• Title/Summary/Keyword: cluster method

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Classification of Terrestrial LiDAR Data Using Factor and Cluster Analysis (요인 및 군집분석을 이용한 지상 라이다 자료의 분류)

  • Choi, Seung-Pil;Cho, Ji-Hyun;Kim, Yeol;Kim, Jun-Seong
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.4
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    • pp.139-144
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    • 2011
  • This study proposed a classification method of LIDAR data by using simultaneously the color information (R, G, B) and reflection intensity information (I) obtained from terrestrial LIDAR and by analyzing the association between these data through the use of statistical classification methods. To this end, first, the factors that maximize variance were calculated using the variables, R, G, B, and I, whereby the factor matrix between the principal factor and each variable was calculated. However, although the factor matrix shows basic data by reducing them, it is difficult to know clearly which variables become highly associated by which factors; therefore, Varimax method from orthogonal rotation was used to obtain the factor matrix and then the factor scores were calculated. And, by using a non-hierarchical clustering method, K-mean method, a cluster analysis was performed on the factor scores obtained via K-mean method as factor analysis, and afterwards the classification accuracy of the terrestrial LiDAR data was evaluated.

Natural Scene Text Binarization using Tensor Voting and Markov Random Field (텐서보팅과 마르코프 랜덤 필드를 이용한 자연 영상의 텍스트 이진화)

  • Choi, Hyun Su;Lee, Guee Sang
    • Smart Media Journal
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    • v.4 no.4
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    • pp.18-23
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    • 2015
  • In this paper, we propose a method for detecting the number of clusters. This method can improve the performance of a gaussian mixture model function in conventional markov random field method by using the tensor voting. The key point of the proposed method is that extracts the number of the center through the continuity of saliency map of the input data of the tensor voting token. At first, we separate the foreground and background region candidate in a given natural images. After that, we extract the appropriate cluster number for each separate candidate regions by applying the tensor voting. We can make accurate modeling a gaussian mixture model by using a detected number of cluster. We can return the result of natural binary text image by calculating the unary term and the pairwise term of markov random field. After the experiment, we can confirm that the proposed method returns the optimal cluster number and text binarization results are improved.

Energy Efficient Clustering Method for Dynamic Cluster based Wireless Sensor Network (무선 센서 네트워크 환경에서의 dynamic cluster 기반의 에너지 효율적인 클러스터링 기법)

  • Park Jung-Im;Kang Jung-Hun;Park Myong-Soon
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06d
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    • pp.139-141
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    • 2006
  • 무선 센서 네트워크에서 이벤트 영역을 탐지하는데 있어 이동성을 가진 target objects의 첫 boundary information을 탐지하는 것도 중요하지만 탐지 후 변화하는 boundary information을 지속적으로 반영하는 것 또한 매우 중요하다. 따라서 본 논문에서는 boundary information의 지속적인 반영방법에 대해, Event의 발생빈도수에 따른 clustering update 모델링과 특정 상황에 따른 cluster를 재구성해야 하는 방안을 비교 분석한 후 이에 대한 클러스터링의 에너지 효율적인 방법에 대해서 제안하고 있다.

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Color Data Clustering Algorithm using Fuzzy Color Model (퍼지컬러 모델을 이용한 컬러 데이터 클러스터링 알고리즘1)

  • Kim, Dae-Won;Lee, Kwang H.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.05a
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    • pp.119-122
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    • 2002
  • The research Interest of this paper is focused on the efficient clustering task for an arbitrary color data. In order to tackle this problem, we have tiled to model the inherent uncertainty and vagueness of color data using fuzzy color model. By laking a fuzzy approach to color modeling, we could make a soft decision for the vague regions between neighboring colors. The proposed fuzzy color model defined a three dimensional fuzzy color ball and color membership computation method with the two inter-color distance measures. With the fuzzy color model, we developed a new fuzzy clustering algorithm for an efficient partition of color data. Each fuzzy cluster set has a cluster prototype which is represented by fuzzy color centroid.

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Classification of Bodytype on Adult Male for the Apparel Sizing System (Part 3) -Bodytype of Trunk from the Photoqraphic Data- (남성복의 치수규격을 위한 체형분류(제3보) -사진자료에 의한 동체부의 분류-)

  • 김구자
    • Journal of the Korean Society of Clothing and Textiles
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    • v.19 no.6
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    • pp.924-932
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    • 1995
  • Concept of the comfort and fitness has become a major concern in the basic function of the ready.made clothes. Until now ready-made clothes were not made by on the basis of the bodytype, but by the body size only This research was performed to classify and characterize the bodytypes of Korean adult males. Sample size was 1290 subjects and their age range was from 19 to 54 years old. 25 variables from the photographic data were applied to analyze the bodytype of trunk. Data were analyzed by the multivariate method, especially factor and cluster analysis. The groups forming a cluster can be subdivided into 5 sets by crosstabulation extracted by the hierarchical cluster analysis. 5 bodytypes classified by the photographic sources could be combined with the anthropometric data and were demonstrated with 5 silhouette. Type 3 and 4 in trunk were dominant and were composed of the majority of 55.6% of the subjects. Bodytypes of Korean males were influenced by the degree of posture erectness and of curvature of the front side of the body in waist and abdomen.

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High Availability Web Server Cluster Using Self-healing Technique (자가 치유 기법을 이용한 고가용도 웹 서버 클러스터)

  • Chung, Ji Yung;Kim, Young Ro
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.5 no.1
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    • pp.23-32
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    • 2009
  • Although the web is becoming a widely accepted medium, it provides relatively poor performance and low availability. A cluster consists of a collection of interconnected stand-alone computers working together and provides a high-availability solution in application area such as web services or information systems. Web server clusters require a high-availability service with a proactive and practical fault management. However, as the system complexity grows, it is not easy to meet the requirement. Therefore, web server clusters must have self-fault management capability for meeting high-availability requirement. In this paper, we propose high availability web server clusters using self-healing technique with a minimal human intervention. Our experimental results show that a proposed method can be used to improve the availability of web server clusters.

A Study on Reduction Method of Electromagnetic Noise of PCB for Vehicle Cluster (자동차 클러스터용 PCB의 전자기 노이즈 저감 방안 연구)

  • Kim, Byeong-Woo;Hur, Jin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.7
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    • pp.1336-1341
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    • 2009
  • In this paper, an EMI reduction effects using an EMC chamber is described and reduction methods is proposed. In the case of general electronic components a working frequency is low. But in this paper the vehicle cluster works 75MHz in the main clock frequency, becoming weak by noise because of being attached in TFT LCD. As the outer case installed in the vehicle is made up of plastic materials, the noise is radiated if not protecting noise in the PCB itself. Therefore, This paper will explain the theoretical basis and propriety with respect to the discussion and need about the guide for PCB design considering EMC, through the reduction of PCB noise.

A Method Finding Representative Questionare for Mutual Information and Entropy (상호정보와 엔트로피를 활용한 대표문항 선택방법)

  • Choi, Byong-Su;Kim, Hyun-Ji
    • Communications for Statistical Applications and Methods
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    • v.17 no.4
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    • pp.591-598
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    • 2010
  • A questionnaire may consist of duplicated or similar items. This study finds the duplicated or similar items by using the MDS and the cluster analysis of response patterns. By identifying the characteristics of the cluster, those items are combined into a representative item. The similarity of items is measured by the mutual information.

Support Vector Machine based Cluster Merging (Support Vector Machines 기반의 클러스터 결합 기법)

  • Choi, Byung-In;Rhee, Frank Chung-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.3
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    • pp.369-374
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    • 2004
  • A cluster merging algorithm that merges convex clusters resulted by the Fuzzy Convex Clustering(FCC) method into non-convex clusters was proposed. This was achieved by proposing a fast and reliable distance measure between two convex clusters using Support Vector Machines(SVM) to improve accuracy and speed over other existing conventional methods. In doing so, it was possible to reduce cluster number without losing its representation of the data. In this paper, results for several data sets are given to show the validity of our distance measure and algorithm.

Improvement of CH selection of WSN Protocol

  • Lee, WooSuk;Jung, Kye-Dong;Lee, Jong-Yong
    • International journal of advanced smart convergence
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    • v.6 no.3
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    • pp.53-58
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    • 2017
  • A WSN (Wireless Sensor Network) is a network that is composed of wireless sensor nodes. There is no restriction on the place where it can be installed because it is composed wirelessly. Instead, sensor nodes have limited energy. Therefore, to use the network for a long time, energy consumption should be minimized. Several protocols have been proposed to minimize energy consumption, and the typical protocol is the LEACH protocol. The LEACH protocol is a cluster-based protocol that minimizes energy consumption by dividing the sensor field into clusters. Depending on how you organize the clusters of sensor field, network lifetimes may increase or decrease. In this paper, we will improve the network lifetime by improving the cluster head selection method in LEACH Protocol.