• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.23-30
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• 2017

Since shape, size and distribution of particles in particulate composites have spreaded characteristics, properties of particulate composites have variation and also system behavior using particulate composites have variation. However, it is difficult to consider spreaded characteristic of particles so that a system behavior is analysed using homogeneous techniques or using microstructure in local areas. In this study, for considering random variation of particles, RMDFs(random morphology description functions) are used to generate random microstructure and relationship between the number of gaussian functions and spreaded characteristic of particles was analysed using the geometrical moment of area. Also, multi-scale analysis was carried out for cantilever beam with full-random microstructure to study behavior of particulate composites structure. As a result, it is defined that spreaded characteristic of particles and the variation of deflections of cantilever beam are decreased as the number of Gaussian functions(N) is increased and converges at N=200.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.279-284
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• 2010

The plane curve approach which was proposed by Boukharouba et. al. is a multi-threshold selection method through searching peak-valley based on histogram cumulative distribution function. However the method is required to select parameters to compose plane curve, and the shape of plane curve is affected according to parameters. Therefore detection of peak-valley is effected by parameters. In this paper, we propose an entropy maximizing-based method to select optimal plane curve parameters, and propose a multi-thresholding method based on the selected parameters. The effectiveness of the proposed method is demonstrated by multi-thresholding experiments on various images and comparison with other conventional thresholding methods based on histogram.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.885-890
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• 2014

This paper has presented the change of subthreshold swings for gate oxide thickness of asymmetric double gate(DG) MOSFET, and solved Poisson equation to obtain the analytical solution of potential distribution. The Gaussian function as doping distribution is used to approch experimental results. The symmetric DGMOSFET is three terminal device. Meanwhile the asymmetric DGMOSFET is four terminal device and can separately determine the bias voltage and oxide thickness for top and bottom gates. As a result to observe the subthreshold swings for the change of top and bottom gate oxide thickness, we know the subthreshold swings are greatly changed for gate oxide thickness. Especially we know the subthreshold swings are increasing with the increase of top and bottom gate oxide thickness, and top gate oxide thickness greatly influences subthreshold swings.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.867-873
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• 2018

Recently, interests in the field of image processing have increased with the increased demand for digital imaging devices. However, digital images are damaged by the noise generated by various causes during image processing. Generally in digital imaging devices, noise such as AWGN, etc. is generated and performance and reliability are deteriorated, and various researches are in progress to remove it. Accordingly in the present paper, an algorithm to protect the high frequency components of the images and to efficiently remove AWGN is proposed. The proposed algorithm calculates the final output by adjusting estimate values applied with Gaussian mask and weight values applied according to the local mask distribution. And for performance evaluation of the proposed algorithm, simulations were performed with the existing methods, and the characteristics were compared through PSNR and the processed, enlarged images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.965-974
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• 2007

In this paper, we proposed the feature selection algorithm for multi-class genre classification. In our proposed algorithm, we developed GMM separation score based on Gaussian mixture model for measuring separability between two genres. Additionally, we improved feature subset selection algorithm based on sequential forward selection for multi-class genre classification. Instead of setting criterion as entire genre separability measures, we set criterion as worst genre separability measure for each sequential selection step. In order to assess the performance proposed algorithm, we extracted various features which represent characteristics such as timbre, rhythm, pitch and so on. Then, we investigate classification performance by GMM classifier and k-NN classifier for selected features using conventional algorithm and proposed algorithm. Proposed algorithm showed improved performance in classification accuracy up to 10 percent for classification experiments of low dimension feature vector especially.

• Journal of Korean Ophthalmic Optics Society
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• v.7 no.1
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• pp.51-55
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• 2002

This study was to investigate the effect of EEG wave type of visual cortex on conjugate movement of eyeball according to movement of visual target. Visual evoked potential(VEP) system used the Bio-Pag(production in USA) and recorded to 586 computer. The illumination of test room was 50lux and the visual target was red light dot of 3cm size. The results of dextroversion and levoversion as follows : The visual stimulation waves on the visual cortex have about 71% of delta wave, about 12% of beta wave, about 9% theta wave and about 6% of alpha wave respectively. The dextroversion and levoversion state was similar results on the histogram amplitude of EEG wave, frequency of EEG wave type, EEG wave style and phase diagram of amplitude. Expecially the histogram amplitude of EEG wave appeared almost the Gaussian shape and the phase analysis of amplitude of EEG wave was nearly linear shape. On the fast fourier transform of the amplitude and Hz, the frequency was almost low frequency under 20 Hz, and the dextroversion and levoversion shape was similar results.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.35-35
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• 2011

반도체 공정 및 디스플레이 공정에서 발생하는 오염입자는 공정 불량을 일으키는 가장 큰 원인 중의 하나이며, 수십 나노에서 수 백 나노의 크기를 갖는다. 최근 디스플레이 및 반도체 산업이 발전함에 따라 회로의 선폭이 점차 감소하고 있으며 오염입자의 임계 직경(critical diameter) 또한 작아지고 있다. 현재 반도체 및 디스플레이 산업에서 사용되는 측정방법은 레이저를 이용하여 공정 후 표면에 남아있는 오염입자를 측정하는 ex-situ 방법이 주를 이루고 있다. Ex-situ 방법을 이용한 오염입자의 제어는 웨이퍼 전체를 측정할 수 없을 뿐만 아니라 실시간 측정이 불가능하기 때문에 공정 모니터링 장비로 사용이 어려우며 오염입자와 공정 간의 상관관계 파악에도 많은 제약이 따르게 된다. 이에 따라 저압에서 in-situ 방법을 이용한 실시간 오염입자 측정 기술 개발이 요구되고 있다. 본 연구에서는 저압 환경에서 실시간으로 입자를 모니터링 할 수 있는 장비를 입자의 광 산란 원리를 이용하여 개발하였으며, 산란 신호를 입자크기로 변환하는 신호 분석 알고리즘 연구를 수행하였다. 빛이 입자와 충돌하게 되면 산란 및 흡수 현상이 발생하게 되는데 이 때 발생하는 산란 및 흡수량과 입자 크기와의 연관성이 Gustav Mie에 의해서 밝혀졌으며, 현재까지 광을 이용한 입자 크기 분석 장치의 기본 원리로 사용되고 있다. 하지만, Mie 이론은 단일입자가 일정한 강도를 가진 광을 통과할 경우인 이상적인 조건에서 적용이 가능하고 실제 조건에서는 광이 가우시안 분포를 가지며 광 집속에 의해서 광 강도가 위치에 따라 변하기 때문에 이러한 조건을 가지는 광을 입자가 통과할 때 발생하는 산란량은 단순히 Mie 이론에 의해서 계산하는 것이 불가능 하다. 본 연구에서는 이러한 현상을 입자 측정의 불확정성 이라고 규정하고 입자가 특정한 위치를 통과할 확률을 이용하여 신호를 분석하는 알고리즘을 개발 및 연구를 수행하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.704-707
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• 2013

This paper has analyzed the subthreshold swings for top and bottom gate voltages of asymmetric double gate(DG) MOSFET. The asymmetric DGMOSFET is four terminal device to be able to separately bias for top and bottom gates. The subthreshold swing, therefore, has to be analyze not only for top gate voltage, but also for bottom gate voltage. In the pursuit of this purpose, Poisson equation has been solved to obtain the analytical solution of potential distribution with Gaussian function, and the subthreshold swing model has been presented. As a result to observe the subthreshold swings for the change of top and bottom gate voltage using this subthreshold swing model, we know the subthreshold swings are greatly changed for gate voltages. Especially we know the conduction path has been changed for top and bottom gate voltage and this is expected to greatly influence on subthreshold swings.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.16-23
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• 2007

Changeable biometrics has been developed as a solution to problem of enhancing security and privacy. The idea is to transform a biometric signal or feature into a new one for the purposes of enrollment and matching. In this paper, we propose a changeable biometric system that can be applied to appearance based face recognition system. In the first step when using feature extraction, ICA(Independent Component Analysis) coefficient vectors extracted from an input face image are replaced randomly using their mean and variation. The transformed vectors by replacement are scrambled randomly and a new transformed face coefficient vector (transformed template) is generated by combination of the two transformed vectors. When this transformed template is compromised, it is replaced with new random numbers and a new scrambling rule. Because e transformed template is generated by e addition of two vectors, e original ICA coefficients could not be easily recovered from the transformed coefficients.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.12-18
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• 2011

In this paper, we proposed Interval Type-2 polynomial Radial Basis Function Neural Networks. In the receptive filed of hidden layer, Interval Type-2 fuzzy set is used. The characteristic of Interval Type-2 fuzzy set has Footprint Of Uncertainly(FOU), which denotes a certain level of robustness in the presence of un-known information when compared with the type-1 fuzzy set. In order to improve the performance of proposed model, we used the linear polynomial function as connection weight of network. The parameters such as center values of receptive field, constant deviation, and connection weight between hidden layer and output layer are optimized by Conjugate Gradient Method(CGM) and Space Search Evolutionary Algorithm(SSEA). The proposed model is applied to gas furnace dataset and its result are compared with those reported in the previous studies.