• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.4
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• pp.353-362
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• 2012

3D building modeling from airborne Lidar without model regularization may cause positional errors or topological inconsistency in building models. Regularization of 3D building models, on the other hand, restricts the types of models which can be reconstructed. To resolve these issues, this paper modelled 3D buildings from airborne Lidar by building model regularization which considers more various types of buildings. Building points are first segmented into roof planes by clustering in feature space and segmentation in object space. Then, 3D building models are reconstructed by consecutive adjustment of planes, lines, and points to satisfy parallelism, symmetry, and consistency between model components. The experimental results demonstrated that the method could make more various types of 3d building models with regularity. The effects of regularization on the positional accuracies of models were also analyzed quantitatively.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.136-150
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• 2008

Many studies have been carried out for automatic extraction of building by LiDAR data or airphoto. Combining the benefits of 3D location information data and shape information data of image can improve the accuracy. So, in this research building recognition algorithm based on contour was used to improve accuracy of building recognition by LiDAR data and elaborate building boundary recognition by airphoto. Building recognition algorithm based on contour can generate building boundary and roof structure information. Also it shows better accuracy of building detection than the existing recognition methods based on TIN or NDSM. Out of creating buffers in regular size on the building boundary which is presumed by contour, this research limits the boundary area of airphoto and elaborate building boundary to fit into edge of airphoto by double active contour. From the result of this research, 3D building boundary will be able to be detected by optimal matching on the constant range of extracted boundary in the future.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.33-38
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• 2005

The goal of this study is to segment building points effectively utilizing scan-line characteristics of airborne laser scanner. Points are classified as to their altitude similarity and adjacency with other classified points, and point searching range for the classification is restricted within some number of scan-lines, preventing classification speed from lowering as the process goes on. Besides, we detected wrong discrimination of one object into more than two classes, then integrated them into a single class. Consequently we could discriminate points of each building from others, its annexes and none building points simultaneously.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1110-1112
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• 2015

에너지 절감을 위해 다양한 분야에서 노력을 기울이고 있지만 전체 에너지 사용량의 약 20% 이상을 차지하는 건물 분야는 정부의 정책과 제도적인 지원 하에 에너지 절감활동을 활발하게 진행하고 있다. 특히 $3000m^2$ 이상의 중대형 건물의 경우 BEMS(Building Energy Management System)기반의 건물에너지 관리가 의무화 될 예정이다. 하지만 기존 BEMS의 경우 특정 기업에 의한 단독 솔루션 형태로 제공되고 있어 BEMS간 데이터 상호호환성을 보장하지 않고, 단순 모니터링 기능에 의존하여 저장/관리 되지 않고 버려지는 데이터들이 많아 차후 문제가 발생한 경우 과거 데이터를 통한 분석 작업에 어려움이 있다. 따라서 본 논문에서는 건물에너지 통합관리 측면에서 원격지에 설치된 다양한 BEMS들의 센서/미터 데이터들을 웹을 통해 수집하고 데이터 웨어하우스에 저장/관리되며 건물에너지 통계, 분석 및 진단을 가능하도록 하는 데이터 웨어하우스 기반의 원격 건물에너지 통합 관리 시스템 설계에 대해 서술한다.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.370.2-370.2
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• 2016

투명 박막 태양전지는 건물과 일체화 된 building-integrated photovoltaics (BIPV) 시스템에 적용되어 건물의 외장재로서 외관의 심미적 가치를 높일 수 있다. 현재 BIPV 모듈은 glass 타입의 형태가 시장을 주도할 것으로 예상되며[1], 건물의 외부 미관을 고려하여 투명 박막 태양전지에 색을 구현하는 연구가 진행되고 있다. 투명 박막 태양전지에 적용하기 위한 목적으로 본 연구에서는 스핀코팅을 이용하여 표면 플라즈몬 효과가 큰 Cu 나노입자를 Si 웨이퍼와 유리기판 위에 각각 분포 시킨 후, 광학적 특성을 분석하였다. 스핀코팅의 속도(rpm)를 다양하게 변화 시킨 후 나노 입자의 분포를 관찰하였으며, 속도가 증가할수록 나노입자의 수는 감소함을 확인하였다. 또한 속도가 증가할수록 입자 사이의 거리는 멀어졌으며, 최저 속도 100 rpm에 비해 4000 rpm에서 스핀코팅 한 입자들은 응집이 상대적으로 되지 않았음을 관찰하였다. 속도가 증가할수록 입자가 기판 위에 적게 잔재하기 때문에 반사율과 투과율이 가시광선 영역에서 증가하였으며, 유리 기판에 구현한 색깔이 점차 옅어짐을 관찰하였다. 이러한 결과로부터 스핀코팅의 속도를 변화시킴으로써 나노입자의 분포 양상과 이에 따른 색상의 변화를 유발 할 수 있다는 사실을 확인하였다.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.281-286
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• 2005

여러 분야에서 활용성이 증가하고 있는 도시지역에 대한 3차원 모형화 구축은 기존에는 항공사진이나 고해상도 위성영상을 주로 활용하여 왔으나, 최근에는 높은 정밀도를 보장하는 항공LIDAR 측량기법에 대한 연구가 활발히 진행되고 있다. 특히, 다양한 형태, 크기, 종류의 건물들이 존재하는 광범위한 도시지역을 모형화 하기 위하여 정밀도가 높은 LIDAR 자료를 통하여 신속하고 정확하게 현실에 가까운 건물 모형으로 복원하는 기술 개발이 요구되고 있다. 본 연구에서는 LIDAR 관측자료 및 디지털 영상, 수치지도 등의 자료를 활용하여 LIDAR자료의 전처리 과정과 다양한 필터를 적용하여 지면과 비지면 정보를 분류하였으며, LoG 연산자에 의한 건물 경계선 및 특징점 추출기법을 개발하여 도시 지역의 3차원 건물 복원기법을 제안하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.291-292
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• 2018

The purpose of this study is to examine the sensitivity of the audience to the background of the building where Chinese historical film 'Hero' is used. In this study, the sensitive vocabulary suitable for the building background was derived through previous research related to sensitivity, and the sensitive analysis was analyzed by questionnaire form. Research result shows that the building background of the movie can have an sensitive impact on the audience and will help to understand Chinese traditional style and culture.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.737-742
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• 2017

Recently, unconventional high-rise building shapes have attracted attention as a landmark of metropolitan cities and the search for innovative building forms in architecture is ongoing. In this study, $Isotruss^{(R)}$ grid(ITG) used in smaller scale structures was applied to building structural systems and its structural performance was examined. The structural behavior of an ITG was compared with that of a diagrid structure as a reference structure. The stiffness-based design method of the diagrid system was used for the preliminary design stage of member sizing in an ITG. The structural design of 16, 32, and 48-story buildings was carried out for the two systems with the same size. The angle of the inclined columns for ITG and diagrid was $59^{\circ}$ and $68.2^{\circ}$, respectively. The lateral stiffness, steel tonnage of the exterior frame, axial strength ratio, story drift ratio, and natural frequency of the two systems were compared. Based on the analysis result of 6 buildings, the two systems had similar structural capacity; 93.3% and 88.7% of the lateral load was carried by the perimeter frame in the ITG system and diagrid system, respectively. This suggests that the ITG system is better in arranging core columns. Therefore, the proposed ITG system has not only a unique façade, but also substantial structural capacity equivalent to the existing system.

• Journal of Korean Association for Spatial Structures
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• v.11 no.4
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• pp.89-99
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• 2011

As the scope of the target of terrorism is recently extending, the danger of domestic terroristic attacks is increasing constantly, and the form of terrorism is changing from hard targets such as significant facilities of the country into soft target of multi-complex buildings such as skyscrapers. Accordingly this study analyzes the terrorism threat level on skyscrapers by comparing the assessment results of the terrorism threat level on skyscrapers and high-rise buildings with the assessment results of the terrorism threat level on low-rise buildings through fema 455 - Rapid Visual Screening. As a result, skyscrapers and high-rise buildings are relatively higher threat rating than consequences and vulnerability rating. This is caused by the fact that the terrorism threat level on skyscrapers is high due to their residents and their national or regional symbolism and visibility

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.341-348
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• 2020

The ability to extract useful information from an image, such as the human eye, is an interface technology essential for AI computer implementation. The building recognition technology has a lower recognition rate than other image recognition technologies due to the various building shapes, the ambient noise images according to the season, and the distortion by angle and distance. The computer vision based building recognition algorithms presented so far has limitations in discernment and expandability due to manual definition of building characteristics. This paper introduces the deep learning CNN (Convolutional Neural Network) model, and proposes new method to improve the recognition rate even by changes of building images caused by season, illumination, angle and perspective. This paper introduces the partial images that characterize the building, such as windows or wall images, and executes the training with whole building images. Experimental results show that the building recognition rate is improved by about 14% compared to the general CNN model.