• Title/Summary/Keyword: Cluster Tree

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Scene Change Detection Using Local Information (지역적 정보를 이용한 장면 전환 검출)

  • Shin, Seong-Yoon;Shin, Kwang-Sung;Lee, Hyun-Chang;Jin, Chan-Yong;Rhee, Yang-Won
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.151-152
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    • 2012
  • This paper proposes a Scene Change Detection method using the local decision tree and clustering. The local decision tree detects cluster boundaries wherein local scenes occur, in such a way as to compare time similarity distributions among the difference values between detected scenes and their adjacent frames, and group an unbroken sequence of frames with similarities in difference value into a cluster unit.

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Scene Change Detection Using Local Information (지역적 정보를 이용한 장면 전환 검출)

  • Shin, Seong-Yoon;Jin, Chan-Yong;Rhee, Yang-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.6
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    • pp.1199-1203
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    • 2012
  • This paper proposes a Scene Change Detection method using the local decision tree and clustering. The local decision tree detects cluster boundaries wherein local scenes occur, in such a way as to compare time similarity distributions among the difference values between detected scenes and their adjacent frames, and group an unbroken sequence of frames with similarities in difference value into a cluster unit.

A Cluster Based Energy Efficient Tree Routing Protocol in Wireless Sensor Networks (광역 WSN 을 위한 클러스팅 트리 라우팅 프로토콜)

  • Nurhayati, Nurhayati;Choi, Sung-Hee;Lee, Kyung-Oh
    • Proceedings of the Korea Information Processing Society Conference
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    • 2011.04a
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    • pp.576-579
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    • 2011
  • Wireless sensor network are widely all over different fields. Because of its distinguished characteristics, we must take account of the factor of energy consumed when designing routing protocol. Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. In BCDCP, all sensors sends data from the CH (Cluster Head) and then to the BS (Base Station). BCDCP works well in a smallscale network however is not preferred in a large scale network since it uses much energy for long distance wireless communication. TBRP can be used for large scale network, but it weakness lies on the fact that the nodedry out of energy easily since it uses multi-hops transmission data to the Base Station. Here, we proposed a routing protocol. A Cluster Based Energy Efficient Tree Routing Protocol (CETRP) in Wireless Sensor Networks (WSNs) to prolong network life time through the balanced energy consumption. CETRP selects Cluster Head of cluster tree shape and uses maximum two hops data transmission to the Cluster Head in every level. We show CETRP outperforms BCDCP and TBRP with several experiments.

Incremental EM algorithm with multiresolution kd-trees and cluster validation and its application to image segmentation (다중해상도 kd-트리와 클러스터 유효성을 이용한 점증적 EM 알고리즘과 이의 영상 분할에의 적용)

  • Lee, Kyoung-Mi
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.6
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    • pp.523-528
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    • 2015
  • In this paper, we propose a new multiresolutional and dynamic approach of the EM algorithm. EM is a very popular and powerful clustering algorithm. EM, however, has problems that indexes multiresolution data and requires a priori information on a proper number of clusters in many applications, To solve such problems, the proposed EM algorithm can impose a multiresolution kd-tree structure in the E-step and allocates a cluster based on sequential data. To validate clusters, we use a merge criteria for cluster merging. We demonstrate the proposed EM algorithm outperforms for texture image segmentation.

Assessing the Performance of Pongamia pinnata (l.) Pierre under Ex-situ Condition in Karnataka

  • Divakara, Baragur Neelappa;Nikhitha, Chitradurga Umesh
    • Journal of Forest and Environmental Science
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    • v.38 no.1
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    • pp.12-20
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    • 2022
  • Pongamia (Pongamia pinnata L.) as a source of non-edible oil, is potential tree species for biodiesel production. For several reasons, both technical and economical, the potential of P. pinnata is far from being realized. The exploitation of genetic diversity for crop improvement has been the major driving force for the exploration and ex situ/in situ conservation of plant genetic resources. However, P. pinnata improvement for high oil and seed production is not achieved because of unsystematic way of tree improvement. Performance of P. pinnata planted by Karnataka Forest Department was assessed based on yield potential by collecting 157 clones out of 264 clones established by Karnataka Forest Department research wing under different research circles/ranges. It was evident that the all the seed and pod traits were significantly different. Further, selection of superior germplasm based on oil and pod/seed parameters was achieved by application of Mahalanobis statistics and Tocher's technique. On the basis of D2 values for all possible 253 pairs of populations the 157 genotypes were grouped into 28 clusters. The clustering pattern showed that geographical diversity is not necessarily related to genetic diversity. Cluster means indicated a wide range of variation for all the pod and seed traits. The best cluster having total oil content of more than 34.9% with 100 seed weight of above 125 g viz. Cluster I, II, III, IX, XV, XIX, XXI, XXIII, XXVI and XXVII were selected for clonal propagation.

Forest Structure in Relation to Slope Aspect and Altitude in Valley forests at Baraebong, Jirisan National Park' (지리산국립공원 바래봉지역 계곡부의 사면방향과 해발고에 따른 산림구조)

  • 박인협;서영권;최영철
    • Korean Journal of Environment and Ecology
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    • v.16 no.4
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    • pp.449-456
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    • 2003
  • The valley forests at Baraebong area, Jirisan National Park were studied to investigate forest structure of tree, subtree and shrub layers in relation to aspect and altitude of the slope. Density and basal area of the tree layer in the north-facing slope were greater than those in the south-facing slope. As elevation increased, basal area of the tree layer decreased in north-facing slope. The impotance percentage of Quercus mongolica increased with increasing elevation while those of Quercus serrata and Pinus densiflora decreased. Species diversity of the north-facing slope was 1.307 and that of the south-facing slope was 1.114. There was a tendency that number of species, species diversity and evenness decreased with increasing elevation. The result of cluster analysis for the tree and subtree layer indicated that the studied forests were classified into Quercus senrraa-broad-leaved tree species community at the low and middle elevation belts of the south-facing slope, Quercus mongolika-broad-leaved tree species community at the high elevation belt of the south-facing slope, the middle and high elevation belts of the north-facing slope and top area, and Pinus densiflora-Quercus mangolica community at the low elevation belt of the north-facing slope. There were significantly positive correlations in the importance percentages among Carpinus laxiflora, Quercus serrata, Styrax obassica and Linden obtuiloba, and among Castanea crenata, Rhodndendron schippen-bachii and Vibntnum erosum.

Detecting outliers in multivariate data and visualization-R scripts (다변량 자료에서 특이점 검출 및 시각화 - R 스크립트)

  • Kim, Sung-Soo
    • The Korean Journal of Applied Statistics
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    • v.31 no.4
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    • pp.517-528
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    • 2018
  • We provide R scripts to detect outliers in multivariate data and visualization. Detecting outliers is provided using three approaches 1) Robust Mahalanobis distance, 2) High Dimensional data, 3) density-based approach methods. We use the following techniques to visualize detected potential outliers 1) multidimensional scaling (MDS) and minimal spanning tree (MST) with k-means clustering, 2) MDS with fviz cluster, 3) principal component analysis (PCA) with fviz cluster. For real data sets, we use MLB pitching data including Ryu, Hyun-jin in 2013 and 2014. The developed R scripts can be downloaded at "http://www.knou.ac.kr/~sskim/ddpoutlier.html" (R scripts and also R package can be downloaded here).

Communication Protocol to Support Mobile Sinks by Multi-hop Clusters in Wireless Sensor Networks (무선 센서 네트워크에서 멀티-홉 클러스터를 통한 이동 싱크 지원 통신 프로토콜)

  • Oh, Seung-Min;Jung, Ju-Hyun;Lee, Jeong-Cheol;Park, Ho-Sung;Yim, Yong-Bin;Kim, Sang-Ha
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.3A
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    • pp.287-295
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    • 2010
  • In wireless sensor networks(WSNs), the studies that support sink mobility without global position information exploit a Backbone-based Virtual Infrastructure (BVI) which considers one-hop clusters and a backbone-based tree. Since the clusters of a sink and a source node are connected via flooding into the infrastructure, it causes high routing cost. Although the network could reduce the number of clusters via multi-level clusters, if the source nodes exist at nearest clusters from the cluster attached by the sink and they are in different branches of the tree, the data should be delivered via detour paths on the tree. Therefore, to reduce the number of clusters, we propose a novel multi-hop cluster based communication protocol supporting sink mobility without global position information. We exploit a rendezvous cluster head for sink location service and data dissemination but the proposed protocol effectively reduces data detour via comparing cluster hops from the source. Simulation shows that the proposed protocol is superior to the existing protocols in terms of the data delivery hop counts.

Clustering based on Dependence Tree in Massive Data Streams

  • Yun, Hong-Won
    • Journal of information and communication convergence engineering
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    • v.6 no.2
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    • pp.182-186
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    • 2008
  • RFID systems generate huge amount of data quickly. The data are associated with the locations and the timestamps and the containment relationships. It is requires to assure efficient queries and updates for product tracking and monitoring. We propose a clustering technique for fast query processing. Our study presents the state charts of temporal event flow and proposes the dependence trees with data association and uses them to cluster the linked events. Our experimental evaluation show the power of proposing clustering technique based on dependence tree.

A design of binary decision tree using genetic algorithms and its application to the alphabetic charcter (유전 알고리즘을 이용한 이진 결정 트리의 설계와 영문자 인식에의 응용)

  • 정순원;김경민;박귀태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1995.10b
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    • pp.218-223
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    • 1995
  • A new design scheme of a binary decision tree is proposed. In this scheme a binary decision tree is constructed by using genetic algorithm and FCM algorithm. At each node optimal or near-optimal feature or feature subset among all the available features is selected based on fitness function in genetic algorithm which is inversely proportional to classification error, balance between cluster, number of feature used. The proposed design scheme is applied to the handwtitten alphabetic characters. Experimental results show the usefulness of the proposed scheme.

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