• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.501-512
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• 2003

This paper proposes an indexing technique for fast retrieval of similar image subsequences using the multi-dimensional time warping distance. The time warping distance is a more suitable similarity measure than Lp distance in many applications where sequences may be of different lengths and/or different sampling rates. Our indexing scheme employs a disk-based suffix tree as an index structure and uses a lower-bound distance function to filter out dissimilar subsequences without false dismissals. It applies the normaliration for an easier control of relative weighting of feature dimensions and the discretization to compress the index tree. Experiments on medical and synthetic image sequences verify that the proposed method significantly outperforms the naive method and scales well in a large volume of image sequence databases.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.99-108
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• 2004

In this paper, a new fast detection and clutter rejection method is proposed for CCD-image-based Automatic Target Detection System. For defence application, fast computation is a critical point, thus we concentrated on the ability to detect various targets with simple computation. In training stage, 1D template set is generated by regional vertical projection and K-means clustering, and binary tree structure is adopted to reduce the number of template matching in test stage. We also use adaptive skip-width by Correlation-based Adaptive Predictive Search(CAPS) to further improve the detecting speed. In clutter rejection stage, we obtain Fourier Descriptor coefficients from boundary information, which are useful to rejected clutters.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.626-631
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• 2005

This paper presents the target object search algorithm under dynamic programming (DP) in the Tree-type maze. We organized an experimental environment with the concatenation Y-shape diverged way, small mobile robot, and a target object. By the principle of optimality, the backbone of DP, an agent recognizes that a given whole problem can be solved if the values of the best solution of certain ancillary problem can be determined according to the principle of optimality. In experiment, we used two different control algorithms: a left-handed method and DP. Finally we verified the efficiency of DP in the practical application using a real robot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.647-666
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• 2009

Multiple-input multiple-output (MIMO) multiplexing is an attractive technology that increases the channel capacity without requiring additional spectral resources. The design of low complexity and high performance detection algorithms capable of accurately demultiplexing the transmitted signals is challenging. In this technical survey, we introduce the state-of-the-art MIMO detection techniques. These techniques are divided into three categories, viz. linear detection (LD), decision-feedback detection (DFD), and tree-search detection (TSD). Also, we introduce the lattice basis reduction techniques that obtain a more orthogonal channel matrix over which the detection is done. Detailed discussions on the advantages and drawbacks of each detection algorithm are also introduced. Furthermore, several recent author contributions related to MIMO detection are revisited throughout this survey.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1746-1752
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• 2000

In this paper, a cache mechanism is proposed to improve the speed of query processing in distributed director database systems. To decrease search time of requested objects and query processing time. query requests and results about objects in a remote site are stored in the cache of a local site. Cache system architecture is designed according to the classified information. Cache schema are designed for each cache information. Operational algorithms are developed for meta data cache which has meta data tree. This tree improves the speed of query processing by reducing the scope of search space. Finally, performance evaluation is performed by comparing the proposed cache mechanism with X500.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.4
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• pp.191-198
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• 2003

The generalized knapsack problem or gknap is the combinatorial optimization problem of optimizing a nonnegative linear function over the integral hull of the intersection of a polynomially separable 0-1 polytope and a knapsack constraint. The knapsack, the restricted shortest path, and the constrained spanning tree problem are a partial list of gknap. More interesting1y, all the problem that are known to have a fully polynomial approximation scheme, or FPTAS are gknap. We establish some necessary and sufficient conditions for a gknap to admit an FPTAS. To do so, we recapture the standard scaling and approximate binary search techniques in the framework of gknap. This also enables us to find a weaker sufficient condition than the strong NP-hardness that a gknap does not have an FPTAS. Finally, we apply the conditions to explore the fully polynomial approximability of the constrained spanning problem whose fully polynomial approximability is still open.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.85-92
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• 2006

In this paper, we study a wireless cellular network design problem. It consists of selecting the location of the base station controllers and mobile service switching centres, selecting their types, designing the network into a tree-topology, and selecting the link types, while considering the location and the demand of base transceiver stations. We propose a constraint programming model and develop a heuristic combining local search and constraint programming techniques to find very good solutions in a reasonable amount of time for this category of problem. Numerical results show that our approach, on average, improves the results from the literature.

• Clean Technology
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• v.7 no.2
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• pp.99-107
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• 2001

Optimization methodologies have been proposed of find the best environment-friendly recycling pathways of plastic materials based on life-cycle assessment (LCA) methodology. The main difficulty in conducting this optimization study is that multiple environmental burdens have to be considered simultaneously as the cost functions. Instead of generating conservative Pareto or noninferior solutions following multi-objective optimization approaches, we have proposed some practical criteria on how to combine the different environmental burdens into a single measure. The obtained single objective optimization problem can then be solved by conventional nonlinear programming techniques or, more effectively, by a tree search method based on decision flows. The latter method reduces multi-dimensional optimization problems to a set of one-dimensional problems in series. It is expected the suggested tree search approach can be applied to many LCA studies as a new promising optimization tool.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.153-168
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• 1994

This paper is concerned with the development of tree-search algorithm for the exact solution to the vehicle problem (VRP), where set of vehicles of known capacity based at depot, have to be routed in order to supply customers with known requirements. When is required is to design routes, so that the total cost (i. e. total route length or time duration, ect.) is minimized. For obtianing the exact solution, the most important factors are the value of bound and branching strategy. Using the bound based on with bound ascent procedures from subgradient and state-space ascents, the incorporation of bounds into tree search algorithm to solve the problem is shown. Computational results of the corresponding algorithm show that VRPs with up to 40 customers can be solved optimally with this algorithm.

• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.33-38
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• 2008

최근 컴퓨터비전이나 로봇 공학 분야에서 가격이 저렴한 웹캠을 이용한 영상, 즉 2차원 영상으로부터 물체를 인식하는 연구가 활발히 이루어지고 있다. 이러한 로봇이나 비전에서 물체를 찾아내는 여러 가지 방향들이 제시되고 있으며, 지속적으로 로봇은 사람과 유사해져가고 있다. 이를 실현하기 위해서는 사람이 사과를 보고 사과라고 알기 때문에 사과라고 인식하듯이 로봇 또한 미리 알고 있어야 한다는 가정 하에 내용기반의 물체인식이 필요하다. 그러나 엄청난 양의 내용의 데이터베이스가 필요하다. 그래서 용량은 하드웨어기술로 커버가 가능하지만 화면상에 있는 물체들을 빠르게 데이터베이스상의 자료와 매칭이 되어야한다. 본 논문에서는 이미지를 SIFT(Scale Invariant Feature Transform)알고리즘으로 BTS(Binary Search Tree)로 트리구조의 데이터베이스를 구축하여 많은 양의 데이터베이스 중 빠르게 검색하여 화면에 있는 물체를 인식하는 방법을 제안하였다.