• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.711-725
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• 2013

A heuristic with multi-byte suffix matching plays an important role in real pattern matching algorithms. By skipping many characters at a time in the process of comparing a given pattern with the text, the pattern matching algorithm based on a heuristic with multi-byte suffix matching shows a faster average search time than algorithms based on deterministic finite automata. Based on various experimental results and simulations, the previous works show that the pattern matching algorithms with multi-byte suffix matching performs well. However, there have been limited studies on the mathematical model for analyzing the performance in a standard manner. In this paper, we propose a new probabilistic model, which evaluates the performance of a heuristic with multi-byte suffix matching in an average-case search. When the theoretical analysis results and experimental results were compared, the proposed probabilistic model was found to be sufficient for evaluating the performance of a heuristic with suffix matching in the real pattern matching algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1860-1863
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• 1997

Transfer alignement is the process of initializing attitude of slave INS using the data of master INS. This paper presents the performance analysis of transfer alignment at sea using convariance analysis method. Velocity & angle matching and angular rate & acceleration matching are used for analysis, and the performance of two matching methods are compared. We propose a new method for angular rate & acceleration matching. Under the assumption of accurate modeling of ship flexure, the performance of transfer alignment time and accuray is improved very much for the new method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1234-1239
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• 2011

The scan matching is widely used in localization and mapping of mobile robots. This paper presents a probabilistic scan matching method. To improve the performance of the scan matching, a direction of data point is incorporated into the scan matching. The direction of data point is calculated using the line fitted by the neighborhood data. Owing to the incorporation, the performance of the matching was improved. The number of iterations in the scan matching decreased, and the tolerance against a high rotation between scans increased. Based on real data of a laser range finder, experiments verified the performance of the proposed direction augmented probabilistic scan matching algorithm.

• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1619-1627
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• 2017

Image hashing has been successfully applied for the problems associated with the protection of intellectual property, management of large database and indexation of content. For a reliable hashing system, improving hash matching accuracy is crucial. In order to improve the hash matching performance, we propose an asymmetric hash matching method using the psychovisual threshold, which is the maximum amount of distortion that still allows the human visual system to identity an image. A performance evaluation over sets of image distortions shows that the proposed asymmetric matching method effectively improves the hash matching performance as compared with the conventional Hamming distance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.135-141
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• 2013

String matching is one of the key algorithms in network security and many areas could be benefit from a faster string matching algorithm. Based on the most efficient string matching algorithm in sual applications, the Boyer-Moore (BM) algorithm, a novel algorithm called RQS is proposed. RQS utilizes an improved bad character heuristic to achieve bigger shift value area and an enhanced good suffix heuristic to dramatically improve the worst case performance. The two heuristics combined with a novel determinant condition to switch between them enable RQS achieve a higher performance than BM both under normal and worst case situation. The experimental results reveal that RQS appears efficient than BM many times in worst case, and the longer the pattern, the bigger the performance improvement. The performance of RQS is 7.57~36.34% higher than BM in English text searching, 16.26~26.18% higher than BM in uniformly random text searching, and 9.77% higher than BM in the real world Snort pattern set searching.

• Management Science and Financial Engineering
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• v.10 no.1
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• pp.77-96
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• 2004

In this paper, we present a dynamic matching methodology for the logistics brokerage agent that intermediates empty vehicles and freights registered to the logistics e-marketplace by car owners and shippers. In this matching methodology, two types of decisions should be made： one is when to match freights and vehicles and the other is how to match freights and vehicles at that time. We propose three strategies for deciding when to match, ie. real time matching (RTM) , periodic matching (PM), and fixed matching (FM) and use Hungarian method for solving the how-to-match problem. In order to compare the performance of the when-to-match strategies, computational experiments are done and the results show that the waiting-and-matching strategies, PM and FM, give better performance than real time matching strategy, RTM. We can expect that the suggested matching methodology may be used as an efficient and effective tool for the brokerage agent in the logistics e-marketplaces.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.449-457
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• 2011

As automated image processing techniques have been required in multi-temporal/multi-sensor geospatial image applications, use of automated but highly invariant image matching technique has been a critical ingredient. Note that there is high possibility of geometric and spectral differences between multi-temporal/multi-sensor geospatial images due to differences in sensor, acquisition geometry, season, and weather, etc. Among many image matching techniques, the SIFT (Scale Invariant Feature Transform) is a popular method since it has been recognized to be very robust to diverse imaging conditions. Therefore, the SIFT has high potential for the geospatial image processing. This paper presents a performance test results of the SIFT on geospatial imagery by simulating various image differences such as shear, scale, rotation, intensity, noise, and spectral differences. Since a geospatial image application often requires a number of good matching points over the images, the number of matching points was analyzed with its matching positional accuracy. The test results show that the SIFT is highly invariant but could not overcome significant image differences. In addition, it guarantees no outlier-free matching such that it is highly recommended to use outlier removal techniques such as RANSAC (RANdom SAmple Consensus).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.97-103
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• 2005

Most car navigation systems(CNS) estimate the vehicle's location using global positioning system(GPS) or dead reckoning(DR) system. However, the estimated location has undesirable errors because of various noise sources such as unpredictable GPS noises. As a result, the measured position is not lying on the road, although the vehicle is known to be restricted on the road network. The purpose of map matching is to locate the vehicle's position on the road network where the vehicle is most likely to be positioned. In this paper, we analyze some general map matching algorithms first. Then, we propose a map matching method using compensation vectors to improve the performance of map matching. The proposed method calculates a compensation vector from the discrepancy between a measured position and an estimated position. The compensation vector and a newly measured position are to be used to determine the next estimation. To show the performance improvement of the map matching using compensation vectors, the real time map matching experiments are performed. The real road experiments demonstrate the effectiveness and applicability of the proposed map matching.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.139-142
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• 2004

In this paper, we present a dynamic matching methodology for the logistics brokerage agent that intermediates empty vehicles and freights registered to the logistics e-marketplace by car owners and shippers. In this matching methodology, two types of decisions should be made: one is when to match freights and vehicles and the other is how to match freights and vehicles at that time. We propose three strategies for deciding when to match, i.e. real time matching (RTM), periodic matching (PM), and fixed matching (FM) and use Hungarian method for solving tho how-to-match problem. In order to compare the performance of the when-to-match strategies, computational experiments are done and the results show that the waiting-and matching strategies, PM and FM, give better performance than real time matching strategy, RTM. We can expect that the suggested matching methodology may be used as an efficient and affective tool for the brokerage agent in the logistics e-marketplaces

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.93-113
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• 2007

In the previous research, we considered a logistics brokerage problem with the objective of minimizing total transportation lead time of freights in a logistics e-marketplace, in which a logistics brokerage agent intermediates empty vehicles and freights registered by car owners and shippers [7]. However, in the logistics e-marketplace, transportation due date tardiness is more important than the transportation lead time, since transportation service level is critically determined by whether the due date is met or not. Therefore, in this paper, we deal with the logistics brokerage problem with the objective of minimizing total tardiness of freights. Hungarian method based matching algorithms, real time matching(RTM), periodic matching(PM), and fixed matching(FM), are used for solving the problem considered in this paper. In order to test performance of the proposed algorithms, we perform computational experiments on a various problem instances. The results show that the waiting-and-matching algorithms, PM and FM, also give better performance than real time matching strategy, RTM, for the total tardiness minimization problem as the algorithms did for the total lead time minimization problem.