own without considering the secondary other users, but it will try transfer secondary most users select the same channel collision will be more. Myopic / CA method has been proposed to solve this problem. Instead of selecting one channel to maximize their performance, select a candidate channels plurality of their advantage, the secondary user transfers to randomly selected channel that one in this way is a scheme. In this paper, we analyze whether it can be defined in a number of the channel number of candidates, depending on the network environment, maximizes the performance of the entire network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.209-214
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• 2003

Multi-mode coding method is a reliable DC-suppression method. There are two ways to improve the DC-suppression performance. One is improving scrambler's performance, and the other is improving selection criteria. The latter uses the MRDS(minimum running digital sum) criterion. It is easy to calculate, but its performance goes down when the length of codeword is getting longer. The MSW(mean squared weight) criterion that is known as the best so far regardless of the length of codeword has the high complexity. In this paper, we present the new selection criteria, MPRDS(minimum peak RDS) and A BSRDS(absolute RDS). Their performance are close to the MSW, implementation is simple. And also we present the SC(sign change) that has a subsidiary role with the original selection criteria and improve the capacity.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.53-62
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• 2013

Currently we have 11 climatological stations registered in World Meteorological Organization. Geographically, these stations are unevenly distributed in Korea and are mainly located on seaside. Therefore station's density analysis should be performed to produce the high-quality climatological data. Using the correlation integral method, the density of climatological stations can be measured by the estimation of fractal dimension. In this study, new climatological stations having the higher fractal dimension were selected. Sequential or simultaneous selection method were carried out until 3 new stations were selected based on the fractal dimension.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.863-870
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• 2019

In the GSM method for OWC-MIMO System, it is important to select an activation pattern set(: APS) for the performance optimization in the environment where mutual interference is high depending on the location of the transmitter and receiver. However, due to the high computational complexity, a high cost is paid in selecting the transmission APS. In this paper, we propose a method to reduce the candidate APS by pre-determining basic APS when generating candidate APS. The simulation results show that the proposed method has the same BER performance and reduce the computational complexity by 90% compared to the general GSM method in the high interfering environment.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.135-142
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• 2020

In this paper, we describe the iris localization method in RGB images. Most of the iris localization methods are developed for infrared images, thus an iris localization method in RGB images is required for various applications. The proposed method consists of four stages: i) detection of the candidate irises using circular Hough transform (CHT) from an input image, ii) detection of a pupil center based on deep learning, iii) determine the iris using the pupil center, and iv) correction of the iris region. The candidate irises are detected in the order of the number of intersections of the center point candidates after generating the Hough space, and the iris in the candidates is determined based on the detected pupil center. Also, the error due to distortion of the iris shape is corrected by finding a new boundary point based on the detected iris center. In experiments, the proposed method has an improved accuracy about 27.4% compared to the CHT method.

• 월간 한농연
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• s.64
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• pp.8-9
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• 2007

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.657-667
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• 2012

In the MPR selection algorithm of Optimized Link State Routing (OLSR), each node selects own MPRs independently, so most of nodes are selected to MPR at least once. To cope with this problem, the MPR candidate selection algorithm was proposed. The MPR candidate selection algorithm can reduce the number of MPRs, but the efficiencies of route and connectivity decline due to decreased number of MPRs. So, in this paper, we propose the Significant Multi-Point Relay (S-MPR) selection algorithm which can enhance the performance of ad hoc network by improving the MPR selection algorithm of OLSR. In proposed S-MPR selection algorithm, each node selects the most important node to S-MPR to guarantee the connectivity then selects remaining MPRs in MPR candidates. So proposed S-MPR selection algorithm can reduce the overhead of many MPRs without decline of routing performance. To show the performance gain of proposed S-MPR selection algorithm, we simulate the proposed S-MPR selection algorithm by using OPNET.

• Journal of KIISE:Software and Applications
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• v.27 no.9
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• pp.961-972
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• 2000

본 논문에서는 사용자의 적합 피드백을 기반으로 적합 문서들에서 발생하는 용어들과 초기 질의어간의 발생 빈도 유사도 및 퍼지 추론을 이용하여 용어의 가중치를 산정하는 방법에 대하여 제안한다. 피드백 문서들에서 발생하는 용어들 중에서 불용어를 제외한 모든 용어들을 질의어로 확장될 수 있는 후보 용어들로 선택하고, 발생 빈도 유사성을 이용한 초기 질의어-후보 용어의 관련 정도, 용어의 IDF, DF 정보를 퍼지 추론에 적용하여 후보 용어의 초기 질의어에 대한 최종적인 관련 정도를 산정 하였으며, 피드백 문서들에서의 가중치와 관련 정도를 결합하여 후보 용어들의 가중치를 산정 하였다. 본 논문에서는 성능을 평가하기 위하여 KT-set 1.0과 KT-set 2.0을 사용하였으며, 성능의 상대적인 평가를 위하여 Dec-Hi 방법, 용어 분포 유사도를 이용한 방법, 퍼지 추론을 이용한 방법들을 정확률-재현률을 사용하여 평가하였다.