• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.15-21
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• 2009

The goal of wireless sensor networks is to collect sensing data on specific region over wireless communication. Sink node gathers all local sensing data, processes and transmits them to users who use sensor networks. Generally, senor nodes are low-cost, low power devices with limited sensing, computation and wireless communication capabilities. And sensor network applies to multi-hop communication on large-scale network. As neighboring sensor nodes have similar data, clustering is more effective technique for 'data-aggregation'. In cluster formation technique based on multi-hop, it is necessary that the number of cluster member nodes should be distributed equally because of the balance of cluster formation To achieve this, we propose a method to customize cluster member nodes for energy-efficiency in wireless sensor networks.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.109-116
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• 2008

Even though many studies on parallel rendering based on PC clusters have been done. most of those did not cope with non-uniform scenes, where locations of 3D models are biased. In this work. we have built a PC cluster system with POV-Ray, a free rendering software on the public domain, and developed an adaptive load balancing scheme to optimize the parallel efficiency Especially, we noticed that a frame of 3D animation are closely coherent with adjacent frames. and thus we could estimate distribution of computation amount, based on the computation time of previous frame. The experimental results with 2 real animation data show that the proposed scheme reduces by 40% of execution time compared to the simple static partitioning scheme.

• The Journal of the Acoustical Society of Korea
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• v.34 no.4
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• pp.303-309
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• 2015

Speaker diarization is the task of determining the speakers for unlabeled data, and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) has been widely used in the field of speaker diarization for its simplicity and computational efficiency. One challenging issue, however, is that if different clusters in non-spatial dataset are adjacent to each other, over-clustering may occur which subsequently degrades the performance of DBSCAN. In this paper, we identify the drawbacks of DBSCAN and propose a new density clustering algorithm based on local distribution property around object. Variable density criterions for local density and spreadness of object are used for effective data clustering. We compare the proposed algorithm to DBSCAN in terms of clustering accuracy. Experimental results confirm that the proposed algorithm exhibits higher accuracy than DBSCAN without over-clustering and confirm that the new approach based on local density and object spreadness is efficient.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.239-248
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• 2010

Leukocyte in blood smear image provides significant information to doctors for diagnosis of patient health status. Therefore, it is necessary step to separate leukocyte from blood smear image among various blood cells for early disease prediction. In this paper, we present a saliency map and stepwise region merging based leukocyte segmentation method. Since leukocyte region has salient color and texture, we create a saliency map using these feature map. Saliency map is used for sub-image separation. Then, clustering is performed on each sub-image using mean-shift. After mean-shift is applied, stepwise region-merging is applied to particle clusters to obtain final leukocyte nucleus. The experimental results show that our system can indeed improve segmentation performance compared to previous researches with average accuracy rate of 71%.

• Journal of the Korea Society of Computer and Information
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• v.9 no.3
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• pp.189-194
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• 2004

This paper proposes a Simulated Annealing(SA) algorithm for cluster-based Multicast Routing problems. Multicasting, the transmission of data to a group, can be solved from constructing multicast tree, that is. the whole network is partitioned to some clusters and the clusters are constructed by multicast tree. Multicast tree can be constructed by minimum-cost Steiner tree. In this paper, an SA algorithm is used in the minimum-cost Steiner tree. Especially, in SA, the cooling schedule is an important factor for the algorithm. Hence, in this paper, a cooling schedule is proposed for SA for multicast routing problems and analyzed the simulation results.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.11-14
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• 2001

본 논문은 컬러를 이용한 영상 검색 방법에 관한 것으로 영상 데이터의 효율적인 관리를 위해 먼저 전처리 단계로 웨이블릿 변환을 수행한 후 가장 낮은 저주파 부밴드 영상을 획득한다. 그리고, 변환 후 획득된 영상을 클러스터로 구분한 후, 고유치 및 고유 벡터를 이용하여 특징을 추출하여 색인 정보로 이용하였다. 클러스터링은 영상 화소의 컬러공간 상의 3차원 거리를 클러스터링의 기준으로 삼아 순차 영역 분할(Sequential Clustering) 방법을 적용하였다.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.67-73
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• 2005

최근 이동체의 위치 데이타를 활용하는 위치 기반 서비스에 대한 관심이 급증하고 있다. 이러한 위치 기반 서비스에서 이용되는 대용량 위치 데이타를 효율적으로 관리하기 위한 아키텍처로서 클러스터 기반 분산 컴퓨팅 구조를 갖는 GALIS(Gracefully Aging Location Information System) 아키텍처가 제안되었다. GALIS는 비균등 2-단계 그리드를 사용하여 노드들의 부하 분산 및 색인을 수행한다. 하지만 비균등 2-단계 그리드의 분할 알고리즘은 이동체가 특정 지역에 편중되는 경우 불필요한 노드를 생성하는 문제를 가지고 있다. 따라서 본 논문에서는 이동체의 다양한 분포에 대하여 더욱 효율적인 노드 분할 알고리즘을 제시한다. 본 논문에서 제시한 노드 분할 알고리즘은 이동체의 현재 위치에 따른 공간적 분포를 고려하기 때문에 이동체가 특정 지역에 편중되는 경우에도 불필요한 노드를 생성하지 않고 효율적인 부하 분산을 수행할 수 있으며, 분산 시스템에서 중요시되는 균형 있는 부하 분산을 수행할 수 있다. 또한, 가상 노드 분할 시뮬레이터를 구현하여 다양한 이동체 데이타 분포 형태에 대해 실험하였으며, 이러한 실험을 통하여 기존의 알고리즘보다 더욱 효율적으로 노드를 분할하는 것을 검증하였다.

• Journal of IKEEE
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• v.24 no.1
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• pp.127-131
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• 2020

Fuzzy C-Means(FCM) algorithm is frequently used as a representative image segmentation method using clustering. FCM divides the image space into cluster regions with similar pixel values, which requires a lot of segmentation time. In particular, the processing speed problem for analyzing various patterns of the current users of the web is more important. To solve this speed problem, this paper proposes an improved FCM (Improved FCM : IFCM) algorithm for segmenting the image into the Otsu threshold and FCM. In the proposed method, the threshold that maximizes the variance between classes of Otsu is determined, applied to the FCM, and the image is segmented. Experiments show that IFCM improves performance by shortening image segmentation time compared to conventional FCM.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.16-27
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• 2011

Embryo is a very early stage of the development of multicellular organism such as animals and plants. It is an important research target for studying ontogeny because the fundamental body system of multicellular organism is determined during an embryo state. Researchers in the developmental biology have a large volume of embryo image databases for studying embryos and they frequently search for an embryo image efficiently from those databases. Thus, it is crucial to organize databases for their efficient search. Hierarchical clustering methods have been widely used for database organization. However, most of previous algorithms tend to produce a highly skewed tree as a result of clustering because they do not simultaneously consider both the size of a cluster and the number of objects within the cluster. The skewed tree requires much time to be traversed in users' search process. In this paper, we propose a method that effectively organizes a large volume of embryo image data in a balanced tree structure. We first represent embryo image data as a similarity-based graph. Next, we identify clusters by performing a graph partitioning algorithm repeatedly. We check constantly the size of a cluster and the number of objects, and partition clusters whose size is too large or whose number of objects is too high, which prevents clusters from growing too large or having too many objects. We show the superiority of the proposed method by extensive experiments. Moreover, we implement the visualization tool to help users quickly and easily navigate the embryo image database.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.10
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• pp.1-9
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• 2003

In GRID environments, an efficient load balancing algorithm should be adopted since the system performances of GRID system are not homogeneous. In this work, a new two-step mesh-partitioning scheme based on the graph-partitioning scheme was introduced to consider the difference of system performance. In the two-step mesh-partitioning scheme, the system performance weights were calculated to reflect the effect of heterogeneous system performances and WEVM(Weighted Edge and vertex Method) was adopted to minimize the increase' of communications. Numerical experiments were carried out in multi-cluster environment and WAN (Wide Area Network) environment to investigate the effectiveness of the two-step mesh-partitioning scheme.