• 한국전산구조공학회논문집
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• 제19권4호
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• pp.357-367
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• 2006

재분배 기법은 민감도 해석 없이 변위에 대한 각 부재의 변위기여도를 간단하게 계산 한 후, 변위기여도에 근거하여 물량을 분배함으로서 변위를 제어할 수 있는 실용적인 고층건물 변위 설계법으로 인식되고 있다. 그러나 에너지 이론에 근거한 재분배 기법은 하중 조건에 따라서 서로 다른 변위기여도를 가질 수 있게 되며, 특히 횡력 뿐만 아니라 상당한 량의 연직하중도 함께 받고 있는 고층건물의 재분배 기법 적용시의 변위기여도 계산에는 연직하중의 영향이 고려하여야 한다. 또한, 고층 건물의 변위설계에 재분배 기법을 적용하기 위해서는 실용성을 높이기 위해서 부재 그룹핑이 고려되어지는데 부재 그룹핑 고려에 따른 연직하중의 영향을 다르게 나타나게 된다. 그러므로, 본 연구에서는 하중의 종류와 부재 그룹핑 여부를 변수로 하여 세 가지의 재분배 알고리즘을 개발한 후, 이를 20층 강접 골조 전단벽 예제와 60층 아웃리거 예제의 변위 설계 적용하였다.

• 한국정보통신학회논문지
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• 제19권2호
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• pp.301-307
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• 2015

본 논문에서는 공간적 상관관계를 갖는 MIMO(multiple-input multiple-output) 채널을 가정하여 도청자가 존재하는 환경인 와이어탭(wiretap) 채널을 고려한다. 이 때, 각 노드에서 안테나의 교차 편파를 가정하여 1-비트 피드백을 이용하는 직교 시공간 블록 코드(OSTBC: orthogonal space-time block code)의 물리계층 보안 성능을 분석한다. 본 논문에서는 1-비트 피드백을 이용하여 OSTBC(O-OSTBC: one-bit feedback-based OSTBC) 전송을 위한 송신안테나 그룹을 선택하는 방법을 제시하고, 다양한 송신안테나 그룹핑 방법들에 대하여 보안 불통 확률(secrecy outage probability)을 비교한다. 특히, 높은 공간적 상관관계를 갖는 MIMO 채널에서 O-OSTBC와 기존의 OSTBC와의 보안 불통 확률의 성능을 비교하여 효율적인 송신안테나 그룹핑 방법을 제안한다.

• 한국군사과학기술학회지
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• 제21권6호
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• pp.752-759
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• 2018

The SBR technique is one of the asymptotic high frequency method, where a dense grid of rays are launched and traced to analyze the scattering properties of the target. In this paper, we propose an accelerated SBR technique using grouping a central ray and 8 surrounding rays around the center ray. First, launched rays are grouped into groups consisting of a central ray and 8 surrounding rays. After the central ray of each group is preferentially traced, 8 surrounding rays are rapidly traced using the information of ray tracing for the central ray. Simulation result of scattering analysis for CAD models verifies that the proposed method reduces the computational time without decreasing the accuracy.

• 융합정보논문지
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• 제12권3호
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• pp.38-45
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• 2022

핀테크 기술의 발전으로 인해 스마트폰을 이용한 금융거래가 활성화되고 있다. 금융거래시 사용자 인증을 위한 비밀번호는 스마트 폰의 터치 스크린 상에 보여지는 가상 키패드를 통해 입력된다. 비밀번호를 터치할 때 공격자가 높은 해상도를 가진 카메라로 촬영하거나 어깨 너머로 훔쳐보는 방식으로 사용자가 입력한 비밀번호를 알아낼 수 있다. 이런 공격을 막기 위해 보안이 적용된 가상 키패드는 크기가 작은 터치 스크린에 입력하기 어렵고, 훔쳐보기 공격에 취약점이 여전히 존재한다. 본 논문에서는 전체 키패드를 몇 개의 그룹으로 나누고 작은 화면에 표시하여 입력할 문자가 속해 있는 그룹을 터치하고, 그룹 내에서 해당 문자를 터치하는 방식으로 입력할 문자를 쉽게 찾을 수 있다. 제안기법은 입력할 문자가 속한 그룹을 선택하며 해당 그룹에 키패드를 10개 이내로 작은 스크린에 보여주기 때문에 키패드의 크기를 기존 방법보다 2배 이상 확대가 가능하고, 위치를 랜덤하게 배치하여 터치한 위치를 통한 공격을 차단할 수 있다.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• 제5권3호
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• pp.76-85
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• 2024

The purpose of this study is to propose a new method of analysis focusing on interconnections between species rather than traditional biodiversity analysis, which represents ecosystems in terms of species and individual counts such as species diversity and species richness. This new approach aims to enhance our understanding of ecosystem networks. Utilizing data from the 4th National Natural Environment Survey (2014-2018), the following eight taxonomic groups were targeted for our study: herbaceous plants, woody plants, butterflies, Passeriformes birds, mammals, reptiles & amphibians, freshwater fishes, and benthonic macroinvertebrates. A co-occurrence frequency analysis was conducted using nationwide data collected over five years. As a result, in all eight taxonomic groups, the degree value represented by a linear regression trend line showed a slope of 0.8 and the weighted degree value showed an exponential nonlinear curve trend line with a coefficient of determination (R²) exceeding 0.95. The average value of the clustering coefficient was also around 0.8, reminiscent of well-known social phenomena. Creating a combination set from the species list grouped by temporal information such as survey date and spatial information such as coordinates or grids is an easy approach to discern species distributed regionally and locally. Particularly, grouping by species or taxonomic groups to produce data such as co-occurrence frequency between survey points could allow us to discover spatial similarities based on species present. This analysis could overcome limitations of species data. Since there are no restrictions on time or space, data collected over a short period in a small area and long-term national-scale data can be analyzed through appropriate grouping. The co-occurrence frequency analysis enables us to measure how many species are associated with a single species and the frequency of associations among each species, which will greatly help us understand ecosystems that seem too complex to comprehend. Such connectivity data and graphs generated by the co-occurrence frequency analysis of species are expected to provide a wealth of information and insights not only to researchers, but also to those who observe, manage, and live within ecosystems.

• 가정과삶의질연구
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• 제13권4호
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• pp.139-150
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• 1995

This research is planned to compare a quantitative methodology and a qualitative methodology in the study of the household work. For these research tasks this study is centered on husbands' participation in the household work. First it is reviewed study precedent using a quantitative method and a qualitative method to compare a research methodology of the household work. It is selected a survey method of quantitative methodology and a depth interview of qualitative methodology, Second the data are collected through the questionnaire and the depth interview with three couples,. Third to compare a quantitative methodology and a qualitative methodology it is looked about problems in the concept the grouping the collection of data and the interpretation of household work.

• ETRI Journal
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• 제27권1호
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• pp.22-42
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• 2005

Traditional traffic identification methods based on wellknown port numbers are not appropriate for the identification of new types of Internet applications. This paper proposes a new method to identify current Internet traffic, which is a preliminary but essential step toward traffic characterization. We categorized most current network-based applications into several classes according to their traffic patterns. Then, using this categorization, we developed a flow grouping method that determines the application name of traffic flows. We have incorporated our method into NG-MON, a traffic analysis system, to analyze Internet traffic between our enterprise network and the Internet, and characterized all the traffic according to their application types.

• Journal of information and communication convergence engineering
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• 제9권3호
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• pp.295-300
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• 2011

Twitter is a popular microblogging service that enables the users to send and read short text messages. These messages are becoming source to analyze topic trends and identify relations among temporal topics. In this paper, we propose a method to classify the temporal topics on Twitter as a problem of grouping the similar patterns. To provide a starting point for a classification under the same topics, we identify the content word weighting scheme based on Latent Dirichlet Allocation (LDA). And we formulate how the temporal topics in the time window can be classified like peaky topics, constant topics, and periodic topics. We provide different real case studies which show the validity of the proposed method. Evaluations show that the proposed method is useful as a classifying model in the analysis of the temporal topics.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 추계학술대회 논문집 전력기술부문
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• pp.252-254
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• 2007

This paper introduces the method of sequential clustering as a tool for the effective clustering of mass unit electrical systems. The interconnected network system retains information about the location of each line. With this information, this paper aims to carry out initial clustering through the transmission usage rate, compare the results of similarity measures for regional information with similarity measures for regional price, and introduce the technicalities of the clustering method. This transmission usage rate used power flow based on congestion costs and modified similarity measurements using the FCM algorithm. This paper also aims to prove the propriety of the proposed clustering method by comparing it with existing clustering methods that use the similarity measurement system. The proposed algorithm is demonstrated through the IEEE 39-bus RTS.

• Journal of Electrical Engineering and Technology
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• 제3권3호
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• pp.436-443
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• 2008

This paper presents a new method for building detection and reconstruction from aerial images. In our approach, we extract useful building location information from the generated disparity map to segment the interested objects and consequently reduce unnecessary line segments extracted in the low level feature extraction step. Hypothesis selection is carried out by using an undirected graph, in which close cycles represent complete rooftops hypotheses. We test the proposed method with the synthetic images generated from Avenches dataset of Ascona aerial images. The experiment result shows that the extracted 3D line segments of the reconstructed buildings have an average error of 1.69m and our method can be efficiently used for the task of building detection and reconstruction from aerial images.