• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1996년도 가을 학술발표회 논문집
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• pp.202-209
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• 1996

In this paper, two dimensional vertical and comer infinite elements which can include multiple wave components to model underlying half space are developed. These elements are natural and economical to model underlying stiff half space or rock. To verify the behavior of these infinite elements, vertical, horizontal, and rocking compliances of a rigid strip foundation on a viscoelastic soil profile are analyzed and compared with those of Tzong and Penzien who used the boundary solution method. Good agreements are noticed between the two methods. The influence of material properties like Poisson's ratio, material damping, and stiffness ratio of layers as well as the influence of geometrical properties such as layer thicknesses and depth of foundation embedment are studied. Example analysis is carried out for the shaking table which is located in KIMM(Korea Institute of Machinery and Materials), and the vertical and horizontal displacements of the analysis are compared with the measured, and show good results and demonstrate the efficiency of the proposed method.

• 한국지능시스템학회논문지
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• 제8권5호
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• pp.39-44
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• 1998

이동 로봇의 운행을 위해서 이동 로봇의 절대 위치를 결정하는 것이 중요하다. 본 논문에서는 신경회로망을 이용하여 랜드마크의 영상을 통해 이동 로봇의 위치를 결정하는 방법을 제안한다. 픽셀의 불확시한 값, 부정확한 카메라 조정과 렌즈의 왜곡으로 인해 이동 로봇의 위치를 결정에 있어서 위치 오차가 생기게 된다. 이러한 오차를 줄이기 위해서 BPNN(Back Propagation Neural Network)를 사용하는 방법을 제안한다. 기존의 방법과 비교하여 우수성을 보여주기 위해서 실험결과를 보여준다.

• International Journal of Aeronautical and Space Sciences
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• 제8권1호
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• pp.122-128
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• 2007

In this paper, a method of station keeping strategy using relative orbital motion and numerical optimization technique is presented for geostationary satellite. Relative position vector with respect to an ideal geostationary orbit is generated using high precision orbit propagation, and compressed in terms of polynomial and trigonometric function. Then, this relative orbit model is combined with optimization scheme to propose a very efficient and flexible method of station keeping planning. Proper selection of objective and constraint functions for optimization can yield a variety of station keeping methods improved over the classical ones. Nonlinear simulation results have been shown to support such concept.

• 한국정밀공학회지
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• 제15권4호
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• pp.105-110
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• 1998

In this study, statistical and neural network methods were used to recognize the cutting tool states. This system employed the tool dynamometer and cutting force signals which are processed from the tool dynamometer sensor using linear discriminent function. To learn the necessary input/output mapping for turning operation diagnosis, the weights and thresholds of the neural network were adjusted according to the error back propagation method during off-line training. The cutting conditions, cutting force ratios and statistical values(standard deviation, coefficient of variation) attained from the cutting force signals were used as the inputs to the neural network. Through the suggested neural network a cutting tool states may be successfully diagnosed.

• 센서학회지
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• 제23권1호
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• pp.1-6
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• 2014

In many medical image devices, dc noise often prevents normal diagnosis. In wireless capsule endoscopy systems, multipath fading through indoor wireless links induces inter-symbol interference (ISI) and indoor electric devices generate impulsive noise in the received signal. Moreover, dc noise, ISI, and impulsive noise are also found in optical fiber communication that can be used in remote medical diagnosis. In this paper, a blind signal processing method based on the biased probability density functions of constant modulus error that is robust to those problems that can cause error propagation in decision feedback (DF) methods is presented. Based on this property of robustness to error propagation, a DF version of the method is proposed. In the simulation for the impulse response of optical fiber channels having slowly varying dc noise and impulsive noise, the proposed DF method yields a performance enhancement of approximately 10 dB in mean squared error over its linear counterpart.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.148-153
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• 2009

Few methods have dealt with segmenting multiple images with analogous content. Concurrent images of a scene and gathered images of a similar foreground are examples of these images, which we term consistent scene images. In this paper, we present a method to segment these images based on manual segmentation of one image, by iteratively propagating information via multi-level cues with adaptive confidence. The cues are classified as low-, mid-, and high- levels based on whether they pertain to pixels, patches, and shapes. Propagated cues are used to compute potentials in an MRF framework, and segmentation is done by energy minimization. Through this process, the proposed method attempts to maximize the amount of extracted information and maximize the consistency of segmentation. We demonstrate the effectiveness of the proposed method on several sets of consistent scene images and provide a comparison with results based only on mid-level cues [1].

• 한국경영과학회지
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• 제30권1호
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• pp.55-74
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• 2005

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2002년도 제25회 KOSCI SYMPOSIUM 논문집
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• pp.231-235
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• 2002

A theoretical and experimental study on the combustion process in a constant volume micro combustor is described. Unlike in a macro scale constant volume combustor, the heat loss to the wall plays a major role in flame propagation in a micro micro combustor. In order to analyze the effect of heat loss on combustion phenomena, pressure transition from ignition was measured. A number of cylindrical micro combustors with different diameter and depth were used for experiment to study the effect of length scales and shape factor. The diameter of combustor ranged from 7.5mm to 22.5 mm and the height of cylinder was from 1mm to 4mm. Initial pressure was also varied for the experiment. The diagnostic methods were severely limited due to the size of the apparatus and uncertainties of certain quantities to be measured in a small-scale environment. An analytical method to derive physical quantities that are essential for performance prediction from the pressure measurements is described.

• 한국통신학회논문지
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• 제33권12A호
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• pp.1177-1184
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• 2008

Non-line-of-sight (NLOS) propagation can severely weaken the accuracy of ranging and localization in wireless location systems. NLOS bias mitigation techniques have recently been proposed to relieve the NLOS effects, but positively rely on the capability to accurately distinguish between LOS and NLOS propagation scenarios. This paper proposes an energy-capture-based NLOS identification method for LDR-UWB systems, based on the analysis of the characteristics of the channel impulse response (CIR). With this proposed energy capture method, the probability of successfully identifying NLOS is much improved than the existing methods, such as the kurtosis method, the strongest path compare method, etc. This NLOS identification method can be employed in adaptive modulation scheme to decrease bit error ratio (BER) level for certain signal-to-noise ratio (SNR). The BER performance with the adaptive modulation can be significantly enhanced by selecting proper modulation method with the knowledge of channel information from the proposed NLOS identification method.

• KIEE International Transactions on Electrophysics and Applications
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• 제3C권5호
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• pp.199-206
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• 2003

Numerical solutions to complex characteristic equations are quite often required to solve electromagnetic wave problems. In general, two traditional complex root search algorithms, the Newton-Raphson method and the Muller method, are used to produce such solutions. However, when utilizing these two methods, the choice of the initial iteration value is very sensitive, otherwise, the iteration can fail to converge into a solution. Thus, as an alternative approach, where the selection of the initial iteration value is more relaxed and the computation speed is high, Davidenko's method is used to determine accurate complex propagation constants for leaky circular symmetric modes in circular dielectric rod waveguides. Based on a precise determination of the complex propagation constants, the leaky mode characteristics of several lower-order circular symmetric modes are then numerically analyzed. In addition, no modification of the characteristic equation is required for the application of Davidenko's method.