• 영어영문학
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• 제56권6호
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• pp.1295-1310
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• 2010

In her "After Language Poetry: Innovation and Its Theoretical Discontents" in Contemporary Poetics (2007), Marjorie Perloff spotted Steve McCaffery's and Lyn Hejinian's points of reference and opacity/transparency in poetic language, and theorizes in her perspicacious insights that poetic language is not a window, to be seen through, a transparent glass pointing to something outside it, but a system of signs with its own semiological interconnectedness. Providing a critique and contextualizing Perloff's argument, the purpose of this paper is to introduce a topological model for poetry, language, and theory and further to elaborate the relation between the theory and the practice of language poetry in terms of "the revolution of language." Jacques Lacan's poetics of knowledge and of the topology of the mind, in particular, that of "extimacy," can articulate the way how language poetry problematizes the opposition between inside and outside in the substance of language itself. In fact, as signifiers always refer not to things, but to other signifiers, signifiers becomes unconscious, and can say more than they actually says. The original signifiers become unconscious through the process of repression which makes a structure of multiple and polyphonic signifying chains. Language poets use this polyphonic language of the Other at Freudian "Another Scene" and Lacan's "Other." When the reader participates the constructive meanings, the locus of the language writing transforms itself into that of the Other which becomes the open field of language. The language poet can even manage to put himself in the between-the-two, a strange place, the place of the dream and of the Unheimlichkeit (uncanny), and suture between "the outer skin of the interior" and "the inner skin of the exterior" of the impossible real of definite meaning. The objective goal of the evacuation of meaning is all the same the first aspect suggested by the aims of the experimentalism by the language poetry. The open linguistic fields of the language poetry, then, will be supplemented by The Freudian "unconscious" processes of dreams, free associations, slips of tongue, and symptoms which are composed of this polyphonic language. These fields can be properly excavated by the methods and topological mapping of the poetics of extimacy and of the klein bottle.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.637-641
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• 2007

Airborne LIDAR (Light Detection and Ranging) technology has reached a degree of the required accuracy in mapping professions, and advanced LIDAR systems are becoming increasingly common in the various fields of application. LiDAR data constitute an excellent source of information for reconstructing the Earth's surface due to capability of rapid and dense 3D spatial data acquisition with high accuracy. However, organizing the LIDAR data and extracting information from the data are difficult tasks because LIDAR data are composed of randomly distributed point clouds and do not provide sufficient semantic information. The main reason for this difficulty in processing LIDAR data is that the data provide only irregularly spaced point coordinates without topological and relational information among the points. This study introduces an efficient and robust method for automatic extraction of building footprints using airborne LIDAR data. The proposed method separates ground and non-ground data based on the histogram analysis and then rearranges the building boundary points using convex hull algorithm to extract building footprints. The method was implemented to LIDAR data of the heavily built-up area. Experimental results showed the feasibility and efficiency of the proposed method for automatic producing building layers of the large scale digital maps and 3D building reconstruction.

• 정보처리학회논문지A
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• 제11A권5호
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• pp.341-346
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• 2004

최근에 병렬처리를 위한 새로운 위상으로 하이퍼-스타 그래프 HS(m, k)가 제안되었다. 하이퍼-스타 그래프는 하이퍼큐브와 스타 그래프의 성질을 가지고 있으면서, 같은 노드수를 갖는 하이퍼큐브 보다 망비용이 우수한 그래프이다 본 논문에서는 하이퍼-스타 그래프 HS(m, k)가 하이퍼큐브의 서브그래프임을 증명한다. 그리고 정규형 그래프인 하이퍼-스타 HS(2n, n)가 제안된 매핑 기법에 의해 노드 대칭임을 보이며, 최소 높이를 갖는 스패닝 트리를 이용한 일-대-다 방송 기법을 제안하고, 방송 수행 시간이 2n-1임을 보인다.

• 정보처리학회논문지D
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• 제8D권5호
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• pp.507-512
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• 2001

특징 기반 유사성은 멀티미디어 데이터베이스 시스템에서 중요한 연구 쟁점이 되고 있다. 멀티미디어 데이터의 특징이 멀티미디어 객체들을 구별하는데 유용하다지만 특징 벡터의 차원의 수가 증가함에 따라 종래의 다차원 데이터 구조의 성능은 떨어지는 경향이 있다. $R^{*}-Tree$는 R-Tree의 가장 성공적인 병형으로 본 논문에서 고차원 특징 벡터를 위한 새로운 인덱싱 방법으로서 자기 조직화 맵 기반 $R^{*}-Tree$를 제안한다. 자기 조직화 맵 기잔 $R^{*}-Tree$는 고차원 데이터를 좀더 스칼라화해서 탐색할 수 있도록 SOM과 $R^{*}-Tree$를 결합하여 구축한 인덱싱 기법이다. 자기 조직 맵은 고차원 특징 벡터들로부터 2차원 공간으로의 맵핑을 제공한다. 그러나 맵을 위상 특징 맵이라 하고 인접 노느에서 서로 유사한 특징 벡터들을 모아서 입력데이터의 특징 공간들 속에 유사성을 보존하는데 위상 특징 맵의 각 노드는 코드북 벡터를 가지고 있다. 실험적으로 4만개의 이미지로부터 추출된 색깔 특징 벡터들을 이용하여 자기 조직화 맵 기반 $R^{*}-Tree$의 검색시간 비용과 자기 조직화 맵과 $R^{*}-Tree$의 검색 시간 비용을 비교한다. 그 결과 $R^{*}-Tree$를 구축하는데 필요한 노드 수와 검색 시간 비용이 감소됨으로써 자기 조직화 맵 기반 $R^{*}-Tree$는 자기 조직화 맵과 $R^{*}-Tree$보다 훨씬 우수한 성능을 나타냄이 입증되었다.

• 한국균학회지
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• 제43권4호
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• pp.231-238
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• 2015

팽이버섯(Flammulina velutipes) 25품종의 유전체 재분석 데이터를 표준유전체(KACC42781)와 비교하여 genomewide single nucleotide polymorphism (SNP)를 선발하였다. 균주에 따른 mapping율의 차이는 균주간 변이를 반영하였으며, genome-wide SNP분포는 homozygous SNP, heterozygous SNP로 구분되었으며 모두 균주에 따른 변이가 크게 나타났다. 수집균주들 사이의 유연관계를 살펴보기 위해, 계통수를 그려본 결과, Group I은 F. velutipes var. 계통인 ASI 4062, 4148, 4195이 묶여지고, Group II는 ASI 4188 F. elastica, ASI 4190 F. fennae, ASI 4194 F. rossica의 다른 종이 별도의 그룹을 형성하였다. 그 외 F. velutipes 19개 계통은 같은 그룹으로 나타났으며 그 유전적 자리를 잘 반영하였다. 한편 백색 group과 갈색 group을 유연관계로 분석하고자 시도하였으나 색깔에 따른 group은 이루어지지 않았다. 한국 백색 품종인 ASI 4210, 4166, 4178과 일본 백색 품종인 ASI 4209, 4167을 분석한 결과 phylogenetic tree상에서 한국 백색 품종과 일본 백색 품종간의 유전적 상동성이 매우 높음을 확인할 수 있었다.

• 조명전기설비학회논문지
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• 제13권3호
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• pp.56-63
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• 1999

전력계통의 변전소 설비들은 계통의 확장에 따라 점점 복잡하고 거대해지고 있다. 또한, 몇몇 장비들은 점점 노후되고, 종종 예상치 않은 고장을 일으킨다. 변전소 설비들 중 변압기의 신뢰도를 증가시키기 위해서, 변압기의 진단기법 개발이 매우 필요하다. 본 연구에서는, 전력용 변압기의 용해 가스들을 근거로 KSOM(Kohonen Self Organizing Map)에 의한 열화정도와 원인의 분석기법을 개발하였다. KOSM은 용해가스에 의해 구성된 다차원 패텅을 이차원 평면에 지형학적 맵핑이 가능하다. 그리고 정장변압기에 대한 열화의 정도와 잠재적인 열화의 가능성을 제안된 정량적 지표에 의해 제시하였다. 아울러, 변압기의 열화과정을 제안된 지표를 근거로 특정한 변압기에 대해 분석하였다. 제안된 방법의 타당성을 입증하기 위해서 사례연구가 수행되고, 그 결과를 제시하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권2호
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• pp.800-816
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• 2018

In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.

• 한국측량학회지
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• 제25권6_1호
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• pp.507-516
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• 2007

Segmentation and organization of the LiDAR (Light Detection and Ranging) data of the Earth's surface are difficult tasks because the captured LiDAR data are composed of irregularly distributed point clouds with lack of semantic information. The reason for this difficulty in processing LiDAR data is that the data provide huge amount of the spatial coordinates without topological and/or relational information among the points. This study introduces LiDAR data segmentation technique by utilizing histograms of the LiDAR height image data and analyzing roof shape for 3D reconstruction and visualization of the buildings. One of the advantages in utilizing LiDAR height image data is no registration required because the LiDAR data are geo-referenced and ortho-projected data. In consequence, measurements on the image provide absolute reference coordinates. The LiDAR image allows measurement of the initial building boundaries to estimate locations of the side walls and to form the planar surfaces which represent approximate building footprints. LiDAR points close to each side wall were grouped together then the least-square planar surface fitting with the segmented point clouds was performed to determine precise location of each wall of an building. Finally, roof shape analysis was performed by accumulated slopes along the profiles of the roof top. However, simulated LiDAR data were used for analyzing roof shape because buildings with various shapes of the roof do not exist in the test area. The proposed approach has been tested on the heavily built-up urban residential area. 3D digital vector map produced by digitizing complied aerial photographs was used to evaluate accuracy of the results. Experimental results show efficiency of the proposed methodology for 3D building reconstruction and large scale digital mapping especially for the urban area.