• Title/Summary/Keyword: cluster method

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Unconstrained Numeral Recognition Using Dithering and Multiple Modular MLPs (디더링과 모듈 구조의 다중 MLP를 이용한 무제약 필기체 숫자 인식)

  • 임길택;남윤석;진성일
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.456-459
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    • 1999
  • In this paper, we propose a method of unconstrained handwritten numeral recognition using image dithering and multiple modular MLPs. The set of sample numeral patterns is subdivided into clusters which are extended by their radius. On each extended cluster, we constructed MLPs network as the expert recognizer of corresponding cluster. The gating network is also trained by an MLPs to weigh the outputs of expert MLPs. In training and test phase of the recognizer, we utilize the multiple dithered numeral images and the combination of the outputs for corresponding dithered images. Experimental results show that our recognition method works very well.

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A Matching Strategy to Recognize Occluded Number (폐색된 숫자를 인식하는 매칭 방법)

  • Pham, Thi Thuong;Choi, Hyung-Il;Kim, Gye-Young
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2011.01a
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    • pp.55-58
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    • 2011
  • This paper proposes a method of occluded number recognition by matching interest points. Interest points of input pattern are found via SURF features extracting and matched to interest points of clusters in database following three steps: SURF matching, coordinate matching and SURF matching on coordinate matched points. Then the satisfied interest points are counted to compute matching rate of each cluster. The input pattern will be assigned to cluster having highest matching rate. We have experimented our method to different numerical fonts and got encouraging results.

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Evaluation of Genetic Diversity among Korean Wild Codonopsis lanceolata by Using RAPD

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    • Korean Journal of Plant Resources
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    • v.10 no.3
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    • pp.258-264
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    • 1997
  • The introduction of molecular biology methodologies to plant improvement programs offers an invaluable opportunity for extensive germplasm characterization. We have applied the developed technique of random amplification of polymorphic DNA(RAPD)to the analysis of evaluating genetic diversity among Korean wild Codonopsis lanceolata. A total of 340 polymorpic hands were gernerated on agarose- and polyacrylamide-gel by 19 primers of abitrary sequence. grouped by cluster analysis using sample matching coefficients of similarity. Among of the samples. the minimum genetic distance value was obtained between sample no. 1(Girisan) and no. 2(Girisan), and the largest value between sample no. 11(Sulaksan) and no. 17(Sulaksan).In separate cluster dendrograms based on agareose - and polyacryamide-gel. some differences were observed; In the case of agarose gel,41 samples could be devided into 7 groups at below about 0.44 level of distance. However they were divided into 6 gourps at below about 0.40 level of distance in the case of polyacrylamide gel. These results showed that polymophic data in agrose were not grouped to wild plant selected from each mountainous district except for wild plants selected from Sulaksan and Chiaksan. We believe that polyacrylamide-RAPD is a superior method for detecting DNA polymorphism compared to agarose-RAPD method.

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Performance Evaluation of Spatial Clustering Method using Regular Grid (균등 격자를 이용한 공간 클러스터링 기법의 성능 평가)

  • 문상호
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.468-471
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    • 2003
  • In this paper, experimental tests are performed to evaluate the efficiency of spatial clustering method using regular grid that is proposed in our recent research. In details, we estimate the execution time for finding clusters varying spatial objects on sample data sets with various distributions and perform experimental tests varying threshold value on a data set. We also compare the running time of cluster generating algorithm with that of cluster merging algorithm per each test.

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Similarity measure for P2P processing of semantic data (시맨틱웹 데이터의 P2P 처리를 위한 유사도 측정)

  • Kim, Byung Gon;Kim, Youn Hee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.4
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    • pp.11-20
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    • 2010
  • Ontology is important role in semantic web to construct and query semantic data. Because of dynamic characteristic of ontology, P2P environment is considered for ontology processing in web environment. For efficient processing of ontology in P2P environment, clustering of peers should be considered. When new peer is added to the network, cluster allocation problem of the new peer is important for system efficiency. For clustering of peers with similar chateristics, similarlity measure method of ontology in added peer with ontologies in other clusters is needed. In this paper, we propose similarity measure techniques of ontologies for clustering of peers. Similarity measure method in this paper considered ontology's strucural characteristics like schema, class, property. Results of experiments show that ontologies of similar topics, class, property can be allocated to the same cluster.

Refining Initial Seeds using Max Average Distance for K-Means Clustering (K-Means 클러스터링 성능 향상을 위한 최대평균거리 기반 초기값 설정)

  • Lee, Shin-Won;Lee, Won-Hee
    • Journal of Internet Computing and Services
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    • v.12 no.2
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    • pp.103-111
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    • 2011
  • Clustering methods is divided into hierarchical clustering, partitioning clustering, and more. If the amount of documents is huge, it takes too much time to cluster them in hierarchical clustering. In this paper we deal with K-Means algorithm that is one of partitioning clustering and is adequate to cluster so many documents rapidly and easily. We propose the new method of selecting initial seeds in K-Means algorithm. In this method, the initial seeds have been selected that are positioned as far away from each other as possible.

Bit Error Reduction for Holographic Data Storage System Using Subclustering (서브클러스터링을 이용한 홀로그래픽 정보저장 시스템의 비트 에러 보정 기법)

  • Kim, Sang-Hoon;Yang, Hyun-Seok;Park, Young-Pil
    • Transactions of the Society of Information Storage Systems
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    • v.6 no.1
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    • pp.31-36
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    • 2010
  • Data storage related with writing and retrieving requires high storage capacity, fast transfer rate and less access time. Today any data storage system cannot satisfy these conditions, however holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System can be constructed without mechanical actuating part so fast data transfer rate and high storage capacity about 1Tb/cm3 can be realized. In this research, to correct errors of binary data stored in holographic data storage system, a new method for reduction errors is suggested. First, find cluster centers using subtractive clustering algorithm then reduce intensities of pixels around cluster centers. By using this error reduction method following results are obtained ; the effect of Inter Pixel Interference noise in the holographic data storage system is decreased and the intensity profile of data page becomes uniform therefore the better data storage system can be constructed.

A Type 2 Fuzzy C-means (제2종 퍼지 집합을 이용한 퍼지 C-means)

  • Hwang, Cheul;Rhee, Fransk Chung-Hoon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.16-19
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    • 2001
  • This paper presents a type-2 fuzzy C-means (FCM) algorithm that is an extension of the conventional fuzzy C-means algorithm. In our proposed method, the membership values for each pattern are extended as type-2 fuzzy memberships by assigning membership grades to the type-1 memberships. In doing so, cluster centers that are estimated by type-2 memberships may converge to a more desirable location than cluster centers obtained by a type-1 FCM method in the presence of noise.

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XML Document Clustering Technique by K-means algorithm through PCA (주성분 분석의 K 평균 알고리즘을 통한 XML 문서 군집화 기법)

  • Kim, Woo-Saeng
    • The KIPS Transactions:PartD
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    • v.18D no.5
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    • pp.339-342
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    • 2011
  • Recently, researches are studied in developing efficient techniques for accessing, querying, and storing XML documents which are frequently used in the Internet. In this paper, we propose a new method to cluster XML documents efficiently. We use a K-means algorithm with a Principal Component Analysis(PCA) to cluster XML documents after they are represented by vectors in the feature vector space by transferring them as names and levels of the elements of the corresponding trees. The experiment shows that our proposed method has a good result.

Simulation for the Efficient Utilization of Energy in Wireless Sensor Network (무선 센서네트워크에서의 효과적인 에너지 활용 시뮬레이션)

  • Baeg, Seung-Beom;Cho, Tae-Ho
    • Journal of the Korea Society for Simulation
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    • v.14 no.3
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    • pp.33-42
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    • 2005
  • One of the imminent problems to be solved within wireless sensor network is to balance out energy dissipation among deployed sensor nodes. In this paper, we present a transmission relay method of communications between BS (Base Station) and CHs (Cluster Heads) for balancing the energy consumption and extending the average lifetime of sensor nodes by the fuzzy logic application. The proposed method is designed based on LEACH protocol. The area deployed by sensor nodes is divided into two groups based on distance from BS to the nodes. RCH (Relay Cluster Head) relays transmissions from CH to BS if the CH is in the area far away from BS in order to reduce the energy consumption. RCH decides whether to relay the transmissions based on the threshold distance value that is obtained as a output of fuzzy logic system, Our simulation result shows that the application of fuzzy logic provides the better balancing of energy depletion and prolonged lifetime of the nodes.

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