• Journal of the Society of Naval Architects of Korea
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• v.45 no.2
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• pp.144-150
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• 2008

Ships and offshore structures are exposed to wave and engine excitation loadings during navigation and cargo/ballasting operations. These excessive loads may cause damages to hull and may result loss of life the ship. Therefore, it is important to develop a system that allow accurate measurements of global hull loads. The objective of the study is developing a fiber optic monitoring system that is capable of monitoring, recording and warning of the vessel performance. A method for measurement of global loads on a vessel, using strain measurements from a network of fiber optic strain sensors and extensive finite-element analyses(FEA) with idealistic load cases, is presented. The method has been successfully validated on the idealized ship structure model with strain sensors.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.26-30
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• 2003

The Lanczos algorithm is the most commonly used in approximating a small number of extreme eigenvalues for symmetric large sparse matrices. Global communications in MP(Message Passing) parallel computer decrease the computation speed. In this paper, we introduce the s-step Lanczos method, and s-step method generates reduction matrices which are similar to reduction matrices generated by the standard Lanczos method. One iteration of the s-step Lanczos algorithm corresponds to s iterations of the standard Lanczos algorithm. The s-step method has the minimized global communication and has the superior parallel properties to the standard method. These algorithms are implemented on Cray T3E and performance results are presented.

• Journal of the Korean Society of Safety
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• v.25 no.2
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• pp.12-17
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• 2010

Numerical simulations were performed for the prediction of the flame structure during the interaction between hydrogen and hydrocarbon flames. A counterflow flow geometry was introduced to establish the interacting two flames. Methane was used as a representative hydrocarbon fuel in this study. A well-known numerical code for the counterflow flame, OPPDIF, was used for the simulations. The detailed chemistry was adopted to predict the flame structure reasonably. The interaction of two one-dimensional premixed flames established in counterflow burner was investigated with the global strain rate and velocity ratio. It was found that the maximum temperature located near the methane flame surface while the heat release rate of methane was lower than hydrogen flame. The flame thickness become narrow with increasing the velocity ratio while the global strain rate was fixed. The local strain rate and heat release rate at the methane flame surface were correlated with the global strain rate, while those at the hydrogen flame were not correlated with the global strain rate. However, the maximum temperature of the interacting flames was correlated with the global strain rate.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.123-131
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• 2015

Training neural networks is a complex task with great importance in the field of supervised learning. In the training process, a set of input-output patterns is repeated to an artificial neural network (ANN). From those patterns weights of all the interconnections between neurons are adjusted until the specified input yields the desired output. In this paper, a new hybrid algorithm is proposed for global optimization of connection weights in an ANN. Dynamic swarms are shown to converge rapidly during the initial stages of a global search, but around the global optimum, the search process becomes very slow. In contrast, the gradient descent method can achieve faster convergence speed around the global optimum, and at the same time, the convergence accuracy can be relatively high. Therefore, the proposed hybrid algorithm combines the dynamic particle swarm optimization (DPSO) algorithm with the backpropagation (BP) algorithm, also referred to as the DPSO-BP algorithm, to train the weights of an ANN. In this paper, we intend to show the superiority (time performance and quality of solution) of the proposed hybrid algorithm (DPSO-BP) over other more standard algorithms in neural network training. The algorithms are compared using two different datasets, and the results are simulated.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.4
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• pp.201-207
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• 2001

This paper describes an automated detection algorithm of ST-T episodes using global curvature which can connect the isoelectric level in ECG and can eliminate not only the slope of ST segment, but also difference of the baseline and global curve. This above method of baseline correction is very faster than the classical baseline correction methods. The optimal values of parameters for baseline correction were found as the value having the highest detection rate of ST episode. The features as input of backpropagation Neural Network were extracted from the whole ST segment. The European ST-T database was used as training and test data. Finally, ST elevation, ST depression and normal ST were classified. The average ST episode sensitivity and predictivity were 85.42%, 80.29%, respectively. This result shows the high speed and reliability in ST episode detection. In conclusion, the proposed method showed the possibility in various applications for the Holter system.

• Journal of Engineering Education Research
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• v.12 no.3
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• pp.41-49
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• 2009

The paper introduces an educational environment for multidisciplinary automotive development project made with other global institutions worldwide. The main objective is to accelerate students design and manufacturing skills, while giving them the experience of global communications for a large scale collaboration. This objective demands the intimate partnership between industrial design and engineering worldwide as well. Not only is the design and manufacturing portion of the project a challenge, but the students must organize the project teams together to incorporate different subsystem designs from other institutions, which, after all, requires constant communication and a truly team-oriented atmosphere for the global innovative engineering education.

• Transactions on Electrical and Electronic Materials
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• v.13 no.1
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• pp.31-34
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• 2012

The addition of nano/micro silica into unsaturated polyester resin (UPR) results in the improvement of the electrical properties of Silica-UPR composites. The surface, volume resistivity, dielectric strength, dissipation factor and dry arc resistivity of nano silica-UPR composites were found to improve significantly. The effects of the nano and micro fillers in UPR have been evaluated. They are presented in this paper. To evaluate the electrical properties of the nano & micro composites, all the measurements were done as per the prescribed methods in ASTM. It was observed that the addition of nano silica improves the electrical properties as compared to micro silica. The better dispersion of silica particles in unsaturated polyester resin enhances the electrical properties of silica-UPR composites.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.251-254
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• 2015

출석체크를 자동으로 하는 시스템으로 QR 코드나 NFC 등의 전자 태그기반 방식들이 있으나 태깅을 수동으로 해야 하는 불편함과 함께 태그의 물리적 파손 문제 등의 단점이 그 확산에 제한 사항으로 작용하고 있다. 본 논문에서는, 태그 기반 대신 Bluetooth Low Energy(BLE) 비콘 신호를 학생들의 스마트폰으로 수신하여 위치와 시간을 확인함으로 출석을 자동으로 체크하는 경제적이고 안정적인 출결 시스템을 제안한다. 나아가, 시스템 초기 및 유지 비용을 구성하는 요인들을 분석하고, 시스템의 안정적 운영을 보장하는 제한조건 하에서 BLE 비콘의 설치 및 운영의 경제성을 높이기 위한 추가적 변인들을 열거하고 변인들 간의 trade-off를 고려하여 시스템을 설계해야 함을 보였다.

• Journal of the Korean Institute of Gas
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• v.8 no.2 s.23
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• pp.42-47
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• 2004

The axisymmetric methane-air counterflow flame in microgravity was simulated to investigate effects of the global strain rate on the flame structure. The flame shapes and profiles of temperature and the axial velocity for the mole fraction of methane in the methane-nitrogen fuel stream, Xm= 20, 50, $80\%$, and the global strain rate, ag= 20, 60, 90 $s^{-1}$ each mole fraction were compared. The profiles of the temperature and axial velocity of the axisymmetric simulations were in good agreement with those of OPPDIF, an one-dimensional flamelet code. It was confirmed that the flame is stretched more and the flame radius increases and the flame thickness decreases as the global strain rate increases.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.137-143
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• 2005

Autonomous mobile robot has an ability to navigate using both map in known environment and sensors for detecting obstacles in unknown environment. In general, autonomous mobile robot navigates by global path planning on the basis of already made map and local path planning on the basis of various kinds of sensors to avoid abrupt obstacles. This paper provides a global path planning method using self-organizing feature map which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial weight vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified method in this research uses a predetermined initial weight vectors, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. According to simulation results one can conclude that the modified neural network is useful tool for the global path planning problem of a mobile robot.