• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.569-577
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• 2018

In this paper, with the aid of information which is included within data, preprocessing algorithm-based black plastic classifier is designed. The slope and area of spectrum obtained by using laser induced breakdown spectroscopy(LIBS) are analyzed for each material and its ensuing information is applied as the input data of the proposed classifier. The slope is represented by the rate of change of wavelength and intensity. Also, the area is calculated by the wavelength of the spectrum peak where the material property of chemical elements such as carbon and hydrogen appears. Using informations such as slope and area, input data of the proposed classifier is constructed. In the preprocessing part of the classifier, Principal Component Analysis(PCA) and fuzzy transform are used for dimensional reduction from high dimensional input variables to low dimensional input variables. Characteristic analysis of the materials as well as the processing speed of the classifier is improved. In the condition part, FCM clustering is applied and linear function is used as connection weight in the conclusion part. By means of Particle Swarm Optimization(PSO), parameters such as the number of clusters, fuzzification coefficient and the number of input variables are optimized. To demonstrate the superiority of classification performance, classification rate is compared by using WEKA 3.8 data mining software which contains various classifiers such as Naivebayes, SVM and Multilayer perceptron.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1361-1369
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• 2000

For the implementation of 3D Sound Localization system, the binaural filtering by HRTFs is generally employed. But the HRTF filter is of high order and its coefficients for all directions have to be stored, which imposes a rather large memory requirement. To cope with this, research works have centered on obtaining low dimensional HRTF representations without significant loss of information and synthesizing the original HRTF efficiently, by means of feature extraction methods for multivariate dat including PCA. In these researches, conventional linear PCA was applied to the frequency domain HRTF data and using relatively small number of principal components the original HRTFs could be synthesized in approximation. In this paper we applied neural network based nonlinear PCA model (NLPCA) and the nonlinear PLS repression model (NLPLS) for this low dimensional HRTF modeling and analyze the results in comparison with the PCA. The NLPCA that performs projection of data onto the nonlinear surfaces showed the capability of more efficient HRTF feature extraction than linear PCA and the NLPLS regression model that incorporates the direction information in feature extraction yielded more stable results in synthesizing general HRTFs not included in the model training.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.6
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• pp.942-950
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• 1997

Far field acoustic pressure from the evolution and interaction of three-dimensional vortex filament is calculated numerically. A vortex ring is a typical example of the three-dimensional vortex filament. An elliptic vortex ring emits a strong sound signal due to significant distortion and stretching of the vortec filament. The far field acoustic pressure is linearly dependent on the third time derivatives of the vortex positions. A numerical scheme of high resolution is employed to describe in detail the elliptic vortex ring motions which ar highly nonlinear. Descretized vortex filaments are interpolated by using a parametric blending function to remove a possible numerical instability. The distorted vortex filament, owing to the self-induced and the induced velocity from the other vortex segments, is redistributed at each time step. The accuracy and efficiency of the scheme are validated by comparisons with the analytic solution of circular vortex ring interaction.

• Korean Chemical Engineering Research
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• v.50 no.5
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• pp.830-836
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• 2012

Dead times appear often in describing process dynamics and raise some difficulties in simulating process dynamics or analyzing process control systems. To relieve these difficulties, it is needed to approximate the infinite dimensional dead time by the finite dimensional transfer function and, for this, the Pade approximation method is often used. For the accurate approximation of the dead time, high order Pade approximation is needed and the high order Pade approximation is not easy to memorize and is not stable numerically. We propose a method based on the continued fraction expansion that provides the same transfer functions. The method is excellent numerically as well as systematic to be memorized easily. It can be used conveniently for the process control lecture and computations.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.3
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• pp.380-391
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• 1997

A numerical study has been done on the evolution of particle size distribution in particle laden high temperature jet flows undergoing convection, diffusion, thermophoresis and coagulation. The dynamic behavior of these particles have been modelled by approximating the particle size distribution by a lognormal function throughout the process and the moments of the particle size distribution have been used to solve the general dynamic equation. The size distributions of spherical particles in the radial and axial direction have been obtained including the effect of buoyancy. Of particular interests are the variations of geometric mean diameter, number concentration and polydispersity. Results show that buoyancy significantly alters the size distribution in both axial and radial direction. One dimensional analysis for non-spherical particles has also been done and the results have been compared with the existing experimental data.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1860-1868
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• 1998

A simple postprocessing algorithm is proposed to reduce the blocky artifacts of Block Discrete Cosine Transform (BDCT) coded images. Since the block noise is mostly antisymmetric relative to the block boundaries, we model the blocky noise as one-dimensional antisymmertric functions made by superposing DCT basis functions. observing the frequency characteristics of the noies model, we approximate its high frequency components as those of step functions. Then the proposed postprocessing algorithm eliminates the carefully selected high frequency components of step functions in the one-dimensional sN-point DCT domain, when the encoding block size is $N\;{\times}\;N$. It is shown that the proposed algorithm can also be performed in the spatial domain without computational burden of transforms. The experimental results show that the proposed algorithm well reduces the blocky artifacts in both subjective and objectie viewpoints.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.4
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• pp.53-66
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• 1990

Rainfall is a phenomenon that shows a high variability both in space and time, Hy drologists are usually interested in the description of spatial distribution of rainfall over watershed. The theory of Kriging, generalized covariance technique using nonstationary mean in the regions under orographic effect, was chosen to construct random surface of total storm depth. For the constructed random surface, the double Fourier analysis of the total storm depths was performed, and the principal harmonics of storm were determined. The local component, or storm residuals was obtained by subtracting the periodic component of the storm from total storm depths. It is assumed that the residuals are a sample function of a homogeneous random field. This random field can be characterized by an isotropic one dimensional autocorrelation function or its corresponding spectral density function. Under this assumption, this study proposed a theorectical model for spectral density function adapted to two watersheds.

• Journal of Electrical Engineering and Technology
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• v.1 no.2
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• pp.233-236
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• 2006

A 3-D numerical simulation of a buried-channel CCD (Charge Coupled Device) with a deep depletion has been performed to investigate its electrical and physical behaviors. Results are presented for a deep depletion CCD (EEV CCD12; JET-X CCD) fabricated on a high-resistivity $(1.5k\Omega-cm)\;65{\mu}m$ thick epi-layer, on a $550{\mu}m$ thick p+ substrate, which is optimized for X-ray detection. Accurate predictions of the Potential minimum and barrier height of a CCD Pixel as a function of mobile electrons are found to give good charge transfer. The depletion depth approximation as a function of gate and substrate bias voltage provided average errors of less than 6%, compared with the results estimated from X-ray detection efficiency measurements. The result obtained from the transient simulation of signal charge movement is also presented based on 3-Dimensional analysis.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.2
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• pp.144-154
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• 1998

A functionally graded material is a nonhomogeneous material, which is composed of several different materials to maintain structural rigidity and endure high temperature loads. An analytical method is presenter to solve the unsteady heat conduction equation for nonhomogeneous materials. A one-dimensional infinite plate made of functionally graded material is considered. The approximate Green's function solution is derived and to be used to obtain the temperature distribution them the stress distributions may be obtained. The volume fraction, the porosity, the stress difference, and the stress ratio are the design parameters and are to be used to set up a systematic design procedure.