• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1199-1208
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• 2005

Nowadays, it is performed actively to optimize by using an approximate model. This is called the approximate optimization. In addition, the sequential approximate optimization (SAO) is the repetitive method to find an optimum by considering the convergence of an approximate optimum. In some recent studies, it is proposed to increase the fidelity of approximate models by applying the sequential sampling. However, because the accuracy and efficiency of an approximate model is directly connected with the design area and the termination criteria are not clear, sequential sampling method has the disadvantages that could support an unreasonable approximate optimum. In this study, the SAO is executed by using trust region, Kriging model and Optimal Latin Hypercube design (OLHD). Trust region is used to guarantee the convergence and Kriging model and OLHD are suitable for computer experiment. finally, this SAO method is applied to various optimization problems of highly nonlinear mathematical functions. As a result, each approximate optimum is acquired and the accuracy and efficiency of this method is verified by comparing with the result by established method.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.906-915
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• 2005

In this paper we propose content based image retrieval method using sequential clustering and projection information. Proposed method uses the mean of color in clustered color regions by sequential clustering and the projection information in each clustered color regions, which combines spatial information with color information in images efficiently. The experimental results showed that the proposed method retrieval efficiency improved 11.6 percent over conventional methods. In addition, the proposed method robustly tolerates large changes in appearance and shape caused by changes in viewing positions, camera zooms, etc.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.7-14
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• 2003

In the back analysis of braced excavation based on displacement measurements, the accumulated errors of abnormal displacement caused by unexpected loads are usually observed. To minimize such errors, in this study, displacement increment was used fur back analysis rather than displacement for the conventional method. That is, the increment of sequential displacement is used as the objective function and the back analysis program is developed by taking advantage of sequential linear programming method by modified method of feasible directions. Based on small scale model test, the analysis of proposed method is verified.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.5
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• pp.896-904
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• 1987

In this paper, a design method for sequential circuit which is easy to have Built-in Self Test is kproposed using the functional advantages of multifunctional BILBO and LSSD. To achieve the hardware reduction, it is designed that a multifunctional BILBO has double operational functions of NLFSR and LFSR, when neccessary, and that test signal could be used as an input-output signal in the same line. By applying the proposed multifunctional BILBO to the sequential PLA, the test patterns and the additional circuit could be reduced in test operation and the propagation delay is vanished in normal operation, as we expected. Above them, the partitioned method for large scale sequential circuit is also suggested and it is observed that test patterns and additional circuit in them reduced by this method.

• Speech Sciences
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• v.7 no.4
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• pp.41-47
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• 2000

This paper concerns an effective text-prompted speaker verification method to increase the performance of speaker verification. While various speaker verification methods have already been developed, their effectiveness has not yet been formally proven in terms of achieving an acceptable performance level. It is also noted that the traditional methods were focused primarily on single, prompted utterance for verification. This paper, instead, proposes sequential decision method using variable threshold focused at handling two utterances for text-prompted speaker verification. Experimental results show that the proposed speaker verification method outperforms that of the speaker verification scheme without using the sequential decision by a factor of up to 3 times. From these results, we show that the proposed method is highly effective and achieves a reliable performance suitable for practical applications.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.161-164
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• 2005

Data mining techniques can be applied to identify patterns of interest in the gene expression data. One goal in mining gene expression data is to determine how the expression of any particular gene might affect the expression of other genes. To find relationships between different genes, association rules have been applied to gene expression data set [1]. A notable limitation of association rule mining method is that only the association in a single profile experiment can be detected. It cannot be used to find rules across different condition profiles or different time point profile experiments. However, with the appearance of time-series microarray data, it became possible to analyze the temporal relationship between genes. In this paper, we analyze the time-series microarray gene expression data to extract the sequential patterns which are similar to the association rules between genes among different time points in the yeast cell cycle. The sequential patterns found in our work can catch the associations between different genes which express or repress at diverse time points. We have applied sequential pattern mining method to time-series microarray gene expression data and discovered a number of sequential patterns from two groups of genes (test, control) and more sequential patterns have been discovered from test group (same CO term group) than from the control group (different GO term group). This result can be a support for the potential of sequential patterns which is capable of catching the biologically meaningful association between genes.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.477-484
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• 2004

The technique of sequential pattern mining means generating a set of inter-transaction patterns residing in time-dependent data. This paper proposes a new method for generating sequential patterns with the use of Hellinger measure. While the current methods are generating single dimensional sequential patterns within a single attribute, the proposed method is able to detect multi-dimensional patterns among different attributes. A number of heuristics, based on the characteristics of Hellinger measure, are proposed to reduce the computational complexity of the sequential pattern systems. Some experimental results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.87.4-87
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• 2002

$\textbullet$ Introduction $\textbullet$ Algorithm of BMPC method $\textbullet$ Sequential solution method $\textbullet$ Simulation $\textbullet$ Conclusion

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.482-487
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• 1988

A sequential-clustered integrator based on GEAR method is developed for the purpose of dynamic simulation of chemical processes. And a single simulator structure capable of employing various integration approaches is designed and its efficiency and flexiblity is evaluated. Sequential integration method is superior to simultaneous method for the process without recycle, but simultaneous method is very powerful for the coupled process with recycle.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.14 no.3
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• pp.339-348
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• 2001

More often a commercial package for the structural analysis is necessary in the structural optimum design. In this case the task of combining the package with an optimization program must be required, hut it is not so simple because interchanging some data between them is difficult. Sequential approximate optimization is currently used as a natural way to overcome the hard task. If sequential approximate optimization has wide side constraints that the lower limit of design variables is very small and their upper limit is very large, it is not so easy to obtain approximated functions accurately for the whole design domain. This paper proposes a sequential design domain method, which is very useful to carry out sequential approximate optimization in this case. In this paper, the response surface methodology is used to obtain approximated functions and the orthogonal array is used for design of experiments. The sequential approximate optimization of 3-bar and 10-bar trusses is demonstrated to verify the reliability of the sequential design domain method.