• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2270-2277
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• 2016

In modern society, creation and distribution of multimedia contents is being actively conducted. These multimedia information have come out the enormous amount daily, the amount of data is also large enough it can't be compared with past text information. Since it has been increased for a need of the method to efficiently store multimedia information and to easily search the information, various methods associated therewith have been actively studied. In particular, image search methods for finding what you want from the video database or multiple sequential images, have attracted attention as a new field of image processing. Image retrieval method to be implemented in this paper, utilizes the attribute of corner patches based on the corner points of the object, for providing a new method of efficient and robust image search. After detecting the edge of the object within the image, the straight lines using a Hough transformation is extracted. A corner patches is formed by defining the extracted intersection of the straight line as a corner point. After configuring the feature vectors with patches rearranged, the similarity between images in the database is measured. Finally, for an accurate comparison between the proposed algorithm and existing algorithms, the recall precision rate, which has been widely used in content-based image retrieval was used to measure the performance evaluation. For the image used in the experiment, it was confirmed that the image is detected more accurately in the proposed method than the conventional image retrieval methods.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.714-716
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• 1996

This paper presents an optimization method for optimal reactive power dispatch which minimizes real power loss and improves voltage profile of power systems using evolutionary computation such as genetic algorithms(GAs), evolutionary programming(EP). and evolution strategy(ES). Many conventional methods to this problem have been proposed in the past, but most these approaches have the common defect of being caught to a local minimum solution. Recently, global search methods such as GAs, EP, and ES are introduced. The proposed methods were applied to the IEEE 30-bus system. Each simulation result, compared with that obtained by using a conventional gradient-based optimization method, Sequential Quadratic Programming (SQP), shows the possibility of applications of evolutionary computation to large scale power systems.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.610-617
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• 2003

Similarity matching in video database is of growing importance in many new applications such as video clustering and digital video libraries. In order to provide efficient access to relevant data in large databases, there have been many research efforts in video indexing with diverse spatial and temporal features. however, most of the previous works relied on sequential matching methods or memory-based inverted file techniques, thus making them unsuitable for a large volume of video databases. In order to resolve this problem, this paper proposes an effective and scalable indexing technique using a trie, originally proposed for string matching, as an index structure. For building an index, we convert each frame into a symbol sequence using a window order heuristic and build a disk-resident trie from a set of symbol sequences. For query processing, we perform a depth-first search on the trie and execute a temporal segmentation. To verify the superiority of our approach, we perform several experiments with real and synthetic data sets. The results reveal that our approach consistently outperforms the sequential scan method, and the performance gain is maintained even with a large volume of video databases.

• The KSFM Journal of Fluid Machinery
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• v.12 no.3
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• pp.7-12
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• 2009

In this paper, shape optimization based on three-dimensional flow analysis has been performed for impeller design of centrifugal compressor. To evaluate the objective function of an isentropic efficiency, Reynolds-averaged Navier-Stokes equations are solved with SST (Shear Stress Transport) turbulence model. The governing equations are discretized by finite volume approximations. The optimization techniques based on the radial basis neural network method are used for the optimization. Latin hypercube sampling as design of experiments is used to generate thirty design points within design space. Sequential quadratic programming is used to search the optimal point based on the radial basis neural network model. Four geometrical variables concerning impeller shape are selected as design variables. The results show that the isentropic efficiency is enhanced effectively from the shape optimization by the radial basis neural network method.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2005.03a
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• pp.521-528
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• 2005

In our previous study, we have developed a preliminary design procedure of MR dampers for controlling seismic response of building structures. In this paper, the effectiveness the proposed method is verified through the numerical analysis of the structures with various period and story number, and twenty earthquake loads are used for statistical assessment. The comparison between the proposed method and simplified sequential search algorithm indicates that the capacity, number and the placement of the MR damper which can achieve the given performance objective are reasonably determined using the proposed design procedure.

• Bulletin of the Society of Naval Architects of Korea
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• v.21 no.2
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• pp.1-7
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• 1984

This paper is concerned with an optimum design study of containerships in preliminary stage by applying economic criteria. The Net Present Value Index (NPVI) and the Required Freight Rate(RFR) are used as measures of merit. Hooke & Jeeves direct search method and External Penalty Function method of Sequential Unconstrained Minimization Techniques(SUMT) are used for solving constrained nonlinear optimization problem. Sensitivity analysis is carried out to investigate the effect on the optimum solution due to change of values in some parameters such as crane capacity, load factor, oil price, ship speed and the ratio between loaded FEU and TEU.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.155-162
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• 2008

Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological dataset with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.943-948
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• 2018

In this paper, we propose a hybrid approach of combining $A^*$ and Genetic algorithm in the path search problem. In $A^*$, the cost from a start node to the intermediate node is optimized in principle but the path from that intermediate node to the goal node is generated and tested based on the cumulated cost and the next node in a priority queue is chosen to be tested. In that process, we adopt the genetic algorithm principle in that the group of nodes to generate the next node from an intermediate node is tested by its fitness function. Top two nodes are selected to use crossover or mutation operation to generate the next generation. If generated nodes are qualified, those nodes are inserted to the priority queue. The proposed method is compared with the original sequential selection and the random selection of the next searching path in $A^*$ algorithm and the result verifies the superiority of the proposed method.

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.515-525
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• 2000

The purpose of this paper was to develop size & shape optimization programming algorithm of plane trusses. The optimum techniques applied in this study were extended penalty method of Sequential Unconstrained Minimization Techniques(SUMT) and direct search method with multi-variables proposed by Hooke & Jeeves. Upper mentioned two methods were used iteratively at each level of size and shape optimization routines. The design variables of size optimization were circular steel tube(structural member) diameter and thickness, those of shape optimization were joint coordinates, and the objective function was represented as total weight of truss. During the optimum design, two level procedures of size and shape optimization were interacted iteratively until the final optimum values were attained. At the previous studies about shape optimization of truss, the member sectional areas and coordinates were applied as design variables. So that they could not apply the buckling effect of compression member. In this paper, actual sizes of member and nodal coordinates are used as design variables to consider the buckling effect of compression member properly.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.4
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• pp.114-122
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• 2013

This study introduces an optimization methodology for the determination of gate location that ensures the melt flow balance within a part cavity of injection mold. A new sequential direct-search scheme based on the recursive reduction of the designer-specified gate design area is developed, and it is integrated with a commercial flow simulation tool for optimization. To quantify the level of melt flow balance, we employ the maximum difference among the fill times for the melt fronts to reach the boundary elements of part cavity as objective function. The proposed methodology is successfully applied in the case study of melt flow balancing in molding of a bar code scanner model. The result shows that the melt flow balance at the optimized gate positions is significantly improved from that for the initial gate position.