• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.2
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• pp.115-124
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• 2001

In this paper, authors propose a new nonlinear rotor flux observer for rotor field oriented control of an induction motor which is designed based on the extended Luenberger Observer theory. Extended Luenberger Observer requires minimal solution of nonlinear partial differential equation on its coordinate transformation and linearization needed on a nonlinear observer design in general. The proposed rotor flux observer is derived from the 2 phase model of induction motor on the orthogonal coordination and it has the reduce gain matrix. Simulation and experimentation were performed under the conventional indirect vector control and direct vector control with the proposed observer at different rotor resistance. Simulation results show that the convergence of the proposed observer is influenced by the chosen eigenvalues. Experimentation results on load operation show the direct vector control with the proposed observer is better than the indirect vector control to maintain the characteristics of the vector control.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.445-449
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• 2009

In this paper, we propose a computationally efficient multi GPU accelerated image registration technique to correct the motion difference between the pre-contrast CT image and post-contrast CTA image. Our method consists of two steps: multi GPU based image registration and a cerebrovascular visualization. At first, it computes a similarity measure considering the parallelism between both GPUs as well as the parallelism inside GPU for performing the voxel-based registration. Then, it subtracts a CT image transformed by optimal transformation matrix from CTA image, and visualizes the subtracted volume using GPU based volume rendering technique. In this paper, we compare our proposed method with existing methods using 5 pairs of pre-contrast brain CT image and post-contrast brain CTA image in order to prove the superiority of our method in regard to visual quality and computational time. Experimental results show that our method well visualizes a brain vessel, so it well diagnose a vessel disease. Our multi GPU based approach is 11.6 times faster than CPU based approach and 1.4 times faster than single GPU based approach for total processing.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.242-249
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• 2011

In this paper, the correspondence matching method of stereo images was proposed by means of sampling projective transformation matrix in planar region of scene. Though this study is based on RANSAC, it does not use uniform distribution by random sampling in RANSAC, but use multi non-uniform computed from difference in positions of feature point of image or templates matching. The existing matching method sampled that the correspondence is presumed to correct by use of the condition which the correct correspondence is almost satisfying, and applied RANSAC by matching the correspondence into one to one, but by sampling in stages in multi probability distribution computed for image in the proposed method, the correct correspondence of high probability can be sampled among multi correspondence candidates effectively. In the result, we could obtain many correct correspondence and verify effectiveness of the proposed method in the simulation and experiment of real images.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.297-303
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• 2009

In this paper, we propose the biomedical spectral pattern classification techniques by the fusion scheme based on the SpPCA and MLP in extended feature space. A conventional PCA technique for the dimension reduction has the problem that it can't find an optimal transformation matrix if the property of input data is nonlinear. To overcome this drawback, we extract features by the SpPCA technique in extended space which use the local patterns rather than whole patterns. In the classification step, individual classifier based on MLP calculates the similarity of each class for local features. Finally, biomedical spectral patterns is classified by the fusion scheme to effectively combine the individual information. As the simulation results to verify the effectiveness, the proposed method showed more improved classification results than conventional methods.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.E4
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• pp.203-213
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• 2002

Receptor modeling is one of statistical methods to achieve reasonable air pollution strategies. In order to maintain and manage ambient air quality, it is necessary to identify sources and to apportion its sources for ambient particulate matters. The main purpose of the study was to survey seasonal trends of inorganic elements in the coarse and fine particles. Second, this study has attempted emission sources qualitatively by a receptor method, the PMF mo-del. After that. both PMF (positive matrix factorization) model and TTFA (target transformation factor analysis) model were applied to compare and to estimate mass contribution of coarse and fine particle sources at the receptor. A total of 138 sets of samples was collected from 1989 to 1996 by a low volume cascade impactor with 9 size fraction stages at Kyung Hee University in Korea. Sixteen chemical species (Si, Ca, Fe, K, Pb, Na, Zn, Mg, Ba, Ni, V, Mn, Cr, Br, Cu. Co) were characterized by XRF. The study result showed that the weighted arithmetic mean of coarse and fine particles were 51.3 and 54.4 $\mu\textrm{g}$/㎥, respectively. Contribution of both particle fractions were esti-mated using TTFA and PMF models. The number of estimated sources was seven according to TTFA model and 8 according to PMF model. Comparison of TTFA and PMF revealed that both methodologies exhibited similar trends in their contribution pattern. However, large differences between contributions were observed in some sour-ces. The results of this study may help to suggest control strategies in local countries where known source profiles do not exist.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.1015-1025
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• 2017

Bayesian personalized ranking (BPR) is a state-of-the-art recommendation system techniques for implicit feedback data. Unfortunately, there might be a loss of information because the BPR model considers only the binary transformation of implicit feedback that is non-binary data in most cases. We propose a modified BPR method using a level of confidence based on the size or strength of implicit feedback to overcome this limitation. The proposed method is useful because it still has a structure of interpretable models for underlying personalized ranking i.e., personal pairwise preferences as in the BPR and that it is capable to reflect a numerical size or the strength of implicit feedback. We propose a computation algorithm based on stochastic gradient descent for the numerical implementation of our proposal. Furthermore, we also show the usefulness of our proposed method compared to ordinary BPR via an analysis of steam video games data.

• Journal of the Korean Society for Heat Treatment
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• v.7 no.1
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• pp.44-52
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• 1994

In order to investigate the effect of tempring treatment on the mechanical properties of ausformed martensite in Fe-30%Ni-0.35%C alloy, the hardness, yield strength and elongation were examined by tensile test. 1. The strength of deformed austenite in Fe-30%Ni-0.35%C alloy was increased due to the work hardening induced from the dislocation density increased during deformation. The strength of ausformed martensite was increased because of defects inherited from deformed austenite by martensitic transformation. 2. The ductility of ausformed martensite was shown a nearly constant values independent of deformation degrees because of the interaction of multiple factors such as increased retained austenite, formation of void and decrement of twin in ausformed martensite. 3. The strength of ausformed martensite by tempering treatment was shown a little decrement up to $340^{\circ}C$, especially showed remarkable softening resistance in higher deformation degrees. 4. Virgin martensite and ausformed martensite were shown a maximum yield strength by clustering in tempering at $100^{\circ}C$ and above $100^{\circ}C$, yield strength was very small decreased due to the decrement of solute carbon by the destruction of clustering. 5. The decomposition of retained austenite was not shown up to $450^{\circ}C$ in ausformed martensite with tempering treatment, and the matrix was rapidly softening because of the decomposition of martensite and the formation of reversed austenite with tempering above $400^{\circ}C$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5385-5391
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• 2013

As on-line purchases is activated, customers' demand increases for the realistic and accurate digital information of a product design. In this paper, we propose a practical method that can generate a realistic 3D model of a real product using a 3D geometry obtained by a 3D scanner and its photographic images. In order to register images to the 3D geometry, the camera focal length, the CCD scanning aspect ratio and the transformation matrix between the camera coordinate and the 3D object coordinate must be determined. To perform this 2D-3D registration with consideration of computational complexity, a three-step method is applied, which consists of camera calibration, determination of a temporary optimum translation vector (TOTV) and nonlinear optimization for three rotational angles. A case study for a metallic coated industrial part, of which the colour appearance is hardly obtained by a 3D colour scanner has performed to demonstrate the effectiveness of the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.399-408
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• 2015

This paper presented airquality data through data visualization in several ways and described its characteristics related to statistical methods for analysis. Software R was used for visualization tools. The airquality data was measured in New York city from May to September of year 1973. First, simple, exploratory data analysis was done in terms of both data visualization and analysis to find out univariate characteristics. Then through data transformation and multiple regression analysis, model for describing the airquality level was found. Also, after some data categorization, overall feature of the data was explored using box plot and three-dimensional perspective drawing and scatter plot.

• Journal of the Korean Ceramic Society
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• v.36 no.12
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• pp.1356-1363
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• 1999

Self-reinforced silicon carbide was prepared by hot pressing and the control of starting phases of raw materials and its microstructural characteristics was investigated. The specimens with self-reinforced microstructure were obtained from the compacts with mixed compositions of ${\alpha}$-and ${\beta}$-SiC powders. Self-reinforced microstructure which is composed of large dispersed grains with rod-like shape and matrix with small equiaxed grains was formed by the transformation to the ${\alpha}$-SiC with 4H polytype for ${\beta}$-SiC and anisotropic grain growth during the heat treatment. Of all speimens the values of volume fraction maximum length and aspect ratio for large grains with rode-like types were the highest at the specimen with 50 vol% ${\beta}$-SiC in the starting SiC powder and therefore this specimen showed the highest fracture toughness due to the crack deflection by rod-like grains during crack propagation.