• 제목/요약/키워드: Space classification

검색결과 1,153건 처리시간 0.028초

RECURRENT PATTERNS IN DST TIME SERIES

  • Kim, Hee-Jeong;Lee, Dae-Young;Choe, Won-Gyu
    • Journal of Astronomy and Space Sciences
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    • 제20권2호
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    • pp.101-108
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    • 2003
  • This study reports one approach for the classification of magnetic storms into recurrent patterns. A storm event is defined as a local minimum of Dst index. The analysis of Dst index for the period of year 1957 through year 2000 has demonstrated that a large portion of the storm events can be classified into a set of recurrent patterns. In our approach, the classification is performed by seeking a categorization that minimizes thermodynamic free energy which is defined as the sum of classification errors and entropy. The error is calculated as the squared sum of the value differences between events. The classification depends on the noise parameter T that represents the strength of the intrinsic error in the observation and classification process. The classification results would be applicable in space weather forecasting.

다중 레이블 분류의 정확도 향상을 위한 스킵 연결 오토인코더 기반 레이블 임베딩 방법론 (Label Embedding for Improving Classification Accuracy UsingAutoEncoderwithSkip-Connections)

  • 김무성;김남규
    • 지능정보연구
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    • 제27권3호
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    • pp.175-197
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    • 2021
  • 최근 딥 러닝 기술의 발전으로 뉴스, 블로그 등 다양한 문서에 포함된 텍스트 분석에 딥 러닝 기술을 활용하는 연구가 활발하게 수행되고 있다. 다양한 텍스트 분석 응용 가운데, 텍스트 분류는 학계와 업계에서 가장 많이 활용되는 대표적인 기술이다. 텍스트 분류의 활용 예로는 정답 레이블이 하나만 존재하는 이진 클래스 분류와 다중 클래스 분류, 그리고 정답 레이블이 여러 개 존재하는 다중 레이블 분류 등이 있다. 특히, 다중 레이블 분류는 여러 개의 정답 레이블이 존재한다는 특성 때문에 일반적인 분류와는 상이한 학습 방법이 요구된다. 또한, 다중 레이블 분류 문제는 레이블과 클래스의 개수가 증가할수록 예측의 난이도가 상승한다는 측면에서 데이터 과학 분야의 난제로 여겨지고 있다. 따라서 이를 해결하기 위해 다수의 레이블을 압축한 후 압축된 레이블을 예측하고, 예측된 압축 레이블을 원래 레이블로 복원하는 레이블 임베딩이 많이 활용되고 있다. 대표적으로 딥 러닝 모델인 오토인코더 기반 레이블 임베딩이 이러한 목적으로 사용되고 있지만, 이러한 기법은 클래스의 수가 무수히 많은 고차원 레이블 공간을 저차원 잠재 레이블 공간으로 압축할 때 많은 정보 손실을 야기한다는 한계가 있다. 이에 본 연구에서는 오토인코더의 인코더와 디코더 각각에 스킵 연결을 추가하여, 고차원 레이블 공간의 압축 과정에서 정보 손실을 최소화할 수 있는 레이블 임베딩 방법을 제안한다. 또한 학술연구정보서비스인 'RISS'에서 수집한 학술논문 4,675건에 대해 각 논문의 초록으로부터 해당 논문의 다중 키워드를 예측하는 실험을 수행한 결과, 제안 방법론이 기존의 일반 오토인코더 기반 레이블 임베딩 기법에 비해 정확도, 정밀도, 재현율, 그리고 F1 점수 등 모든 측면에서 우수한 성능을 나타냄을 확인하였다.

현대한옥의 유형 분류 -2000년 이후 건축가의 디자인을 중심으로- (Type Classification of Contemporary Hanok -Focusing on Architects' Designs since 2000-)

  • 이용희;김현섭
    • 건축역사연구
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    • 제25권5호
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    • pp.51-62
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    • 2016
  • Since the recent Hanok boom in Korea, Contemporary Hanok has been evolving in terms of structure, space, form, etc. To get a comprehensive understanding of the diversified Contemporary Hanok, this paper aims at its type classification by analyzing architects' designs since 2000. The criteria for the classification are two: (1) renovation [Re] or new construction [New]; and (2) degree of Contemporary Hanok's deviation from the traditional Hanok's standard - maintaining the traditional form [Main]; changing space within the traditional form [Space]; changing the traditional frame [Frame]; and juxtaposing the traditional and the modern [Combi]. From the two criteria, this paper deduced eight types of Contemporary Hanok, named respectively: Re-Main, New-Main, Re-Space, New-Space, Re-Frame, New-Frame, Re-Combi, and New-Combi, and studied their cases. It can be argued that various aspects of Contemporary Hanok and their critical meanings were well-investigated through this type classification and case-studies.

다중 클래스 분포 문제에 대한 분류 정확도 분석 (Analysis of Classification Accuracy for Multiclass Problems)

  • 최의선;이철희
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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    • pp.190-193
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    • 2000
  • In this paper, we investigate the distribution of classification accuracies of multiclass problems in the feature space and analyze performances of the conventional feature extraction algorithms. In order to find the distribution of classification accuracies, we sample the feature space and compute the classification accuracy corresponding to each sampling point. Experimental results showed that there exist much better feature sets that the conventional feature extraction algorithms fail to find. In addition, the distribution of classification accuracies is useful for developing and evaluating the feature extraction algorithm.

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Photometric and Spectroscopic Morphology Classifications Using SDSS DR7 : Virgo Cluster

  • 김석;이수창;성언창;;;이영대;정지원;박민아;이원형
    • 천문학회보
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    • 제36권2호
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    • pp.69.1-69.1
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    • 2011
  • While the Virgo Cluster Catalog (VCC) is well established catalog from deep photographic plate survey, with available survey data recently released (e.g., SDSS), it can be further updated concerning the membership and morphology of galaxies. While membership and morphology of galaxies included in the VCC are based on the single band imaging data, thanks to the multi-color imaging and spectroscopic observations of SDSS, we are able to revise the membership and morphology of sample galaxies in the fields of the Virgo cluster. We present a new catalog of galaxies in the Virgo cluster using SDSS DR7 data, the extended Virgo cluster catalog. Using SDSS imaging and spectroscopic data, we introduce two kinds of galaxy classifications which are complementary each other. In addition to traditional morphological classification by visual inspection of the images ("Primary Classification"), we also attempt to classify galaxies with the spectroscopic features ("Secondary Classification"). The primary classification is basically based on the scheme of galaxy morphological classification of VCC. The secondary classification relies on the SED shape and presence of emission/absorption lines returned from SDSS. Our morphological classifications allow to study the evolution and associated star formation histories of galaxies in the Virgo cluster.

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초등학교 공간계획을 위한 지역유형분류 및 특성분석 -서울·경기 지역을 중심으로- (A Study on Community Classification and Property Analysis for Space Planning of Elementary School -Focusing on the Seoul and Gyeonggi Province-)

  • 이상민
    • 교육녹색환경연구
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    • 제3권2호
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    • pp.21-37
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    • 2003
  • This study has the purpose for analysis of each region's property in order to plan a elementary school's space according to community property. For this analysis. we used classification method through classification analysis. classification analysis is one of the useful statistical analysis methode for determining each region's policy through classifying regions which have a similar property. On this study, Seoul and Kyongkido is classified by 4 groups and each group has a different community property. Such a analysis is thought of helping establishing the objective. reasonable space-plan through comparative analysis between subjective claim and objective state indicator of each region.

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SPACE-LIKE SURFACES WITH 1-TYPE GENERALIZED GAUSS MAP

  • Choi, Soon-Meen;Ki, U-Hang;Suh, Young-Jin
    • 대한수학회지
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    • 제35권2호
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    • pp.315-330
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    • 1998
  • Chen and Piccinni [7] have classified all compact surfaces in a Euclidean space $R^{2+p}$ with 1-type generalized Gauss map. Being motivated by this result, the purpose of this paper is to consider the Lorentz version of the classification theorem and to obtain a complete classification of space-like surfaces in indefinite Euclidean space $R_{p}$ $^{2+p}$ with 1-type generalized Gauss map.p.

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국내 문학관 건축의 유형과 공간.형태구성 특징에 관한 연구 - 경상도 지역을 중심으로 - (A Study on the Pattern of Domestic Literature Museum and the Space.Form Composition Characteristic - Focused on Gyeongsang-do region -)

  • 장훈익
    • 한국디지털건축인테리어학회논문집
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    • 제11권3호
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    • pp.69-77
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    • 2011
  • This study considered the characteristic through the present state of domestic literature museum and grouping by type to help the understanding for domestic literature museum. And conducted a case study on Gyeongsang-do region literature museum to grasp the space form composition characteristic of literature museum. The result gained through these studies is as follows. First, grouping domestic literature museum by type, we can conduct the classification founded on location character, an exhibition writer, and the main body of erection and maintenance management. Second, the classification founded on location character of literature museum is able to be divided into the type of the house of writer's birth, a literary work, writing, and etc. Third, the classification founded on the number of exhibition writers can be divided into the type of independence, an individual pavilion, and integration. Fourthly, the classification founded on the main body of erection and management can be divided into the case in which a local self-governing body is wholly in charge of erection and management, a local government is in charge of erection but entrusts management to a corporate body, etc., a corporate body is in charge of erection and management, and a private person is in charge of erection and management. Fifthly, speaking of the characteristic by type of the Gyeongsang-do region literature museum, the classification founded on location has the type of the house of writer's birth the most, the classification founded on the number of exhibition writers has the type of independence the most, and the classification founded on the main body of erection and management has the most the type in which a local self-governing body is in charge of erection and management. Also, for the characteristic by space form, the case which expresses the character of Korean traditional architecture by form is many the most, and there are pieces of work to pursue shape beauty through the articulation of mass or molding manipulation and the change by space form through the proper combination of concreteness and abstraction as well.

Kernel Methods를 이용한 Human Breast Cancer의 subtype의 분류 및 Feature space에서 Clinical Outcome의 pattern 분석 (Subtype classification of Human Breast Cancer via Kernel methods and Pattern Analysis of Clinical Outcome over the feature space)

  • Kim, Hey-Jin;Park, Seungjin;Bang, Sung-Uang
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
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    • pp.175-177
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    • 2003
  • This paper addresses a problem of classifying human breast cancer into its subtypes. A main ingredient in our approach is kernel machines such as support vector machine (SVM). kernel principal component analysis (KPCA). and kernel partial least squares (KPLS). In the task of breast cancer classification, we employ both SVM and KPLS and compare their results. In addition to this classification. we also analyze the patterns of clinical outcomes in the feature space. In order to visualize the clinical outcomes in low-dimensional space, both KPCA and KPLS are used. It turns out that these methods are useful to identify correlations between clinical outcomes and the nonlinearly protected expression profiles in low-dimensional feature space.

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가우시안 혼합모델을 이용한 솔라셀 색상분류 (Solar Cell Classification using Gaussian Mixture Models)

  • 고진석;임재열
    • 반도체디스플레이기술학회지
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    • 제10권2호
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    • pp.1-5
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    • 2011
  • In recent years, worldwide production of solar wafers increased rapidly. Therefore, the solar wafer technology in the developed countries already has become an industry, and related industries such as solar wafer manufacturing equipment have developed rapidly. In this paper we propose the color classification method of the polycrystalline solar wafer that needed in manufacturing equipment. The solar wafer produced in the manufacturing process does not have a uniform color. Therefore, the solar wafer panels made with insensitive color uniformity will fall off the aesthetics. Gaussian mixture models (GMM) are among the most statistically mature methods for clustering and we use the Gaussian mixture models for the classification of the polycrystalline solar wafers. In addition, we compare the performance of the color feature vector from various color space for color classification. Experimental results show that the feature vector from YCbCr color space has the most efficient performance and the correct classification rate is 97.4%.