• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.92-94
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• 2000

비디오 저장 서버를 설계하는데 가장 주안을 두어야 할 점은 서버의 이용률을 증가시키고 그에 따른 비용을 최소화 해야 한다는 점이다. 이를 위한 서버로 분산 비디오 저장 서버가 주로 이용되고 있고, 그 목적으로는 균등한 비디오 할당과 부하조정(load balancing)이 제안되어 왔다. 이에 대한 방안의 하나로 디스크 기반의 비디오 저장 서버 클러스터에서 부하 시프팅(load shifting)이 그 목적을 이루기 위한 한가지 방법으로 연구되었다. 이것은 동일한 용량의 서버로 구성된 비디오 서버 클러스터에서 비디오를 다른 서버에 복사해 놓고 사용되고 있는 비디오 요구시 그 비디오에 대한 요구를 다른 서버의 복사본으로 이동시킴으로써 서버들에 대해 균등한 비디오 할당을 하고 서버나 비디오의 추가와 같은 동적인 변화에 대해 데이터 활당 및 부하 조정을 감안하여 제안된 것이다. 이 논문에서는 기존의 동일한 서버만을 사용한 것과는 달리 용량이 서로 다른 서버나 비디오를 추가할 경우에 요구되는 최적의 비디오 데이터 할당과 부하 조정에 관한 전략에 관하여 설명한다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.49-56
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• 2010

In this paper, we implement a Hadoop based cluster for cloud computing and evaluate the performance of this cluster based on application characteristics by executing RandomTextWriter, WordCount, and PI applications. A RandomTextWriter creates given amount of random words and stores them in the HDFS(Hadoop Distributed File System). A WordCount reads an input file and determines the frequency of a given word per block unit. PI application induces PI value using the Monte Carlo law. During simulation, we investigate the effect of data block size and the number of replications on the execution time of applications. Through simulation, we have confirmed that the execution time of RandomTextWriter was proportional to the number of replications. However, the execution time of WordCount and PI were not affected by the number of replications. Moreover, the execution time of WordCount was optimum when the block size was 64~256MB. Therefore, these results show that the performance of cloud computing system can be enhanced by using a scheduling scheme that considers application's characteristics.

• The KIPS Transactions:PartC
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• v.13C no.4 s.107
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• pp.481-490
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• 2006

In a super-peer based P2P network, The network is clustered and each cluster is managed by a special peer, called a super-peer which has information of all peers in its cluster. This clustered P2P model is known to have efficient information search and less traffic load. In this paper, we first estimate the message traffic cost caused by peer's query, join and update actions within a cluster as well as between the clusters and with these values, we present the optimal number of super-peers that minimizes the traffic cost for the various size of super-peer based P2P networks.rks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.12-19
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• 2020

The clustered heterogeneous wireless sensor network is comprised of sensor nodes and cluster heads, which are hierarchically organized for different objectives. In the network, we should especially take care of managing node resources to enhance network performance based on memory and battery capacity constraints. For instances, if some interesting events occur frequently in the vicinity of particular sensor nodes, those nodes might receive massive amounts of data. Data congestion can happen due to a memory bottleneck or link disconnection at cluster heads because the remaining memory space is filled with those data. In this paper, we utilize drones as mobile sinks to resolve data congestion and model the network, sensor nodes, and cluster heads. We also design a cost function and a congestion indicator to calculate the degree of congestion. Then we propose a data congestion map index and a data congestion mapping scheme to deploy drones at optimal points. Using control variable, we explore the relationship between the degree of congestion and the number of drones to be deployed, as well as the number of drones that must be below a certain degree of congestion and within communication range. Furthermore, we show that our algorithm outperforms previous work by a minimum of 20% in terms of memory overflow.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.437-442
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• 2005

For the purpose of speaker normalization in speaker independent speech recognition systems, experiments are conducted on a method based on Gaussian mixture model(GMM). The method, which is an improvement of the previous study based on vector quantizer, consists of modeling the probability distribution of canonical feature vectors by a GMM with an appropriate number of clusters, and of estimating the warp factor of a test speaker by making use of the obtained probabilistic model. The purpose of this study is twofold: improving the existing ML based methods, and comparing the performance of what is called 'soft decision' method with that of the previous study based on vector quantizer. The effectiveness of the proposed method is investigated by recognition experiments on the TIMIT corpus. The experimental results showed that a little improvement could be obtained tv adjusting the number of clusters in GMM appropriately.

• Journal of Biomedical Engineering Research
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• v.21 no.4
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• pp.333-338
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• 2000

In this paper, an automated segmentation algorithm is proposed for MR brain images using T1-weighted, T2-weighted, and PD images complementarily. The proposed segmentation algorithm is composed of 3 step. In the first step, cerebrum images are extracted by putting a cerebrum mask upon the three input images. In the second step, outstanding clusters that represent inner tissues of the cerebrum are chosen among 3-dimensional(3D) clusters. 3D clusters are determined by intersecting densely distributed parts of 2D histogram in the 3D space formed with three optimal scale images. Optimal scale image is made up of applying scale space filtering to each 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram and searching graph structure. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram. In the final step, cerebrum images are segmented using FCM algorithm with its initial centroid value as the outstanding clusters centroid value. The proposed cluster's centroid accurately. And also can get better segmentation results from the proposed segmentation algorithm with multi spectral analysis than the method of single spectral analysis.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.366-368
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• 2009

본 논문에서는 모바일 로봇이 작업하는 공간상에서 빠르고 안전한 최적 경로계획을 수행할 수 있게 하는 가변적 리드 맵을 이용한 장애물 밀집 정보 기반 경로계획을 제안한다. 모바일 로봇이 작업 공간에 대해서 빠르고 안전한 경로계획을 해 클러스터링 기법을 이용하여 정적 및 동적 장애물의 분포에 대한 맵 정보를 재구성하여 정보화 시킨다. 최적의 경로계획을 위해서는 재구성된 장애물 밀집 클러스터 데이터를 이용하여 전통적 기법의 GA 방법을 변형한 최적 경로계획을 수행한다. 제안한 기술의 효율성을 검증하기 위해 그리드 기반 경로계획 중의 하나인 A*알고리즘과 다양한 맵을 이용하여 성능 비교를 수행하였다. 실험결과 제안한 경로계획 기술은 기존 알고리즘 보다 빠른 처리 성능과 동적 장애물이 밀집한 지역을 회피하는 최적 경로계획을 수행함을 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.677-680
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• 2015

In this paper, we propsed scheme to mitigate conflict and loss of message in vehicle communication. And vehicles that exist in the moving direction, were grouping to the cluster form. Through, to select best relay vehicle, transmit a message to the destination. In addition, we applied the double rayleigh fading environment so that can applied in real-environments. Therefore, vehicle communication network applied proposed scheme, can be problem of mitigate conflict and loss of message. Thus, Increase the reliability of the received signal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.649-651
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• 2017

A clustering problem is one of the organizational problems to improve the network lifetime and scalability in wireless ad-hoc networks. This problem is a difficult combinatorial optimization problem associated with the design and operation of these networks. In this paper, we propose an efficient clustering algorithm to maximize the network lifetime and consider scalability in wireless ad-hoc networks. The clustering problem is known to be NP-hard. We thus solve the problem by using optimization approaches that are able to efficiently obtain high quality solutions within a reasonable time for a large size network. The proposed algorithm selects clusterheads and configures clusters by considering both nodes' power and the clustering cost. We evaluate this performance through some experiments in terms of nodes' transmission energy. Simulation results indicate that the proposed algorithm performs much better than the existing algorithms.