• 한국ITS학회:학술대회논문집
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• v.2006 no.10
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• pp.191-194
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• 2006

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.613-614
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• 2012

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.15-22
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• 2006

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2000.11a
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• pp.39-48
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• 2000

• Geophysics and Geophysical Exploration
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• v.15 no.3
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• pp.129-135
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• 2012

The simultaneous-source full waveform inversion improves the applicability of full waveform inversion by reducing the computational cost. Since this technique adopts simultaneous multi-source for forward modeling, unwanted events remain in the residual seismograms when the receiver geometry of field acquisition is different from that of numerical modeling. As a result, these events impede the convergence of the full waveform inversion. In particular, the streamer-type data with limited offsets is the most difficult data to apply the simultaneous-source technique. To overcome this problem, the global-correlation-based objective function was suggested and it was successfully applied to the simultaneous-source full waveform inversion in time domain. However, this method distorts residual wavefields due to the modified objective function and has a negative influence on the inversion result. In addition, this method has not been applied to the frequency-domain simultaneous-source full waveform inversion. In this paper, we apply a timedamping function to the observed and modeled data, which are used to compute global correlation, to minimize the distortion of residual wavefields. Since the damped wavefields optimize the performance of the global correlation, it mitigates the distortion of the residual wavefields and improves the inversion result. Our algorithm incorporates the globalcorrelation-based full waveform inversion into the frequency domain by back-propagating the time-domain residual wavefields in the frequency domain. Through the numerical examples using the streamer-type data, we show that our inversion algorithm better describes the velocity structure than the conventional global correlation approach does.

• Journal of Engineering Education Research
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• v.21 no.3
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• pp.38-45
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• 2018

The purpose of this study is to analyze the change of perceptions and images of teachers about engineering, according to practical training in laboratories of engineering research institutes. For this purpose, 149 elementary and secondary school teachers were surveyed before and after visiting the engineering research institutes and examined the perception of engineers and engineering. Through this teacher training program, perceptions and images of most teachers are changed positively and they can understand practically about engineering, and related fields. The results of this study can be used as basic data for the development, operation, and expansion of teacher training using advanced science and technology research institutes with excellent human and material resources.

• 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 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 Power Electronics
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• v.27 no.4
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• pp.297-304
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• 2022

This study compares the performance of artificial intelligence (AI)-based maximum power point tracking (MPPT) methods under partial shading conditions in a photovoltaic generation system. Although many studies on AI-based MPPT have been conducted, few studies comparing the tracking performance of various AI-based global MPPT methods seem to exist in the literature. Therefore, this study compares four representative AI-based global MPPT methods including fuzzy logic control (FLC), particle swarm optimization (PSO), grey wolf optimization (GWO), and genetic algorithm (GA). Each method is theoretically analyzed in detail and compared through simulation studies with MATLAB/Simulink under the same conditions. Based on the results of performance comparison, PSO, GWO, and GA successfully tracked the global maximum power point. In particular, the tracking speed of GA was the fastest among the investigated methods under the given conditions.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.459-459
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• 2012

Recently, the discharge of global warming gases in dry etching process of TFT-LCD display industry is a serious issue because perfluorocarbon compound (PFC) gas causes global warming effects. PFCs including CF4, C2F6, C3F8, CHF3, NF3 and SF6 are widely used as etching and cleaning gases. In particular, the SF6 gas is chemically stable compounds. However, these gases have large global warming potential (GWP100 = 24,900) and lifetime (3,200). In this work, we chose C3F6O gas which has a very low GWP (GWP100 = <100) and lifetime (< 1) as a replacement gas. This study investigated the effects of the gas flow ratio of C3F6O/O2 and process pressure in dual-frequency capacitively coupled plasma (CCP) etcher on global warming effects. Also, we compared global warming effects of C3F6O gas with those of SF6 gas during dry etching of a patterned positive type photo-resist/silicon nitride/glass substrate. The etch rate measurements and emission of by-products were analyzed by scanning electron Microscopy (SEM; HITACI, S-3500H) and Fourier transform infrared spectroscopy (FT-IR; MIDAC, I2000), respectively. Calculation of MMTCE (million metric ton carbon equivalents) based on the emitted by-products were performed during etching by controlling various process parameters. The evaluation procedure and results will be discussed in detail.