• Title, Summary, Keyword: 공간 가중치

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Comparison of Segmentation Weight Parameters for Object-oriented Classification (객체기반 영상분류를 위한 영상분할 가중치 비교)

  • Lee, Jung-Bin;Heo, Joon;Sohn, Hong-Gyoo;Yun, Kong-Hyun
    • 한국공간정보시스템학회:학술대회논문집
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    • pp.289-292
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    • 2007
  • 객체기반 영상분류를 위한 영상분할에 있어서 중요한 요소로는 분할축척(Scale), 분광 정보(Color), 공간 정보(Shape) 등이 있으며 공간 정보에 해당하는 공간 변수는 평활도(Smoothness)와 조밀도(Compactness)가 있다. 이들 가중치의 선택이 최종적으로 객체기반 영상분류의 결과를 좌우하게 된다. 본 연구는 객체기반 영상분류의 준비 과정이라 할 수 있는 영상분할에 있어서 다양한 가중치를 적용을 통하여 영상을 분할하였다. 영상분할을 위해 적용한 가중치는 10, 20, 30의 분할축척(Scale)과 분광 정보(Color)와 공간 정보(Shape)간의 가중치 조합, 공간 변수인 평활도(Smoothness)와 조밀도(Compactness)간의 가중치 조합을 사용하였다. 각 가중치 조합을 통하여 분할된 영상의 분석은 Moran's I 와 객체 내부 분산(Intrasegment Variance)을 이용하여 분석하였다. 각 객체간의 상관관계 분석을 위하여 Moran's I를 계산하였으며 분류된 지역의 동질성을 분석하기 위하여 객체 면적을 고려한 객체 내부 분산(Intrasegment Variance)값을 계산하였다. Moran's I 가 낮은 값을 가질수록 객체 간의 공간상관관계가 낮아지므로 이웃 객체간의 이질성은 높아지며 객체 내부 분산(Intrasegment Variance)이 낮은 값을 가질수록 지역간의 동질성은 높아지게 된다. Moran's I 와 객체 내부 분산(Intrasegment Variance)의 조합을 통하여 객체기반 영상분류 시 가장 높은 분류 정확도가 예상되는 밴드별 영상분할 가중치를 얻을 수 있다.

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3D Path-Planning for Weighted-Regions by Weighted-Octree Method (가중 8진트리를 이용한 가중치 지역에 대한 최적경로설정)

  • 임상석;이창규;황주영;박규호
    • Proceedings of the Korean Information Science Society Conference
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    • pp.440-442
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    • 1999
  • 본 논문에서는 가중치 3차원 공간을 가중치 8진트리를 이용하여 나타낸다. 가중치 8진트리는 가중치 영역을 계층적으로 나타내고 용이하게 분해능을 조절할 수 있게 한다. 즉 높은 가중치를 갖는 공간은 세밀하게 분해하고 낮은 가중치를 갖는 공간은 성길하게 분해하여 최적의 경로설정을 바른 시간에 할 수 있도록 한다. 이러한 8진트리를 바탕으로 하여 최적 경로 설정하는 종합틀(Framework)을 제시하고 실험을 통하여 그 결과를 제시한다.

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Research on Areal Interpolation Methods and Error Measurement Techniques for Reorganizing Incompatible Regional Data Units : The Population Weighted Interpolation (지역 자료의 공간 단위 재구성 기법 및 에러 검증 : 인구가중치 내삽법)

  • Shin, Jung-Yeop
    • Journal of the Korean association of regional geographers
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    • v.10 no.2
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    • pp.389-406
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    • 2004
  • with the increasing popularity of regional studies, the importance of regional data has been recognized dramatically in recent years. However, due to potential problems from the intrinsic characteristics of aggregate regional data for the research, and incompatible regional units between source and target regional data units, the method for reorganizing the regional data units for a given research analysis should be required. In this regard, the purpose of this research is to review the significant interpolation methods for reorganizing the data units and, based on it, to propose the population weighted interpolation method. For the first purpose, areal weighted interpolation method, pycnophylactic method, dasymetric method, area-to-point method were reviewed. The proposed population-weighted interpolation method was applied to the case study of population census regional data in Erie County, NY, compared with areal weighted interpolation method, pycnophylactic method in terms of several statistical characteristics.

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Error Analysis of Muskingum-Cunge Flood Routing Method (Muskingum-Cunge 홍수추적 방법의 오차해석)

  • Kim, Dae-Geun;Seo, Il-Won
    • Journal of Korea Water Resources Association
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    • v.36 no.5
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    • pp.751-760
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    • 2003
  • Error analysis of finite difference equation on the Muskingum-Cunge flood routing method with free time and space weighting factor was carried out. The error analysis shows that the numerical solution of the Muskingum-Cunge method becomes diverged with time when the sum of time weighting factor and space weighting factor is greater than 1.0. Numerical diffusion increases when the sum of time weighting factor and space weighting factor decreases. Numerical diffusion and numerical oscillation increase when the grid resolution is coarse. Numerical experiments and field applications show that the Muskingum-Cunge method with free space weighting factor is more effective for simulating the flood routing with great peak diminution than conventional Muskingum-Cunge method with fixed space weighting factor, 0.5.

Multilingual Story Link Detection based on Properties of Event Terms (사건 어휘의 특성을 반영한 다국어 사건 연결 탐색)

  • Lee Kyung-Soon
    • The KIPS Transactions:PartB
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    • v.12B no.1
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    • pp.81-90
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    • 2005
  • In this paper, we propose a novel approach which models multilingual story link detection by adapting the features such as timelines and multilingual spaces as weighting components to give distinctive weights to terms related to events. On timelines term significance is calculated by comparing term distribution of the documents on that day with that on the total document collection reported, and used to represent the document vectors on that day. Since two languages can provide more information than one language, term significance is measured on each language space and used to refer the other language space as a bridge on multilingual spaces. Evaluating the method on Korean and Japanese news articles, our method achieved $14.3{\%}\;and\;16.7{\%}$ improvement for mono- and multi-lingual story pairs, and for multilingual story pairs, respectively. By measuring the space density, the proposed weighting components are verified with a high density of the intra-event stories and a low density of the inter-events stories. This result indicates that the proposed method is helpful for multilingual story link detection.

Kalman-Filter Estimation and Prediction for a Spatial Time Series Model (공간시계열 모형의 칼만필터 추정과 예측)

  • Lee, Sung-Duck;Han, Eun-Hee;Kim, Duck-Ki
    • Communications for Statistical Applications and Methods
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    • v.18 no.1
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    • pp.79-87
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    • 2011
  • A spatial time series model was used for analyzing the method of spatial time series (not the ARIMA model that is popular for analyzing spatial time series) by using chicken pox data which is a highly contagious disease and grid data due to ARIMA not reflecting the spatial processes. Time series model contains a weighting matrix, because that spatial time series model influences the time variation as well as the spatial location. The weighting matrix reflects that the more geographically contiguous region has the higher spatial dependence. It is hypothesized that the weighting matrix gives neighboring areas the same influence in the study of the spatial time series model. Therefore, we try to present the conclusion with a weighting matrix in a way that gives the same weight to existing neighboring areas in the study of the suitability of the STARMA model, spatial time series model and STBL model, in the comparative study of the predictive power for statistical inference, and the results. Furthermore, through the Kalman-Filter method we try to show the superiority of the Kalman-Filter method through a parameter assumption and the processes of prediction.

Semantic Indexing Using Concept Space (개념 공간을 이용한 의미 인덱싱)

  • 강보영;김혜정;황선옥;이상조
    • Proceedings of the Korean Information Science Society Conference
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    • pp.380-382
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    • 2003
  • 본 논문은 문서내의 의미적인 관계에 기반하여, 문서의 내용을 보다 잘 추측할 수 있는 의미 인덱스 추출 및 가중치 부여 시스템을 제안하고자 한다. 문서 내의 개념 추출에 있어서는 기존의 어휘 체인(lexical chains)에 관한 연구를 확장하여 적용였다. 또한, 추출된 개념에서 중요 어휘에 가중치를 부여하기 위해서, 개념 벡터 공간을 이용한 정보성(information quantity)과 정보비(information ratio)를 정의하고, 인덱스의 가중치를 측정할 수 있는 정량화 할 수 있는 척도로 제시하였다.

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A Study on the Spatial Weighted Filter in AWGN Environment (AWGN 환경에서 공간 가중치 필터에 관한 연구)

  • Long, Xu;Kim, Nam-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.3
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    • pp.724-729
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    • 2013
  • Recently, with the popularization of digital devices, the requirements of image quality is becoming higher and higher. However, the images are frequently corrupted in the image data processing, there are several reasons for this and the noise is considered as the main reason. Therefore, in order to alleviate the influence of AWGN(additive white Gaussian noise) in image, this paper puts forward the spatial weighted filtering algorithm. The algorithm set the weighted value according to the spatial distance, compared with the existing methods. The algorithm not only alleviated the influence of AWGN effectively but also reserved image details.

Minimizing Redundant Route Nodes in USN by Integrating Spatially Weighted Parameters: Case Study for University Campus (가중치가 부여된 공간변수에 의거하여 USN 루트노드 최소화 방안 -대학 캠퍼스를 사례로-)

  • Kim, Jin-Taek;Um, Jung-Sup
    • Journal of the Korean Geographical Society
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    • v.45 no.6
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    • pp.788-805
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    • 2010
  • The present USN (Ubiquitous Sensor Networks) node deployment practices have many limitations in terms of positional connectivity. The aim of this research was to minimize a redundancy of USN route nodes, by integrating spatially weighted parameters such as visibility, proximity to cell center, road density, building density and cell overlapping ratio into a comprehensive GIS database. This spatially weighted approach made it possible to reduce the number of route nodes (11) required in the study site as compared to that of the grid network method (24). The field test for RSSI (Received Signal Strength Indicator) indicates that the spatially weighted deployment could comply with the quality assurance standard for node connectivity, and that reduced route nodes do not show a significant degree of signal fluctuation for different site conditions. This study demonstrated that the spatially weighted deployment can be used to minimize a redundancy of USN route nodes in a routine manner, and the quantitative evidence removing a redundancy of USN route nodes could be utilized as major tools to ensure the strong signal in the USN, that is frequently encountered in real applications.

Prediction for spatial time series models with several weight matrices (여러 가지 가중행렬을 가진 공간 시계열 모형들의 예측)

  • Lee, Sung Duck;Ju, Su In;Lee, So Hyun
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.1
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    • pp.11-20
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    • 2017
  • In this paper, we introduced linear spatial time series (space-time autoregressive and moving average model) and nonlinear spatial time series (space-time bilinear model). Also we estimated the parameters by Kalman Filter method and made comparative studies of power of forecast in the final model. We proposed several weight matrices such as equal proportion allocation, reciprocal proportion between distances, and proportion of population sizes. For applications, we collected Mumps data at Korea Center for Disease Control and Prevention from January 2001 until August 2008. We compared three approaches of weight matrices using the Mumps data. Finally, we also decided the most effective model based on sum of square forecast error.