• Journal of Korea Multimedia Society
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• v.7 no.2
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• pp.264-271
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• 2004

A load-sharing algorithm must deal with load imbalance caused by characteristics of a network and heterogeneity of nodes in Internet-based clustering systems. This paper has proposed the Efficient Load-Sharing algorithm. Efficient-Load-Sharing algorithm creates a scheduler based on the WF(Weighted Factoring) algorithm and then allocates tasks by an adaptive granularity strategy and the refined fixed granularity algorithm for better performance. In this paper, adaptive granularity strategy is that master node allocates tasks of relatively slower node to faster node and refined fixed granularity algorithm is to overlap between the time spent by slave nodes on computation and the time spent for network communication. For the simulation, the matrix multiplication using PVM is performed on the heterogeneous clustering environment which consists of two different networks. Compared to other algorithms such as Send, GSS and Weighted Factoring, the proposed algorithm results in an improvement of performance by 75%, 79% and 17%, respectively.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.429-436
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• 2004

This paper proposes an independent component analyses(ICAs) of the fixed-point (FP) algorithm based on Newton and secant method by adding the kurtosis, respectively. The kurtosis is applied to cluster the analyzed components, and the FP algorithm is applied to get the fast analysis and superior performance irrelevant to learning parameters. The proposed ICAs have been applied to the problems for separating the 6-mixed signals of 500 samples and 10-mixed images of $512\times512$ pixels, respectively. The experimental results show that the proposed ICAs have always a fixed analysis sequence. The results can be solved the limit of conventional ICA without a kurtosis which has a variable sequence depending on the running of algorithm. Especially. the proposed ICA can be used for classifying and identifying the signals or the images. The results also show that the secant method has better the separation speed and performance than Newton method. And, the secant method gives relatively larger improvement degree as the problem size increases.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.47-57
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• 2010

The object detection is essential for identifying objects, location information, and user context-aware in the image. In this paper, we propose a robust object detection system. The System linearly transforms learning data obtained from the background images to Principal components. It organizes the Eigen-background with the selected Principal components which are able to discriminate between foreground and background. The Fuzzy-C-means (FCM) carries out clustering for images with inputs from the Eigen-background information and classifies them into objects and backgrounds. It used various patterns of backgrounds as learning data in order to implement a system applicable even to the changing environments, Our system was able to effectively detect partial movements of a human body, as well as to discriminate between objects and backgrounds removing noises and shadows without anyone frame image for fixed background.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.184-192
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• 2011

In this study, we introduce a identification methodology for FCM-based fuzzy model. The two underlying design mechanisms of such networks involve Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on FCM clustering method for efficient processing of data and the optimization of model was carried out using PSO. The premise part of fuzzy rules does not construct as any fixed membership functions such as triangular, gaussian, ellipsoidal because we build up the premise part of fuzzy rules using FCM. As a result, the proposed model can lead to the compact architecture of network. In this study, as the consequence part of fuzzy rules, we are able to use four types of polynomials such as simplified, linear, quadratic, modified quadratic. In addition, a Weighted Least Square Estimation to estimate the coefficients of polynomials, which are the consequent parts of fuzzy model, can decouple each fuzzy rule from the other fuzzy rules. Therefore, a local learning capability and an interpretability of the proposed fuzzy model are improved. Also, the parameters of the proposed fuzzy model such as a fuzzification coefficient of FCM clustering, the number of clusters of FCM clustering, and the polynomial type of the consequent part of fuzzy rules are adjusted using PSO. The proposed model is illustrated with the use of Automobile Miles per Gallon(MPG) and Boston housing called Machine Learning dataset. A comparative analysis reveals that the proposed FCM-based fuzzy model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.33-42
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• 2007

Mobile ad-hoc network(MANET) can increase independence and flexibility of network because it consists of mobile node without the aid of fixed infrastructure. But, Because of unrestriction for the participation and breakaway of node, it has the difficulty in management and stability which is a basic function of network operation. Therefore, to solve those problems, we suggest a distributed weighted clustering algorithm from a manageable and stable point of view. The suggested algorithm uses distributed weighted clustering algorithm when it initially forms the cluster and uses a concept which is distributed gateway and sub-cluster head to reduce the re-clustering to the minimum which occurs mobile nodes after forming the cluster. For performance evaluation, We compare DCA and WCA with the suggested algorithm on the basis of initial overhead, resubscriber rate and a number of cluster.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.104-108
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• 2007

Ad hoc networks are a type of mobile network that function without any fixed infrastructure. One of the weaknesses of ad hoc network is that a route used between a source and a destination is to break during communication. To solve this problem, one approach consists of selecting routes whose nodes have the most stable link cost. This paper proposes a method for improving the low power distributed MAC. This method is based on the context awareness of the each nodes energy in clustering. We propose to select a new scheme to optimize energy conserving between the clustering nodes in MANET. And this architecture scheme would use context-aware considering the energy related information such as energy, RF strength, relative distances between each node in mobile ad hoc networks. The proposed networks scheme could get better improve the awareness for data to achieve and performance on their clustering establishment and messages transmission. Also, by using the context aware computing, according to the condition and the rules defined, the sensor nodes could adjust their behaviors correspondingly to improve the network routing.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.977-987
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• 2014

Many of the recent performance evaluation of clustering schemes in wireless sensor networks considered one sink node operation and fixed sink node location without mentioning about any network application requirements. However, application environments have variable requirements about their networks. In addition, network performance is sufficiently influenced by different sink node location scenarios in multi-hop based network. We also know that sink location can influence to the sensor network performance evaluation because of changed multipath of sensor nodes and changed overload spots in multipath based wireless sensor network environment. Thus, the performance evaluation results are hard to trust because sensor network is easily changed their network connection through their routing algorithms. Therefore, we suggest that these schemes need to evaluate with different sink node location scenarios to show fair evaluation result. Under the results of that, network performance evaluation results are acknowledged by researchers. In this paper, we measured several clustering scheme's performance variations in accordance with various types of sink node location scenarios. As a result, in the case of the clustering scheme that did not consider various types of sink location scenarios, fair evaluation cannot be expected.

• Journal of Information Technology Services
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• v.3 no.2
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• pp.119-127
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• 2004

A mobile ad hoc network(MANET) is a network where a set of mobile devices communicate among themselves using wireless transmission without the support of a fixed network infrastructure. The use of wireless links makes MANET susceptible to attack. Eavesdroppers can access secret information, violating network confidentiality, and compromised nodes can launch attack from within a network. Therefore, the security for MANET depends on using the cryptographic key, which can make the network reliable. In addition, because MANET has a lot of mobile devices, the authentication scheme utilizing only the symmetric key cryptography can not support a wide range of device authentication. Thereby, PKI based device authentication technique in the Ad Hoc network is essential and the paper will utilize the concept of PKI. Especially, this paper is focused on the key management technique of PKI technologies that can offer the advantage of the key distribution, authentication, and non-reputation, and the issuing and managing technique of certificates based on clustering using Threshold Cryptography for secure communication in MANET.

• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.99-113
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• 2002

The multi-class traffic assignment problem is the most typical one of the multi-solution traffic assignment problems and, recently formulation of the models and the solution algorithm have been received a great deal of attention. The useful solution algorithm, however, has not been proposed while formulation of the multi-class traffic assignment could be performed by adopting the variational inequality problem or the fixed point problem. In this research, we developed a hybrid solution algorithm which combines GA algorithm, diagonal algorithm and clustering algorithm for the multi-class traffic assignment formulated as a variational inequality Problem. GA algorithm and clustering algorithm are introduced for the wide area and small cost. We also performed an experiment with toy network(2 link) and tested the characteristics of the suggested algorithm.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.548-553
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• 2004

In this paper we propose modified LBG algorithm to minimize quantization errors. When we apply conventional LBG algorithm for speaker verification system, problems that result from small amount of training data can be generated. That is, quantization error comes from fixed-sized codebook without any consideration for speaker characteristics and splitting vector in the wrong direction worsen performance of speaker verification system. So, we propose modified clustering method that has variable sized codebook according to speaker characteristics and makes right splitting direction by finding the farthest member away from mean and then find another member from the member. Simulation results show effectiveness of the proposed algorithm.