• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1364-1372
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• 2017

In this paper, a problem of event-triggered model predictive control is investigated for continuous-time Takagi-Sugeno (T-S) fuzzy systems with input quantization. To efficiently utilize network resources, event-trigger is employed, which transmits limited signals satisfying the condition that the measurement of errors is over the ratio of a certain level. Considering sampling and quantization, continuous Takagi-Sugeno (T-S) fuzzy systems are regarded as a sector bounded continuous-time T-S fuzzy systems with input delay. Then, a model predictive controller (MPC) based on parallel distributed compensation (PDC) is designed to optimally stabilize the closed loop systems. The proposed MPC optimize the objective function over infinite horizon, which can be easily calculated and implemented solving linear matrix inequalities (LMIs) for every event-triggered time. The validity and effectiveness are shown that the event triggered MPC can stabilize well the systems with even smaller average sampling rate and limited actuator signal guaranteeing optimal performances through the numerical example.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.16-23
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• 2013

The effects of dispersion coefficient of dispersion compensating fiber (DCF) and residual dispersion per span (RDPS) on in the dispersion managed optical links for compensating the distorted 960 Gbps wavelength division multiplexd (WDM) signals due to group velocity dispersion (GVD) and optical nonlinear effects of single mode fiber (SMF) are investigated. It is confirmed that optimal net residual dispersion (NRD), which greatly affects compensating for optical signals, should be induced under the large launch power condition, irrelevant on the considered dispersion coefficient of DCF and RDPS. It is also confirmed that system performances are greatly improved by selecting the very small RDPS and very large dispersion coefficient of DCF.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.5
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• pp.69-73
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• 2004

This paper deals with the transient performance of zero signal reference grid(ZSRG) and insulated/isolated ground(IG) in case of lightning strike or surge currents in buildings. Using HIFREQ, which is a commercial code for electromagnetic field analysis, the difference of transient performances of ZSRG and IG type grounding structure have been presented based on the numerical calculations. It is expected that the quantitative and numerical calculation based analysis, which is adopted in this paper, will attribute to the selection of optimal grounding method in the intelligent buildings.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.253-260
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• 1999

The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences during product use phase and recycling cells are formed design, process and usage attributes. In order to treat the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem for disposal products. In this paper, a heuristic approach for fuzzy ART neural network is suggested. The modified Fuzzy ART neural network is shown that it has a great efficiency and give an extension for systematically generating alternative solutions in the recycling cell formation problem. We present the results of this approach applied to disposal refrigerators and the comparison of performances between other algorithms. This paper introduced a procedure which integrates economic and environmental factors into the disassembly of disposal products for recycling in recycling cells. A qualitative method of disassembly analysis is developed and its aim is to improve the efficiency of the disassembly and to generated an optimal disassembly which maximize profits and minimize environmental impact. Three criteria established to reduce the search space and facilitate recycling opportunities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.728-733
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• 2018

Deep learning has been actively studied for predicting protein secondary structure based only on the sequence information of the amino acids constituting the protein. In this paper, we compared the performances of the convolutional neural networks of various structures to predict the protein secondary structure. To investigate the optimal depth of the layer of neural network for the prediction of protein secondary structure, the performance according to the number of layers was investigated. We also applied the structure of GoogLeNet and ResNet which constitute building blocks of many image classification methods. These methods extract various features from input data, and smooth the gradient transmission in the learning process even using the deep layer. These architectures of convolutional neural networks were modified to suit the characteristics of protein data to improve performance.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.2
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• pp.108-111
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• 2011

The semiconducting material of ZnO in II-VI group was well known as its good application for photo electronics, chemical sensors and field effect transistors due to the remarkable optical properties with wide energy band gap and great ionic reactivities. Up to now the growth of a good quality of ZnO film has been issued for better performances. Even though there were many deposition methods for making ZnO films, pulse laser deposition methods have been preferred for high crystalline films. In this report, the ZnO film was also created by pulsed laser deposition technique which also showed high crystalinity. By controlling several factors when deposited, it was investigated that the optimal condition for ZnO film formation. Mainly, oxygen partial pressures and growth temperatures were changed when ZnO films were synthesized and followed the characterization by HRXRD and AFM.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.9
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• pp.903-912
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• 2009

This study is focused on simulation-based dimensional tolerance optimization process (DTOP) to minimize vehicle pulls by reduction of dimensional variation in front suspension system. In previous studies, the effect of tires and wheel alignment sensitivity have mainly been investigated to eliminate vehicle pulls in nominal design condition without allocating optimal tolerance level for selected components, among various factors regarding vehicle pulls such as vehicle design parameters, vehicle weight balance, tires, and environmental factors. Unfortunately, there are wide variations in the real vehicle, and these have impacted actual vehicle pulls, especially wheel alignment effects from suspension geometry variation has not been considered in the previous studies. In the tolerance design of suspension, tolerance variables with the uncertainty such as parts dimensional variation, assembly process, datum position and direction, and assembly tool tolerance has a great influence on the variation of the suspension dimensional performances. This study introduces total vehicle pull prediction model in considering major key factors for vehicle pull sensitivity. The Monte Carlo-based tolerance analysis model using Taguchi robust method is developed to optimize dimensional tolerance parameters, satisfying on the target variation level.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.6
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• pp.957-962
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• 2013

This paper presents a performance testing device for safety fences of domestic professional baseball stadiums. Safety fences of professional stadiums have been fabricated and installed without adhering to any safety regulations, safety fences demonstrate critically low safety performances and many outfielders are severely injured every season. In this study, we designed and fabricated a performance testing device for safety fences and investigated its validity and reproducibility. A HIC (head injury criterion) was used for the statistical analysis of colliding data. We found that the optimal expulsion pressure and eliminated the accelerometer by replacing it with a velocity sensor using an estimation of the correlation between the momentum data obtained from velocity sensor and the impulse data from the accelerometer.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.61-72
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• 2005

In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2 DOF PID controller. The experimental results for an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard. Accordingly, the proposed algorithm in this study can be readily used for industrial applications

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.95.2-95.2
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• 2011

In order to achieve high performance and low cost for commercial applications, the development of membrane electrode assemblies (MEA), in which the electrochemical reactions actually occur, must be optimized. Expensive platinum is currently used as an electrochemical catalyst due to its high activity. Although various platinum alloys and non-platinum catalysts are under development, their stabilities and catalytic activities, especially in terms of the oxygen reduction (ORR), render them currently unsuitable for practical use. Therefore, it is important to decrease platinum loading by optimizing the catalysts and electrode microstructure. In this study, we prepared several different MEAs (non-uniform Nafion$^{(R)}$ ionomer loading electrode) which have dual catalyst layers to find the optimal Nafion$^{(R)}$ ionomer distribution in the electrodes. We changed Nafion$^{(R)}$ ionomer content in the layers to find the ideal composition of the binder and Pt/C in the electrode. For MEAs with various ionomer contents in the anodes and cathodes, the electrochemical activity (activation overpotential) and the mass transport properties (concentration overpotential) were analyzed and correlated with the single cell performance. The dual catalyst layers MEA showed higher cell performance than uniformly fabricated MEA, especially at the high current density region.