• The Journal of the Acoustical Society of Korea
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• v.21 no.8
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• pp.735-743
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• 2002

In this paper, we propose three new text-independent speaker identification methods. At first, to exclude the frames not having enough features of speaker's vocal from calculation of the maximum likelihood, we propose the FS(Frame Selection) method. This approach selects the important frames by evaluating the difference between the biggest likelihood and the second in each frame, and uses only the frames in calculating the score of likelihood. Our secondly proposed, called the Hybrid, is a combined version of the FS and WMR(Weighting Model Rank). This method determines the claimed speaker using exponential function weights, instead of likelihood itself, only on the selected frames obtained from the FS method. The last proposed, called MWMR (Modified WMR), considers both original likelihood itself and its relative position, when the claimed speaker is determined. It is different from the WMR that take into account only the relative position of likelihood. Through the experiments of the speaker identification, we show that the all the proposed have higher identification rates than the ML. In addition, the Hybrid and MWMR have higher identification rate about 2% and about 3% than WMR, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.301-307
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• 2016

This paper proposes a lyric search method to consider the characteristics of the user query. According to the fact that queries for the lyric search are derived from highlight parts of the music, this paper uses the hierarchical agglomerative clustering to find the highlight and proposes a Gaussian weighting to consider the neighbor of the highlight as well as highlight. By setting the mean of a Gaussian weighting at the highlight, this weighting function has higher weights near the highlight and the lower weights far from the highlight. Then, this paper constructs a index of lyrics with the gaussian weighting. According to the experimental results on a data set obtained from 5 real users, the proposed method is proved to be effective.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.767-770
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• 1996

A H$\_$.inf./ contro theory was applied to motor speed control of two-mass system to get controller which acts effectively with control object including uncertainties. The H$\_$.inf./ control problem was composed and solved. After that, numerical simulation were executed to confirm ability of the controller which compared with PI controller.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.468-470
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• 1986

An optimal control in heat-up operation was formulated for minimizing the quadratic performance criterion which is a function of temperature, temperature gradient in the wall and fuel flow rate. For optimal control law computations mathematical model was simplified with assumptions and then linearized by use of orthogonal collocation in radial direction. Effects of weighting function assigned to temperature and temperature gradient and final time were compared with industrial data.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.55-63
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• 1995

The characteristics of $I{\lambda}$-optimality are investigated with repsect to other experimental design's criteria, D-and G-optimality. The comparisons are based on D- and G-, and $I{\lambda}$-efficiencies using the Beta(p, q) distribution as a weighting function for $I{\lambda}$-optimality. Results indicate that serious consideration should be given to the $I{\lambda}$-optimality criterion especially when the error variance function is not homogeneous.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.548-549
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• 2012

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.709-710
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• 2012

• Journal of KIISE:Databases
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• v.32 no.3
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• pp.228-242
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• 2005

The projected clustering seeks to find clusters in different subspaces within a high dimensional dataset. We propose an algorithm to discover near optimal projected clusters without user specified parameters such as the number of output clusters and the average cardinality of subspaces of projected clusters. The objective function of the algorithm computes projected energy, quality, and the number of outliers in each process of clustering. In order to minimize the projected energy and to maximize the quality in clustering, we start to find best subspace of each cluster on the density of input points by comparing standard deviations of the full dimension. The weighting factor for each dimension of the subspace is used to get id of probable error in measuring projected distances. Our extensive experiments show that our algorithm discovers projected clusters accurately and it is scalable to large volume of data sets.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.12
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• pp.59-66
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• 2010

We developed a model-based controller for 6-DOF micropositioning of a precision stage using $H_{\infty}$ norm, For the design, a state-space system of the mathematical model of the stage is derived In developing the controller, weighting functions are effectively designed in consideration of upper bounds of the sensitivity of the control loop and control input. Step responses in open and closed loop control are provided to verify the micropositioning performance of the stage. By applying the developed controller we prove that the inverse of the weighting function forms the upper bound of the control loop. It is also found that the controller makes the same sensitivity shape with all the DOFs due to the use of $H_{\infty}$ norm. The developed controller is expected to be applied successfully for industrial use.

• Nuclear Engineering and Technology
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• v.17 no.2
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• pp.129-135
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• 1985

Effects of differences between fine- and broad-group structures and spectrum as a weighting function at the resonance energy region of iron on a neutron shielding calculation were analyzed with the ANISN code and ENDF/B-IV data. The problems analyzed are the broad-group effect, the effect for variation of iron thickness, and the effect of problem-dependent weighting spectrum. In order to verify the group data and method used, a calculational benchmark was performed with the continuous-energy Monte Carlo code VIM. The result was compared with the ANISN calculations using the fine- and broad-group data.