• Spatial Information Research
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• v.19 no.3
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• pp.43-52
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• 2011

Recently, interest in location-based service (LBS) which utilizes a DBMS in mobile system environment has been increasing, and it is expected to overcome the existing file-based system's limitation in advanced in-vehicle system by utilizing DBMS's advantages such as efficient storage, transaction management, modelling and spatial queries etc. In particular, the road network data corresponds to the most essential domain in a route planning system, which needs efficient management and maintenance. Accordingly, this study aims to develop an efficient graph-based geodata model for topological network data and to support dynamic path computation algorithm based on heuristic approach in mobile LBS system. To achieve this goal, we design a data model for supporting the hierarchy of network, and implement a path planning system to evaluate its performance in mobile LBS system. Last but not least, we find out that the designed path computation algorithm with hierarchical graph model reduced the number of nodes used for finding and improved the efficiency of memory.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1395-1404
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• 2000

In this paper, we propose a heuristic wavelength routing algorithm for IP datagrams in WDM (Wavelength-Division Multiplexing) networks which operates in a distributed manner, while most previous works have focused centralized algorithms. We first present an efficient construction method for a loose virtual topology with a connectivity property, which reserves a few wavelength to cope with dynamic traffic demands properly. This connectivity property assures that data from any source node could reach any destination node by hopping one or multiple lightpaths. We then develop a high-speed distributed wavelength routing algorithm adaptive to dynamic traffic demands by using such a loose virtual topology and derive the general bounds on average utilization in the distributed wavelength routing algorithms. Finally, we show that the performance of the proposed algorithms is better than that of the FSP(Fixed Shortest-Path) wavelength routing algorithms through simulation using the NSFNET[1] and a dynamic hot-spot traffic model, and that the algorithms is a good candidate in distributed WDM networks in terms of the blocking performance, the control traffic overhead, and the computation complexity.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.395-400
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• 2011

In this paper, we propose an study of the facial emotion recognition considering the dynamical variation of emotional state in facial image sequences. The proposed system consists of two main step: facial image based emotional feature extraction and emotional state classification/recognition. At first, we propose a method for extracting and analyzing the emotional feature region using a combination of Active Shape Model (ASM) and Facial Action Units (FAUs). And then, it is proposed that emotional state classification and recognition method based on Hidden Markov Model (HMM) type of dynamic Bayesian network. Also, we adopt a Harmony Search (HS) algorithm based heuristic optimization procedure in a parameter learning of HMM in order to classify the emotional state more accurately. By using all these methods, we construct the emotion recognition system based on variations of the dynamic facial image sequence and make an attempt at improvement of the recognition performance.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.179-187
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• 2009

Most real world systems contain a series of dynamic and complex phenomena. One of common methods to understand these systems is to build a model and analyze the behavior of them. A two-step methodology comprised of clustering and then model creation is proposed for the analysis on time series data. An interface is designed for CRM(Customer Relationship Management) that provides user with 1:1 customized information using system modeling. It was confirmed from experiments that better clustering would be derived from model based approach than similarity based one. Clustering is followed by model creation over the clustered groups, by which future direction of time series data movement could be predicted. The effectiveness of the method was validated by checking how similarly predicted values from the models move together with real data such as stock prices.

• Journal of KIISE:Databases
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• v.31 no.4
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• pp.395-408
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• 2004

A conjunctive Boolean text query refers to a query that searches for tort documents containing all of the specified keywords, and is the most frequently used query form in information retrieval systems. Typically, the query specifies a long list of keywords for better precision, and in this case, the order of keyword processing has a significant impact on the query speed. Currently known approaches to this ordering are based on heuristics and, therefore, cannot guarantee an optimal ordering. We can use a systematic approach by leveraging a database query processing algorithm like the dynamic programming, but it is not suitable for a text query with a typically long list of keywords because of the algorithm's exponential run-time (Ο(n2$^{n-1}$)) for n keywords. Considering these problems, we propose a new approach based on a property called the join sequence separability. This property states that the optimal join sequence is separable into two subsequences of different join methods under a certain condition on the joined relations, and this property enables us to find a globally optimal join sequence in Ο(n2$^{n-1}$). In this paper we describe the property formally, present an optimization algorithm based on the property, prove that the algorithm finds an optimal join sequence, and validate our approach through simulation using an analytic cost model. Comparison with the heuristic text query optimization approaches shows a maximum of 100 times faster query processing, and comparison with the dynamic programming approach shows exponentially faster query optimization (e.g., 600 times for a 10-keyword query).

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.145-154
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• 2004

The growing demand for customer-responsive, made-to-order manufacturing is stimulating the need for improved dynamic decision-making processes in commercial fleet operations. Moreover, the rapid growth of electronic commerce through the internet is also requiring advanced and precise real-time operation of vehicle fleets. Accompanying these demand side developments/pressures, the growing availability of technologies such as AVL(Automatic Vehicle Location) systems and continuous two-way communication devices is driving developments on the supply side. These technologies enable the dispatcher to identify the current location of trucks and to communicate with drivers in real time affording the carrier fleet dispatcher the opportunity to dynamically respond to changes in demand, driver and vehicle availability, as well as traffic network conditions. This research investigates key aspects of real time dynamic routing and scheduling problems in fleet operation particularly in a truckload pickup-and-delivery problem under various settings, in which information of stochastic demands is revealed on a continuous basis, i.e., as the scheduled routes are executed. The most promising solution strategies for dealing with this real-time problem are analyzed and integrated. Furthermore, this research develops. analyzes, and implements hybrid algorithms for solving them, which combine fast local heuristic approach with an optimization-based approach. In addition, various partitioning algorithms being able to deal with large fleet of vehicles are developed based on 'divided & conquer' technique. Simulation experiments are developed and conducted to evaluate the performance of these algorithms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.3
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• pp.64-72
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• 2003

Comparing with transmission networks, the faults in distribution networks more often occurs because of the complicated structure and the adjacency to customers. Moreover the faults give direct damage to customers. So fault diagnosis and blackout restoration in distribution networks are very important elements to reduce the damage of customers and to maintain the stability. The restoration problem of distribution networks is subject to time. Minimizing the switching numbers in restoration process is the crucial element. In other words. the best restoration is to restore all blackout area through just one switching, if not the restoration has to be accomplished through several switching. This paper proposes the efficient restoration system in distribution networks to minimize the switching numbers. The proposed system uses the dynamic division method of hierarchical structure which consists of heuristic searching method and meta algorithm. The proposed system is applied to the sample networks, and the results showed a promising possibility.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.199-202
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• 2009

The optimal path on real road network has been changed by traffic flow of roads frequently. Therefore a path finding system to find the optimal path on real network should consider traffic flow of roads that is changed on real time. The most of existing path finding methods do not consider traffic flow of roads and do not also perform efficiently if they use traffic information. In this paper, we propose an abstraction method of real road network based on the Terminal Based Navigation System (TBNS) with technique such as TPEG. TBNS can be able to provides quality of path better than before as using traffic information that is transferred by TPEG. The proposed method is to abstract real network as simple graph in order to use traffic information. It is composed boundary nodes based on real nodes, all boundary nodes that have the same of connection are merged together. The result of path finding on an abstract graph diminishes the search space.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.4
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• pp.180-187
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• 2002

Many real-time multimedia applications, such as video conferencing have stringent end-to-end delay constraints and consume large amount of network resources. In order to support these applications efficiently, multicast routing algorithms computing least cost multicast trees that satisfy a given end-to-end delay constraint are needed. However, finding such a tree is known to be computationally expensive. Therefore, we propose a heuristic distributed multicast routing algorithm that reduces a “finding multicast tree”that satisfies a given end-to-end delay constraint and minimizes the average resulting tree cost. Also, simulation results show that the proposed algorithm has much better average cost performance than other existing algorithms.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.10
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• pp.562-574
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• 2004

We address the problem of energy-optimal voltage scheduling for fixed-priority hard real-time systems. First, we prove that the problem is NP-hard. Then, we present a fully polynomial time approximation scheme (FPTAS) for the problem. for any $\varepsilon$>0, the proposed approximation scheme computes a voltage schedule whose energy consumption is at most (1+$\varepsilon$) times that of the optimal voltage schedule. Furthermore, the running time of the proposed approximation scheme is bounded by a polynomial function of the number of input jobs and 1/$\varepsilon$. Experimental results show that the approximation scheme finds more efficient voltage schedules faster than the best existing heuristic.