• Journal of Communications and Networks
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• v.13 no.6
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• pp.655-663
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• 2011

Diffuse optical wireless (DOW) systems have the advantage that they do not require point-to-point siting so one transmitter can communicate with several receivers. In this paper, we investigate multiple access scheduling methods for downlink orthogonal frequency division multiplexing (OFDM) in diffuse optical wireless networks. Unlike the radio frequency (RF) channel, the DOW channel has low-pass filter characteristics and so requires different scheduling methods than those developed for the RF channel. Multi-user diversity orthogonal frequency division multiple access (OFDMA) systems nominate a cluster of subcarriers with the largest signal-to-noise-ratio for transmission. However, in a DOW channel, most users would choose the lowest frequency clusters of subcarriers. To remedy this problem, we make two proposals. The first is to use a variable cluster size across the subcarriers; the lower frequency clusters will have fewer subcarriers while the higher frequency clusters will have more subcarriers. This will equalize the capacity of the clusters. The second proposal is to randomize a user's cluster selection from a group of clusters satisfying a minimum threshold. Through simulation it is shown that combining these strategies can increase the throughput while ensuring a fair distribution of the available spectrum.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.203-210
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• 2000

In this paper, we propose a new unsupervised learning network and competitive learning algorithm for pattern classification. The proposed network is based on relative similarity, which is similarity measure between input data and cluster group. So, the proposed network and algorithm is called relative similarity network(RSN) and learning algorithm. According to definition of similarity and learning rule, structure of RSN is designed and pseudo code of the algorithm is described. In general pattern classification, RSN, in spite of deletion of learning rate, resulted in the identical performance with those of WTA, and SOM. While, in the patterns with cluster groups of unclear boundary, or patterns with different density and various size of cluster groups, RSN produced more effective classification than those of other networks.

• Journal of the Korea Society for Simulation
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• v.22 no.3
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• pp.71-79
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• 2013

Web server cluster systems are widely used, where a large number of PC level servers are interconnected via network. This paper focuses on forecasting an appropriate number of web servers which can serve four different classes of user requests, simple web page viewing, knowledge query, motion picture viewing and motion picture uploading. Two ways of serving different classes of web service requests are considered, commonly used web servers and service dedicated web servers. Computer simulation experiments are performed in order to find a good way of allocating web servers among different classes of web service requests, maintaining certain levels of resource utilization and response time.

• Journal of the Korean Society of Safety
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• v.22 no.6
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• pp.81-86
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• 2007

The purpose of this study is to provide foot classification on 30 generation young men and women by factor analysis and cluster analysis. The sample for this work was chosen from data which were collected and measured by Size Korea during two years($2003{\sim}2004$). In order to analyze and compare features of the foot of men and women, analysis was performed about 871 subjects(male: 422, female: 449) on 24 body parts including height, width, thickness, circumference, length and angle. According to the result of factor analysis about measured data, there were seven factors and six factors for men and women respectively. After cluster analysis, data for men and women were commonly divided by three types for utilization of research results. Type 1 and type 3 had wide distribution about men. Type 2 had wide distribution about women. The results of this study can be applied in manufacturing and design of comfortable shoes and socks.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.67-75
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• 2010

Network reprogramming is a technology that allows several sensor nodes deployed in sensor field to be repaired remotely. Unlike general communication in sensor network where small amount of data is transferred, network reprogramming requires reliable transfer of large amount of data. The existing network reprogramming techniques suffers high cost and large energy consumption to recover data loss in node communication. In this paper, a cluster based network reporgramming scheme is proposed for sensor network. It divides sensor field into several clusters and chooses a cluster header in charge of data relay to minimize duplicated transmission and unnecessary competition. It increases reliability by effective error recovery through status table.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.8
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• pp.375-387
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• 2005

This paper presents an application of parallel Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a service restoration in distribution systems. The main objective of service restoration of distribution systems is, when a fault or overload occurs, to restore as much load as possible by transferring the do-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints, which is a combinatorial optimization problem. This problem has many constraints with many local minima to solve the optimal switch position. This paper develops parallel GA-TS algorithm for service restoration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solutions of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper $10\%$ of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node after predetermined iterations are executed. For parallel computing, we developed a PC cluster system consists of 8 PCs. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through ethernet switch based fast ethernet. To show the validity of the proposed method, proposed algorithm has been tested with a practical distribution system in Korea. From the simulation results, we can find that the proposed algorithm is efficient for the distribution system service restoration in terms of the solution quality, speedup, efficiency and computation time.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.435-447
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• 2006

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel AEA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.11
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• pp.635-642
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• 2004

The traditional communication protocols such as TCP/IP are not suitable for PC cluster systems because of their high software processing overhead. To eliminate this overhead, industry leaders have defined the Virtual Interface Architecture (VIA). VIA provides two different data transfer mechanisms, a traditional Send/Receive model and the Remote Direct Memory Access (RDMA) model. RDMA is extremely efficient way to reduce software overhead because it can bypass the OS and use the network interface controller (NIC) directly for communication, also bypass the CPU on the remote host. In this paper, we have implemented VIA-based RDMA mechanism in hardware. Compared to the traditional Send/Receive model, the RDMA mechanism improves latency and bandwidth. Our RDMA mechanism can also communicate without using remote CPU cycles. Our experimental results show a minimum latency of 12.5${\mu}\textrm{s}$ and a maximum bandwidth of 95.5MB/s. As a result, our RDMA mechanism allows PC cluster systems to have a high performance communication method.

• Journal of the Chungcheong Mathematical Society
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• v.26 no.2
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• pp.351-356
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• 2013

In this article, we discuss the notions of chain prolongation functions on locally compact spaces and get some results for the concepts. We show that chain prolongation function is a cluster map.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.601-605
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• 1991

In this paper an approximate solution method for the large-scale Traveling Salesman Problem(TSP) is presented. The method start with the subdivision of the problem domain into a number of clusters by considering their geometries. The clusters have limited number of nodes so as to get local solutions. They are linked to give the least path which covers the whole domain and become TSPs with start- and end-node. The approximate local solutions in each cluster are obtained by using geometrical property of the cluster, and combined to give an overall-approximate solution for the large-scale TSP.