• Title, Summary, Keyword: 벡터 공간 모델

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MPC-SVM Method using Segmentation of Space Voltage Vectors in a Voltage Source Inverter (전압원 인버터의 공간 전압 벡터 세분화를 통한 모델 예측 제어 기반의 SVM 기법)

  • Moon, Hyun-Cheol;Lee, June-Hee;Lee, June-Seok;Lee, Kyo-Beum
    • Proceedings of the KIPE Conference
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    • pp.163-164
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    • 2016
  • 본 논문에서는 전류품질 향상을 위해 다양한 전압벡터를 인가하는 모델 예측 제어 기반의 공간 벡터 변조 기법을 제안한다. 기존의 모델 예측 제어 기반의 전류제어는 제어주기 동안 하나의 스위치 상태가 인가되어 낮은 스위칭 횟수로 인해 높은 전류품질을 기대하기 힘들다. 이러한 이유로 본 논문에서 제안하는 방법은 공간 벡터도 상에서 전압벡터의 세분화를 통해 스위칭 횟수를 늘려 전류품질을 높일 수 있다. 또한 계통 위상각을 이용해 필요한 전압벡터만을 사용하여 비용함수를 계산하기 때문에 제어주기 동안 계산시간을 보장할 수 있다. 시뮬레이션을 통해 제안한 방법이 기존의 모델 예측 제어 기법의 전류제어 기법보다 향상된 전류품질을 보장하는 것을 검증하였다.

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Word Sense Similarity Clustering Based on Vector Space Model and HAL (벡터 공간 모델과 HAL에 기초한 단어 의미 유사성 군집)

  • Kim, Dong-Sung
    • Korean Journal of Cognitive Science
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    • v.23 no.3
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    • pp.295-322
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    • 2012
  • In this paper, we cluster similar word senses applying vector space model and HAL (Hyperspace Analog to Language). HAL measures corelation among words through a certain size of context (Lund and Burgess 1996). The similarity measurement between a word pair is cosine similarity based on the vector space model, which reduces distortion of space between high frequency words and low frequency words (Salton et al. 1975, Widdows 2004). We use PCA (Principal Component Analysis) and SVD (Singular Value Decomposition) to reduce a large amount of dimensions caused by similarity matrix. For sense similarity clustering, we adopt supervised and non-supervised learning methods. For non-supervised method, we use clustering. For supervised method, we use SVM (Support Vector Machine), Naive Bayes Classifier, and Maximum Entropy Method.

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Robust Face Recognition based on Gabor Feature Vector illumination PCA Model (가버 특징 벡터 조명 PCA 모델 기반 강인한 얼굴 인식)

  • Seol, Tae-In;Kim, Sang-Hoon;Chung, Sun-Tae;Jo, Seong-Won
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.6
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    • pp.67-76
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    • 2008
  • Reliable face recognition under various illumination environments is essential for successful commercialization. Feature-based face recognition relies on a good choice of feature vectors. Gabor feature vectors are known to be more robust to variations of pose and illumination than any other feature vectors so that they are popularly adopted for face recognition. However, they are not completely independent of illuminations. In this paper, we propose an illumination-robust face recognition method based on the Gabor feature vector illumination PCA model. We first construct the Gabor feature vector illumination PCA model where Gator feature vector space is rendered to be decomposed into two orthogonal illumination subspace and face identity subspace. Since the Gabor feature vectors obtained by projection into the face identity subspace are separated from illumination, the face recognition utilizing them becomes more robust to illumination. Through experiments, it is shown that the proposed face recognition based on Gabor feature vector illumination PCA model performs more reliably under various illumination and Pose environments.

An Analysis of Urban Residential Crimes using Eigenvector Spatial Filtering (아이겐벡터 공간필터링을 이용한 도시주거범죄의 분석)

  • Kim, Young-Ho
    • Journal of the Economic Geographical Society of Korea
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    • v.12 no.2
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    • pp.179-194
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    • 2009
  • The spatial distribution of crime incidences in urban neighborhoods is a reflection of their socio-economic environment and spatial inter-relations. Spatial interactions between offenders and victims lead to spatial autocorrelation of the crime incidences. The spatial autocorrelation among the incidences biases the interpretation of the ecological model in OLS framework. This research investigates residential crimes using residential burglaries and robberies occurred in the city of Columbus, Ohio, for 2000. In particular, the spatial distribution of incidence rates of residential crimes are accounted in OLS framework using eigenvectors, which reflect spatial dependence in crime patterns. Result presents that handling spatial autocorrelation enhanced model estimation, and both economic deprivation and crime opportunity are turned out significant in estimating residential crime rates.

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An Expansion of Vector Space for Document Classifications (문서 분류에 이용 가능한 벡터 공간의 확장 방법)

  • Lee, Samuel Sangkon;Yoo, Kyungseok
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.782-784
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    • 2015
  • 본 논문에서는 한국어 문서의 분류 정밀도 향상을 위해 애매어와 해소어 정보를 이용한 확장된 벡터 공간 모델을 제안하였다. 벡터 공간 모델에 사용된 벡터는 같은 정도의 가중치를 갖는 축이 하나 더 존재하지만, 기존의 방법은 그 축에 아무런 처리가 이루어지지 않았기 때문에 벡터끼리의 비교를 할 때 문제가 발생한다. 같은 가중치를 갖는 축이 되는 단어를 애매어라 정의하고, 단어와 분야 사이의 상호정보량을 계산하여 애매어를 결정하였다. 애매어에 의해 애매성을 해소하는 단어를 해소어라 정의하고, 애매어와 동일한 문서에서 출현하는 단어 중에서 상호정보량을 계산하여 해소어의 세기를 결정하였다. 본 논문에서는 애매어와 해소어를 이용하여 벡터의 차원을 확장하여 문서 분류의 정밀도를 향상시키는 방법을 제안하였다.

Development of a Standard Vector Data Model for Interoperability of River-Geospatial Information (하천공간정보의 상호운용성을 위한 표준벡터데이터 모델 개발)

  • Shin, Hyung-Jin;Chae, Hyo-Sok;Lee, Eul-Rae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.2
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    • pp.44-58
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    • 2014
  • In this study, a standard vector data model was developed for interoperability of river-geospatial information and for verification purpose the applicability of the standard vector model was evaluated using a model to RIMGIS vector data at Changnyeong-Hapcheon & Gangjung-Goryeong irrigation watershed. The standards from ISO and OGC were analyzed and the river geospatial data model standard was established by applying the standards. The ERD was designed based on the analysis information on data characteristics and relationship. The verification of RIMGIS vector data included points, lines and polygon to develope GDM was carried out by comparing with the data by layer. This conducting comparison of basic spatial data and attribute data to each record and spatial information vertex. The error in the process of conversion was 0 %, indicating no problem with model. Our Geospatial Data Model presented in this study provides a new and consistent format for the storage and retrieval of river geospatial data from connected database. It is designed to facilitators integrated analysis of large data sets collected by multiple institutes.

Subjective Tests Sub-System Applied with Generalized Vector Space Model (일반화된 벡터 공간 모델을 적용한 주관식 문제 채점 보조 시스템)

  • Oh, Jung-Seok;Chu, Seung-Woo;Kim, Yu-Seop;Lee, Jae-Young
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.965-968
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    • 2004
  • 기존의 주관식 문제 채점 보조 시스템은 자연어 처리의 어려움으로 인해 채점의 자동화가 어려워 전자우편 등을 통하여 채점자에게 채점 의뢰를 하는 수준이었다. 본 논문에서는 이러한 문제점을 해결하기 위하여 문제 공간을 벡터 공간으로 정의하고 벡터를 구성하는 각 자질간의 상관관계를 고려한 방법을 적용하였다. 먼저 학습자가 답안을 작성할 때 동의어 사용을 한다는 가정하에 출제자가 여러 개의 모범 답안을 작성하고 이들 답안을 말뭉치에 첨가하여 구성한 다음 형태소 분석기를 통하여 색인을 추출한다. 그리고 학습자가 작성한 답안 역시 색인을 추출한 다음, 이들 색인들을 각 자질로 정의한 벡터를 구성한다. 이렇게 구성된 벡터들을 이용하여 답안들간 유사도 측정을 하고, 유사도 범위에 따라 답안을 자동으로 정답과 오답으로 분류하려는 시스템을 제안한다. 170 문항의 주관식 문제을 제안된 방법으로 실험하여, 기존 모델에 비해 성능과 신뢰성 향상을 이룰 수 있었다.

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Korean Document Classification Using Extended Vector Space Model (확장된 벡터 공간 모델을 이용한 한국어 문서 분류 방안)

  • Lee, Samuel Sang-Kon
    • The KIPS Transactions:PartB
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    • v.18B no.2
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    • pp.93-108
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    • 2011
  • We propose a extended vector space model by using ambiguous words and disambiguous words to improve the result of a Korean document classification method. In this paper we study the precision enhancement of vector space model and we propose a new axis that represents a weight value. Conventional classification methods without the weight value had some problems in vector comparison. We define a word which has same axis of the weight value as ambiguous word after calculating a mutual information value between a term and its classification field. We define a word which is disambiguous with ambiguous meaning as disambiguous word. We decide the strengthness of a disambiguous word among several words which is occurring ambiguous word and a same document. Finally, we proposed a new classification method based on extension of vector dimension with ambiguous and disambiguous words.

An Intergrated GIS data model of Vector data and Raster data based on Quadtree for Spatial data processing (공간자료의 처리를 위한 사분트리에 기반한 래스터자료와 벡터자료의 통합 GIS모델)

  • Kang, Sin-Bong;Lee, Tae-Seung;Choi, Hee-Jay;Choy, Yoon-Chul
    • Journal of Korean Society for Geospatial Information System
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    • v.2 no.1
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    • pp.99-106
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    • 1994
  • Raster data mode and Vector data are the two major model in geographic information systems. These two data models are difficult to be intergrated because of their differences in structures and properties. Almost all of the current GIS systems process in one data model by converting one data type to another type. So. the loss and change of information caused by data conversiion degrades the accuracy of data. In this paper, we propose a new data model which can process two data models without conversion. We use quadtree for raster data and topological vector model for vector data. The output is formed as raster data model of quadtree. We can get more accurate overay output, and this intergrated model is more suitable for data like forest, landuses, soils that consist of classes which have small distribution changes.

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A Study on the Performance of Structured Document Retrieval Using Node Information (노드정보를 이용한 문서검색의 성능에 관한 연구)

  • Yoon, So-Young
    • Journal of the Korean Society for information Management
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    • v.24 no.1
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    • pp.103-120
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    • 2007
  • Node is the semantic unit and a part of structured document. Information retrieval from structured documents offers an opportunity to go subdivided below the document level in search of relevant information, making any element in an structured document a retrievable unit. The node-based document retrieval constitutes several similarity calculating methods and the extended node retrieval method using structure information. Retrieval performance is hardly influenced by the methods for determining document similarity The extended node method outperformed the others as a whole.