• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.299-302
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of$.$10 persons show that the proposed method yields high recognition rates.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.2
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• pp.12-18
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• 2005

A geometric compensation of thin-walled molded parts in reverse engineering is presented. Researches in reverse engineering have focused on the fitting of points to curves and surfaces. However, the reconstructed model is not the geometric model because the molded parts have some dimensional errors in measurements and deformation during molding. Geometric information can give an improved accuracy in reverse engineering. Thus, measurement data must be compensated with geometric information to reconstruct the mathematical model. The functional and geometric concepts of the part can be derived from geometric information. LSM (Least square method) is adopted to determine the geometric information. Also, an example of geometric compensation is given to improve the accuracy of geometric model and to inspect the reconstructed model.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.822-826
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of 10 persons show that the proposed method yields high recognition rates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3983-4001
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• 2015

Exact average bit error probability (BEP) expressions for mobile-relay-based mobile-to-mobile (M2M) cooperative networks with incremental decode-and-forward (IDF) relaying over N-Nakagami fading channels are derived in this paper. The average BEP performance under different conditions is evaluated numerically to confirm the accuracy of the analysis. Results are presented which show that the fading coefficient, the number of cascaded components, the relative geometrical gain, and the power allocation parameter have a significant influence on the average BEP performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.53-54
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• 2014

By using geometrical structure of Fresnel lens, it can be applied with receiver antenna and geodetic system. In this paper, radiation pattern from fresnel lens array of Soret type is calculate by the FDTD method. For simplicity, fresnel lens should be located linearly and considered to be dielectric rod with a relative permittivity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.43-44
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• 2014

By using geometrical structure of Fresnel lens, it can be applied with receiver antenna and geodetic system. In this paper, we consider Soret typed fresnel lens with reflected plate and its focusing gain characteristics is calculated by the FDTD method.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.187-197
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• 2008

While driving a highway, A driver gets lots of information through geometrical structure, traffic situation, signs on the road. He gets most of the information by visual sense. Acceleration or deceleration and driving direction depend on sight distance. Therefore, it's essential to secure a driver's sight distance for a safe drive. However, design guides of geometrical structure and sight distance suggest respective standards of horizontal and vertical alignment. They do not indicate quantitative standard of combined alignment. Currently, element separated on a two-dimensional projected plane are available, but they do not guarantee safe and pleasant design. I will use the existent model analysing three-dimensional sight distance through mathematical calculation and sort a variety of geometrical structure element and type. In these researches, we will look at how much three-dimensional sight distance is overestimated or underestimated compared to two-dimensional. I will develop a program which predicts traffic velocity on the curvature of two-lane provincial road. stopped sight distance and three-dimensional sight distance will be compared at a predicted drive velocity. I will suggest the way to evaluate road consistency.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.155-166
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• 2019

Road infrastructure has increased explosively due to economic development after industrialization and at present road infrastructure is being changed and increased by construction of new roads and maintenance and expansion of existing roads. Such road infrastructure should support safe driving. Road management plays an important role in safe driving. The purpose of this dissertation is to verify predictability of dangerous sections by analyzing road geometrical structure such as surface irregularity and superelevation for some sections in Central Inland Expressway by MMS and present ways of managing roads using MMS. Having analyzed surface irregularity of roads by using MMS, it was found that over 50 percent of all eight sections, targets of this study need betterments and for superelevation, over 50 percent of two sections goes against superelevation standard. Targets of this study are sections that accidents occurred frequently based on history of past accidents and predictability of dangerous sections can be verified through analysis of road geometrical structure using MMS. Using MMS data created by construction of high definition maps which are being undergone for all roads and methods proposed by this study will help investigate dangerous sections efficiently according to road environment. A result of MMS can be used for maintenance of road furniture.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.155-163
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• 2012

The geometrical and electrical errors of array sensors can severely degrade the performance of array sensor system. Various calibration techniques are developed to alleviate this problem. In this paper, two different calibration methods with respect to location, gain and phase of array sensors are presented. One method applies the first-order Taylor series expansion to approximate the true steering vector from the nominal values of array sensors. Then a set of equations is formed by using the null characteristics of the MUSIC spectrum to estimate errors of location, gain and phase of array sensors. Another method estimates these errors based on the data covariance matrix of pilot sources. From the simulations, it is demonstrated that two calibration algorithms calibrated an array system successfully. In addition to that, Fistas and Manikas's algorithm is more robust against noise than Ng and Lie's one when SNR is from 10dB to 50dB.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.85-96
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• 2001

This paper discusses the problem of finding the Origin-Destination(O-D) shortest path in urban road networks that have variable special qualifies such as time windows for passing as well as geometrical special qualities such as U-turn and left-turn prohibition. The focus of this paper is motivated by the problem of finding minimum travel time paths for an advanced traveler information system (ATIS) in the context of intelligent transportation system(ITS) application. The transportation network with variable and geometrical special qualities is a more realistic representation of the urban road network in the real word. But, the traditional and existing shortest path algorithms can not search practical shortest path that variable special quality is reflected. This paper presents a shortest path algorithm which can search reasonable shortest path information for the urban ATIS application within a real time. The algorithm is based on genetic algorithm(GA). The high performance of the proposed algorithm is demonstrated by computer simulations.