• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.619-622
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• 2009

P2P networks are undergoing rapid progress and inspiring numerous developments by gossip-based protocol. Gossip-based protocols for group communication have attractive scalability and reliability properties. We propose a self-organizing algorithm in the sense that the size of neighbor list achieved without any node knowing the group size. We also propose an efficient mechanism to reduce the redundancy of the system by backing up the nodes in the neighbor list. We present the design, theoretical analysis, and a detailed evaluation of the proposed algorithm and its refinements.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.377-383
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• 2002

The TSP(Traveling Salesman Problem) has been known as NP-complete, there have been various studies to find the near optimal solution. The nearest neighbor heuristic is more simple than the other algorithms which are to find the optimal solution. This paper designs and implements a new distributed nearest neighbor heuristic with bounding function for the TSP using the master/slave model of PVM(Parallel Virtual Machine). Distributed genetic algorithm obtains a near optimal solution and distributed nearest neighbor heuristic finds an optimal solution for the TSP using the near optimal value obtained by distributed genetic algorithm as the initial bounding value. Especially, we get more speedup using a new genetic operator in the genetic algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.53-60
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• 2012

Nearest-neighbor classification predicts the class of an input data with the most frequent class among the near training data of the input data. Even though nearest-neighbor classification doesn't have a training stage, all of the training data are necessary in a predictive stage and the generalization performance depends on the quality of training data. Therefore, as the training data size increase, a nearest-neighbor classification requires the large amount of memory and the large computation time in prediction. In this paper, we propose a prototype selection algorithm that predicts the class of test data with the new set of prototypes which are near-boundary training data. Based on Tomek links and distance metric, the proposed algorithm selects boundary data and decides whether the selected data is added to the set of prototypes by considering classes and distance relationships. In the experiments, the number of prototypes is much smaller than the size of original training data and we takes advantages of storage reduction and fast prediction in a nearest-neighbor classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2256-2262
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• 2015

Recently, device-to-device (D2D) communication has been considered as key technology for future cellular system, because it can solve the problem of excessive data traffic increment and can also provide new communication services. Herein, we propose new neighbor discovery for D2D communication and examine its performance. Our proposed scheme is proximity beacon based discovery in which wireless resource for pilot transmission is assigned based on the spatial correlation of wireless channel and sensing period is adjusted according to target accuracy such that power consumption can be reduced. The performance of our propose scheme is analyzed mathematically and verified through computer simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2567-2586
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• 2012

Localization of sensor nodes is a key technology in Wireless Sensor Networks(WSNs). Trilateration is an important position determination strategy. To further improve the localization accuracy, a novel Trilateration based on Point In Triangle testing Localization (TPITL)algorithm is proposed in the paper. Unlike the traditional trilateration localization algorithm which randomly selects three neighbor anchors, the proposed TPITL algorithm selects three special neighbor anchors of the unknown node for trilateration. The three anchors construct the smallest anchor triangle which encloses the unknown node. To choose the optimized anchors, we propose Point In Triangle testing based on Distance(PITD) method, which applies the estimated distances for trilateration to reduce the PIT testing errors. Simulation results show that the PIT testing errors of PITD are much lower than Approximation PIT(APIT) method and the proposed TPITL algorithm significantly improves the localization accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.1976-1996
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• 2011

Cognitive radio (CR) MAC protocol provides access control of unused spectrum resources without causing interference to primary users. To achieve this goal, in this paper a TDMA based cooperative multi-channel cognitive radio MAC (MCR-MAC) protocol is proposed for wireless ad hoc networks to provide reliable protection for primary users by achieving cooperative detection of incumbent system signals around the communication pair. Each CR node maintains transmission opportunity schedules and a list of available channels that is employed in the neighbor discovery period. To avoid possible signal collision between incumbent systems and cognitive radio ad hoc users, we propose a simple but efficient emergency notification message exchanging mechanism between neighbor CR nodes with little overhead. Our simulation results show that the proposed MCR-MAC can greatly reduce interference with primary users and remarkably improve the network throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2268-2283
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• 2013

Scalable video coding can handle peer heterogeneity of P2P streaming applications, but there is still a lack of comprehensive studies on how to use it to improve video playback quality. In this paper we propose a capacity aware scalable video coding mechanism for P2P on demand streaming system. The proposed mechanism includes capacity based neighbor selection, adaptive data scheduling and streaming layer adjustment, and can enable each peer to select appropriate streaming layers and acquire streaming chunks with proper sequence, along with choosing specific peers to provide them. Simulation results show that the presented mechanism can decrease the system's startup and playback delay, and increase the video playback quality as well as playback continuity, and thus it provides a better quality of experience for users.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1392-1405
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• 2019

The cathode voltage of aluminum electrolytic cell is relatively stable under normal conditions and fluctuates greatly when it has an anomaly. In order to detect the abnormal range of cathode voltage, an anomaly detection algorithm based on sliding window was proposed. The algorithm combines the time series segmentation linear representation method and the k-nearest neighbor local anomaly detection algorithm, which is more efficient than the direct detection of the original sequence. The algorithm first segments the cathode voltage time series, then calculates the length, the slope, and the mean of each line segment pattern, and maps them into a set of spatial objects. And then the local anomaly detection algorithm is used to detect abnormal patterns according to the local anomaly factor and the pattern length. The experimental results showed that the algorithm can effectively detect the abnormal range of cathode voltage.

• Journal of KIISE:Software and Applications
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• v.27 no.3
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• pp.302-313
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• 2000

In English-Korean machine translation, transitive verb-objective collocation is utilized for accurate translation of an English verbal phrase into Korean. This paper presents an algorithm for correct verb translation based on the k-nearest neighbor learning. The semantic distance is defined on the WordNet for the k-nearest neighbor learning. And we also present algorithms for automatic collocation dictionary optimization. The algorithms extract transitive verb-objective pairs as training examples from large corpora and minimize the examples, considering the tradeoff between translation accuracy and example size. Experiments show that these algorithms optimized collocation dictionary keeping about 90% accuracy for a verb 'build'.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.196-200
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• 2008

Recently, the query processing algorithm in spatial network database (SNDB) has attracted many interests. However, there is little research on route-based query processing algorithm in SNDB. Since the moving objects moves only in spatial networks, the route-based algorithm is very useful for LBS and Telematics applications. In this paper, we analyze In-Route Nearest Neighbor (IRNN) query, which is an typical one of route-based queries, and propose a new IRNN query processing algorithm with time constraint. In addition, we show from our performance analysis that our IRNN query processing algorithm with time constraint is better on retrieval performance than the existing IRNN query processing one.