• Journal of the Korean Geophysical Society
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• v.9 no.2
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• pp.99-103
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• 2006

3D object recognition independent of translation and rotation using an ultrasonic sensor array, invariant moment vectors and SOFM(Self Organizing Feature Map) neural networks is presented. Using invariant moment vectors of the acquired 16×8 pixel data of square, rectangular, cylindric and regular triangular blocks, 3D objects could be classified by SOFM neural networks. Invariant moment vectors are constant independent of translation and rotation. The recognition rates for the training and testing data were 95.91% and 92.13%, respectively.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.7
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• pp.745-752
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• 2012

The pivot steering of an individual wheel motor drive vehicle is an effective steering maneuver in the narrow road, but it has become a matter of concern that the torque input of each wheel is very difficult to determine. In this study, the independent yaw moment control was proposed for the smooth pivot steering control of an in-wheel drive vehicle. For this control method, the vertical forces of tires were estimated from the trailing arm dynamic model, and the yaw moments of individual wheels were calculated from the vehicle dynamic model. Dynamic simulation results showed that the independent yaw moment control was much more effective on the minimization of the instabilities of pivot steering in comparison with the conventional direct yaw moment control with yaw rate feedback.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.45-55
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• 2013

With the recent advancement of control method and battery technology, the electric vehicle have been researched to replace the conventional vehicle with electric vehicle with the view point of the environmental concerns and energy conservation. An electric vehicle which is equipped with the independent front steering system and in-wheel motors has advantage in terms of control. For example, the different torque which generated by left and right wheels directly can make yaw moment and the independent steering using outer wheel control is able to reduce the sideslip angle. Using of independent steering and driving system, the 4 wheel electric vehicle can improve a performance better than conventional vehicle. In this paper, we consider the method for improving the cornering performance of independent front steering system and in-wheel motor used electric vehicle with the compensated outer wheel angle and direct yaw moment control. Simulation results show that the method can improve the cornering performance of 4 wheel electric vehicle. We also apply the steering motor failure to steer the vehicle turned by the torque difference without steering. This paper describes an independent front steering and driving, consist of three parts; Vehicle Model, Control Algorithm for independent steering and driving and simulation. First, vehicle model is application of TruckSim software for independent front steering and 4 wheel driving. Second, control algorithm describes the reduced sideslip and direct yaw moment method in view of cornering performance. Last is simulation and verification.

• Journal of the Korean Society of Industry Convergence
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• v.9 no.4
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• pp.263-268
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• 2006

This paper presents a real-time verification system by extracting a features of multimodal biometrics using hybrid method, which is combined the moment balance and the independent component analysis(ICA). The moment balance is applied to reduce the computation loads by extracting the validity signal due to exclude the needless backgrounds of multimodal biometrics. ICA is also applied to increase the verification performance by removing the overlapping signals due to extract the statistically independent basis of signals. Multimodal biometrics are used both the faces and the fingerprints which are acquired by Web camera and acquisition device, respectively. The proposed system has been applied to the fusion problems of 48 faces and 48 fingerprints(24 persons * 2 scenes) of 320*240 pixels, respectively. The experimental results show that the proposed system has a superior verification performances(speed, rate).

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1237-1239
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• 1996

3-D object recognition and restoration independent of the translation and rotation using an ultrasonic sensor array, neural networks and invariant moment are presented. Using invariant moment vectors on the acquired $16{\times}8$ pixel data, 3-D objects can be classified by SOFM(Self Organizing Feature Map) neural networks. Invariant moment vectors kept constant independent of the translation and rotation. The experiment result shows the suggested method can be applied to the environment recognition.

• Journal of the Korean Society of Industry Convergence
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• v.6 no.1
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• pp.23-29
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• 2003

This paper proposes an efficient feature extraction of the images by using independent component analysis(ICA) based on neural networks of the hybrid learning algorithm. The proposed learning algorithm is the fixed point(FP) algorithm based on Newton method and moment. The Newton method, which uses to the tangent line for estimating the root of function, is applied for fast updating the inverse mixing matrix. The moment is also applied for getting the better speed-up by restraining an oscillation due to compute the tangent line. The proposed algorithm has been applied to the 10,000 image patches of $12{\times}12$-pixel that are extracted from 13 natural images. The 144 features of $12{\times}12$-pixel and the 160 features of $16{\times}16$-pixel have been extracted from all patches, respectively. The simulation results show that the extracted features have a localized characteristics being included in the images in space, as well as in frequency and orientation. And the proposed algorithm has better performances of the learning speed than those using the conventional FP algorithm based on Newton method.

• Earthquakes and Structures
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• v.22 no.2
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• pp.157-168
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• 2022

A moment-independent importance measure analysis approach was introduced to quantify the effects of structural uncertainty parameters on probabilistic seismic demands of simply supported girder bridges. Based on the probability distributions of main uncertainty parameters in bridges, conditional and unconditional bridge samples were constructed with Monte-Carlo sampling and analyzed in the OpenSees platform with a series of real seismic ground motion records. Conditional and unconditional probability density functions were developed using kernel density estimation with the results of nonlinear time history analysis of the bridge samples. Moment-independent importance measures of these uncertainty parameters were derived by numerical integrations with the conditional and unconditional probability density functions, and the uncertainty parameters were ranked in descending order of their importance. Different from Tornado diagram approach, the impacts of uncertainty parameters on the whole probability distributions of bridge seismic demands and the interactions of uncertainty parameters were considered simultaneously in the importance measure analysis approach. Results show that the interaction of uncertainty parameters had significant impacts on the seismic demand of components, and in some cases, it changed the most significant parameters for piers, bearings and abutments.

• Bulletin of the Korean Mathematical Society
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• v.35 no.4
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• pp.769-775
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• 1998

In this paper, we obtain an analogue of law of the iterated logarithm for an array of independent, but not necessarily idetically distributed, random variables under some moment conditions of the array.

• Journal of the Korean Mathematical Society
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• v.53 no.6
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• pp.1275-1292
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• 2016

The Marcinkiewicz-Zygmund strong law of large numbers for conditionally independent and conditionally identically distributed random variables is an existing, but merely qualitative result. In this paper, for the more general cases where the conditional order of moment belongs to (0, ${\infty}$) instead of (0, 2), we derive results on convergence rates which are quantitative ones in the sense that they tell us how fast convergence is obtained. Furthermore, some conditional probability inequalities are of independent interest.

• Journal of Korea Foresty Energy
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• v.18 no.2
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• pp.84-91
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• 1999

The objective of this study was to present creep and the effects of mechano-sorptive deflection of drift pin moment resisting joint between LVL members under changing relative humidity (RH) conditions. The LVL members with steel gusset were jointed by a square pattern of eight injected drift pin. Three diameter drift pins were used to test specimens (6mm, 10mm, and 16mm). The creep test was conducted under two constant loading conditions : one at 30 kgf(840 kgf-cm) and the other at 60 kgf(1680 kgf-cm). The experiment was conducted in an open shed outside. (1)The total rotation creep model of moment resisting joing can be expressed as the sum of the creep of controlled environment (3-parameter model), dimensional change and mechano-sorptive deflection resulting from the variable environment. (2)Mechanosorptive rotation creep is recoverable as moisture content increases during adsorption. Least squares method for linear regression analysis was performed using mechano-sorptive rotation creep as the dependent variable and moisture content as the independent variable. The slope of low moment specimens are compared with those of high moment. This means that low moment condition is more easily affected by changes in humidity than high moment conditions. (3)Although creep deflection is higher for small diameter drift pin than for large diameter drift pin, the shape of creep deflection curves for all specimens is similar.