• Journal of Aerospace System Engineering
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• v.12 no.6
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• pp.41-49
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• 2018

In this study, the theoretical dynamic characteristics of a thin-walled composite beam with a single-cell of chordwise asymmetric cross-section was studied. Mathematical modeling was done by considering the transverse shear effects, the warping restraint effects, the constant taper ratio in the longitudinal direction of the beam, and the geometrical cross-section ratio. The mass coefficients, stiffness coefficients, and Eigen frequencies of the selected section were investigated. In particular, the effects of the taper ratio and cross-section ratio of the model on the Eigen frequencies were analyzed and compared when the asymmetry of the section was considered and the warping function was not corrected.

• Journal of the Korea Society for Simulation
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• v.27 no.4
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• pp.27-45
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• 2018

The terrestrial communication network and the underwater acoustic communication network have very different communication characteristics each other in operational environments, communication media, propagation delay, frequency bandwidth, transmission speed, bit error rate, and so on. These different characteristics cause some different address schemes and different maximum transmission units and, as a result, these differences must form certainly obstacles to the intercommunication between a terrestrial communication network and an underwater acoustic communication network. In this paper, we presents a method to use the virtual addresses to resolve the interconnection problem caused by different address schemes between a terrestrial communication network and an underwater acoustic communication network, and, through a mathematical modeling, we analyze the performance on the message transceiving delay time in the underwater environment.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.213-216
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• 2018

본 논문에서는 사람의 인지 시각 특성 중 하나인 JND(Just Noticeable Difference)를 이용한 인지 비디오 부호화 기법을 제안한다. JND 기반 인지 부호화 방법은 사람의 인지 시각 특성을 이용해 시각적으로 인지가 잘 되지 않는 인지 신호를 제거함으로 부호화 효율을 높이는 방법이다. 제안된 방법은 기존 수학적 모델 기반의 JND 기법이 아닌 최근 각광 받고 있는 데이터 중심(data-driven) 모델링 방법인 심층 신경망 기반 JND 모델 생성 기법을 제안한다. 제안된 심층 신경망 기반 JND 모델은 비디오 부호화 과정에서 입력 영상에 대한 전처리를 통해 입력 영상의 인지 중복(perceptual redundancy)를 제거하는 역할을 수행한다. 부호화 실험에서 제안된 방법은 동일하거나 유사한 인지화질을 유지한 상태에서 평균 16.86 %의 부호화 비트를 감소 시켰다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1470-1473
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• 2013

본 논문에서는 안드로이드 플랫폼에서 3D 타이포그래피를 쉽게 표현할 수 있도록 지원하는 라이브러리를 설계 구현하였다. 현재까지 모바일 플랫폼에서 3D 타이포그래피를 지원하기 위한 라이브러리는 iOS에서 사용가능한 FTGL ES만이 공개되었고 이를 직접 안드로이드 플랫폼에서 사용할 수 없으며 제공되는 3D 표현 기능 또한 제한적이었다. 본 연구에서는 iOS용 FTGL ES를 안드로이드 플랫폼에서 사용할 수 있도록 변환하고 OpenGL ES기능을 활용하여 다양한 3D 폰트 표현을 지원할 수 있는 3D 폰트 라이브러리를 개발하였다. Freetype 라이브러리를 통해 폰트의 Glyph 정보들을 얻고 이를 이용해 테두리, 양각, 음각 등 다양한 3D 문자 표현 기능을 구현하였고, 공간상에서 문자들의 배치를 수학적으로 모델링하여 다양한 3D 문자 배치 기능을 구현하였다. 개발된 3D 폰트 라이브러리를 이용하여 다양하게 문자들을 3D 공간에 표현할 수 있으면서, 기존 3D 타이포그래피 표현 방법들에 비해 더 쉽고 빠르게 3D 타이포그래피를 표현할 수 있도록 지원한다.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.17-25
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• 2010

It is necessary for the ship dynamic models to realize ship dynamics and to achieve the real-time analysis in the manoeuvring simulation. Generally, simple dynamic models, such as 1st-order differential equation models of turning angle, turning rate, and forward speed, are used in the manoeuvring simulation for multiple ships. Ship dynamic modeling and parameter estimation methods based on its turning test results are proposed in this paper. Parameter estimation methods for the constant speed model and the speed-changing model are mathematically developed and verified by comparing with turning test results of a real ship.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.11
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• pp.509-520
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• 2015

College Scholastic Ability Test(CSAT) is a primary test to evaluate the study achievement of high-school students and used by most universities for admission decision in South Korea. Because its level of difficulty is a significant issue to both students and universities, the government makes a huge effort to have a consistent difficulty level every year. However, the actual levels of difficulty have significantly fluctuated, which causes many problems with university admission. In this paper, we build two types of data-driven prediction models to predict correct answer rate and to identify significant factors for CSAT English test through accumulated test data of CSAT, unlike traditional methods depending on experts' judgments. Initially, we derive candidate question-specific factors that can influence the correct answer rate, such as the position, EBS-relation, readability, from the annual CSAT practices and CSAT for 10 years. In addition, we drive context-specific factors by employing topic modeling which identify the underlying topics over the text. Then, the correct answer rate is predicted by multiple linear regression and level of difficulty is predicted by classification tree. The experimental results show that 90% of accuracy can be achieved by the level of difficulty (difficult/easy) classification model, whereas the error rate for correct answer rate is below 16%. Points and problem category are found to be critical to predict the correct answer rate. In addition, the correct answer rate is also influenced by some of the topics discovered by topic modeling. Based on our study, it will be possible to predict the range of expected correct answer rate for both question-level and entire test-level, which will help CSAT examiners to control the level of difficulties.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.3
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• pp.68-76
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Thus, in this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm(RVEGA) was presented for stabilization of an IP system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. And the proposed ENNC was implemented successfully on the ADA-2310 data acquisition board and the 80586 microprocessor in order to stabilize the IP system. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• Geophysics and Geophysical Exploration
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• v.17 no.3
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• pp.129-136
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• 2014

Electromagnetic (EM) methods are generally divided into frequency-domain EM (FDEM) and time-domain EM (TDEM) methods, depending on the source waveform. The FDEM and TDEM fields are mathematically related by the Fourier transformation, and the TDEM field can thus be obtained as the Fourier transformation of FDEM data. For modeling in time-domain, we can use fast frequency-domain modeling codes and then convert the results to the time domain with a suitable numerical method. Thus, frequency-to-time transformations are of interest to EM methods, which is generally attained through fast Fourier transform. However, faster frequency-to-time transformation is required for the 3D inversion of TDEM data or for the processing of vast air-borne TDEM data. The diffusion expansion method (DEM) is one of smart frequency-to-time transformation methods. In DEM, the EM field is expanded into a sequence of diffusion functions with a known frequency dependence, but with unknown diffusion-times that must be chosen based on the data to be transformed. Especially, accuracy of DEM is sensitive to the diffusion-time. In this study, we developed a method to determine the optimum range of diffusion-time values, minimizing the RMS error of the frequency-domain data approximated by the diffusion expansion. We confirmed that this method produces accurate results over a wider time range for a homogeneous half-space and two-layered model.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.89-101
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• 2015

This paper proposes a statistical model of 3-D positions when tracking moving targets using the uncooled infrared (IR) stereo camera system. The proposed model is derived from two errors. One is the position error which is caused by the sampling pixels in the digital image. The other is the timing jitter which results from the irregular capture-timing in the infrared cameras. The capture-timing in the IR camera is measured using the jitter meter designed in this paper, and the observed jitters are statistically modeled as Gaussian distribution. This paper derives an integrated probability distribution by combining jitter error with pixel position error. The combined error is modeled as the convolution of two error distributions. To verify the proposed statistical position error model, this paper has some experiments in tracking moving objects with IR stereo camera. The 3-D positions of object are accurately measured by the trajectory scanner, and 3-D positions are also estimated by stereo matching from IR stereo camera system. According to the experiments, the positions of moving object are estimated within the statistically reliable range which is derived by convolution of two probability models of pixel position error and timing jitter respectively. It is expected that the proposed statistical model can be applied to estimate the uncertain 3-D positions of moving objects in the diverse fields.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.2
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• pp.181-190
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• 2007

The linkage framework of surface geometric modeling based on the NURBS and shell finite element analysis is developed in this study. In the geometrically exact shell finite element analysis, the accuracy of the analysis strongly depends upon the accurate computation of the surface geometric quantities. Therefore if we obtain the necessary geometric quantities from the NVRBS surface equation, it's possible to construct the effective linkage framework of surface modeling in the CAD systems and shell finite element analysis using geometrically exact shell finite element. Besides, the linkage framework can be applied to the analysis of general and complex surfaces as well as simple surfaces. In this study, the shell surfaces are generated by interpolating given set of data points based on the NURBS surfaces. These data points usually can be obtained from surface scanning. But the representations of the generated NURBS surface are not same to one another. The accuracy depends on the chosen parameterization methods used in NURBS. Therefore, it is needed to select the suitable parameterization method according to the geometry of the surfaces. To verify the performance and accuracy of our developed linkage framework, we solve several well-known benchmark problems and assess the performance of the developed method.