• Title/Summary/Keyword: Space classification

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Taxonomic Classification of Asteroids in Photometry with KMTNet

  • Choi, Sangho;Moon, Hong-Kyu;Roh, Dong-Goo;Chiang, Howoo;Sohn, Young-Jong
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.2
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    • pp.71.2-71.2
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    • 2019
  • In order to gather clues to surface mineralogy of asteroids, we classify their taxonomy based on their reflected spectra. It is remarkable that a large number of asteroids plotted in the proper orbital element space with distinct colors according to their taxonomic types reveal the dynamical evolution and the structure in the near-Earth space, the main-belt and beyond. Although we have ~1×106 known objects, no more than ~3×103 of them are properly classified taxonomically as visible-near infrared spectroscopy is costly. On the other hand, multi-wavelength broadband photometry in the visible region provides a rather inexpensive alternative tool for approximate taxonomy. Thus we have conducted multi-band observations systematically using Korea Microlensing Telescope Network (KMTNet) with BVRI and griz filters since back in 2015. We then applied aperture photometry with elliptical apertures to fit the trails of objects during the exposures, and classified them with the principle component indices of Ivezic et al. (2001). We will make use of our new, three dimensional asteroid classification scheme for the next step.

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Classification of Subgroups of Solar and Heliospheric Observatory (SOHO) Sungrazing Kreutz Comet Group by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Clustering Algorithm

  • Ulkar Karimova;Yu Yi
    • Journal of Astronomy and Space Sciences
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    • v.41 no.1
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    • pp.35-42
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    • 2024
  • Sungrazing comets, known for their proximity to the Sun, are traditionally classified into broad groups like Kreutz, Marsden, Kracht, Meyer, and non-group comets. While existing methods successfully categorize these groups, finer distinctions within the Kreutz subgroup remain a challenge. In this study, we introduce an automated classification technique using the densitybased spatial clustering of applications with noise (DBSCAN) algorithm to categorize sungrazing comets. Our method extends traditional classifications by finely categorizing the Kreutz subgroup into four distinct subgroups based on a comprehensive range of orbital parameters, providing critical insights into the origins and dynamics of these comets. Corroborative analyses validate the accuracy and effectiveness of our method, offering a more efficient framework for understanding the categorization of sungrazing comets.

A Study on Classification Standard for Efficient Maintenance System of Educational Facilities (교육시설물의 효율적 유지관리 체계정립을 위한 분류 기준연구)

  • Kim, Song-Hwa;Kim, Sung-Kyum;Cho, Chang-Yeon;Son, Jae-Ho;Kim, Jae-On
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2007.11a
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    • pp.403-407
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    • 2007
  • Korean Government conducted "a research for establishing the integrated construction information classification system" and suggested the classification system for the first and second level in terms of the complexity in May, 2001. The Ministry of Construction and Transportation announced a standard of the integrated construction information classification system using previous research in August, 2001. Since 2005, many BTL projects have been constructed for the educational facility. However, there is mixed official standard of the system for the educational facility. Moreover, it is difficult for the SPC to use the current "integrated construction information classification system", since the item in the educational facility cannot be easily located in the current system. Thus, this research suggests an efficient maintenance system for the educational facility. Two classification systems, space-oriented and element-oriented systems, are suggested to increase efficiency of the classification system.

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A Study on the Change of Spatial Structures of Shared Space at Urban Campuses - The opposite concept of Gridlock upon the change to shared campuses - (도심 캠퍼스 공유공간의 공간 구조 변화에 대한 연구 - 그리드락의 반대 개념으로서의 공유 캠퍼스로의 변화에 대하여 -)

  • Kang, Eunki;Baek, Jin
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.34 no.11
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    • pp.145-156
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    • 2018
  • Urban campus, one of the main urban facilities, is the representative place that is struggling with 'gridlock'. Due to privatization of space among different departments and space shortages, gridlock has been occurring as a result. The urban campus trying to solve this problem by changing the quality of space, especially the structure of the shared space, which is expected to be the solution to the grid lock problem. The main purpose of this study is to investigate the structural change in the university's shared space based on paradigm transition. The theoretical consideration is to analyze the spatial characteristics of university shared space that appear at different stages through a new perspective that compares the gridlock phenomenon and the shared paradigm. The framework of the analysis of the shared space, which has recently been restructured, is classified into the spatial characteristics of collaborative space, the creative space, and the common/complex space. In addition, these spatial characteristics are again analyzed through the division of legislative facility classification, management governance subject, area, building location and layout, exposure to the outside as well as the analysis of student and staff entry and exit, sharing structure of site and space, and the classification of program characteristics. The results are as follows: The restructured space is systemized so that the management governance of each space would be connected to each other to share information and space. Furthermore, the spatial boundary between colleges or between campus spaces are not only physically, but categorically clear. The restructured space has semi (or in-between)-spatial characteristics such as the intersection in inside and outside of the pedestrian's circulation and the mixture of programs. This study could serve as principal references in presenting the systematic analysis of directions of the shared spatial structure for the urban campus where new educational space is required due to the changes in the university system.

Optimum Design of Ship Design System Using Neural Network Method in Initial Design of Hull Plate

  • Kim, Soo-Young;Moon, Byung-Young;Kim, Duk-Eun
    • Journal of Mechanical Science and Technology
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    • v.18 no.11
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    • pp.1923-1931
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    • 2004
  • Manufacturing of complex surface plates in stern and stem is a major factor in cost of a preliminary ship design by computing process. If these hull plate parts are effectively classified, it helps to compute the processing cost and find the way to cut-down the processing cost. This paper presents a new method to classify surface plates effectively in the preliminary ship design using neural network. A neural-network-based ship hull plate classification program was developed and tested for the automatic classification of ship design. The input variables are regarded as Gaussian curvature distributions on the plate. Various applicable rules of network topology are applied in the ship design. In automation of hull plate classification, two different numbers of input variables are used. By observing the results of the proposed method, the effectiveness of the proposed method is discussed. As a result, high prediction rate was achieved in the ship design. Accordingly, to the initial design stage, the ship hull plate classification program can be used to predict the ship production cost. And the proposed method will contribute to reduce the production cost of ship.

Performance Improvement of Signature-based Traffic Classification System by Optimizing the Search Space (탐색공간 최적화를 통한 시그니쳐기반 트래픽 분석 시스템 성능향상)

  • Park, Jun-Sang;Yoon, Sung-Ho;Kim, Myung-Sup
    • Journal of Internet Computing and Services
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    • v.12 no.3
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    • pp.89-99
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    • 2011
  • The payload signature-based traffic classification system has to deal with large amount of traffic data, as the number of internet-based applications and network traffic continue to grow. While a number of pattern-matching algorithms have been proposed to improve processing speedin the literature, the performance of pattern matching algorithms is restrictive and depends on the features of its input data. In this paper, we studied how to optimize the search space in order to improve the processing speed of the payload signature-based traffic classification system. Also, the feasibility of our design choices was proved via experimental evaluation on our campus traffic trace.

On Optimizing LDA-extentions Using a Pre-Clustering (사전 클러스터링을 이용한 LDA-확장법들의 최적화)

  • Kim, Sang-Woon;Koo, Byum-Yong;Choi, Woo-Young
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.44 no.3
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    • pp.98-107
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    • 2007
  • For high-dimensional pattern recognition, such as face classification, the small number of training samples leads to the Small Sample Size problem when the number of pattern samples is smaller than the number of dimensionality. Recently, various LDA-extensions have been developed, including LDA, PCA+LDA, and Direct-LDA, to address the problem. This paper proposes a method of improving the classification efficiency by increasing the number of (sub)-classes through pre-clustering a training set prior to the execution of Direct-LDA. In LDA (or Direct-LDA), since the number of classes of the training set puts a limit to the dimensionality to be reduced, it is increased to the number of sub-classes that is obtained through clustering so that the classification performance of LDA-extensions can be improved. In other words, the eigen space of the training set consists of the range space and the null space, and the dimensionality of the range space increases as the number of classes increases. Therefore, when constructing the transformation matrix, through minimizing the null space, the loss of discriminatve information resulted from this space can be minimized. Experimental results for the artificial data of X-OR samples as well as the bench mark face databases of AT&T and Yale demonstrate that the classification efficiency of the proposed method could be improved.