• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.653-657
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• 2004

In this study, PD(partial discharge) signals which occurrs at stator coil of traction Motor are acquired. these data are used for classifying the PD sources. W(Neural Network) has recently applied to classify the PB pattern. The PD data are used for the learning process to classify PD sources. The PD data come from normal specimen and defective specimens such as internal void discharges, slot discharges and surface discharges. PD distribution parameters are calculated from a set of the data, which is used to realize diagnostic algorithm. NN which applies distribution parameters is useful to classify the PD patterns of defective sources generating in stator coil of traction motor.

• Mass Spectrometry Letters
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• v.4 no.2
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• pp.25-29
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• 2013

Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution) method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.592-603
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• 2000

This paper is concerning off-line signature verification using a density function which is obtained by convolving the signature image with twelve-directional $5\times{5}$ gradient masks and the weighted fuzzy mean classifier. The twelve-directional density function based on Nevatia-Babu template gradient is related to the overall shape of a signature image and thus, utilized as a feature set. The weighted fuzzy mean classifier with the reference feature vectors extracted from only genuine signature samples is evaluated for the verification of freehand forgeries. The experimental results show that the proposed system can classify a signature whether it is genuine or forged with more than 98% overall accuracy even without any knowledge of varied freehand forgeries.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.172-183
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• 1998

The purpose of this study is to reduce the number of employees hired by Seoul Metropolitan Subway Corporation(SMSC) as a way of responding to deteriorating financial deficit problem. For the reduction, the personnel structure of Seoul Metro Rapid Transit Subway(SMRTS) newly founded in 1995 is benchmarked. Several assumptions are set for seeking the persuasive alternative; 1) no compulsory reduction of existing personnel, 2) raising the salary of SMSC to the same level of SMRTS for compensating intensified work burden, 3) hiring new employees to the amount of one-third of the reduced workforce for minimizing the problems associated with the reduction. The study suggests that the personnel reduction in relevant parts be planned in the following ways; 1) passenger transport part: from daily 3 shifts of 4 group to 2 shifts of 3 group, 2) fleet inspection, civil d: electric engineering, railtrack maintenance, signal parts: from 12 day-off to 10day-off, 3) architecture, AFC parts: from 2 shifts of 3 group to daily work, 4) fleet maintenance, architecture parts: expanding out-sourcing ＆ automation, and 5) headquarter part: 10% reduction of the total of office workers. The study finds, by implementing the plan, that 1,270 employee can be reduced, and that aggregate 106.8 billion won will be saved for the next 10 years.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.11-17
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• 2009

This paper presents a new adaptive relay selection scheme for a regenerative orthogonal frequency division multiplexing access(OFDMA) relay network with fairness constrains. In the Proposed scheme, we select the best M relays out of a set of K potential relays to maximize system capacity. Among these selected relays, subcarriers are reallocated to satisfy fairness constraints as well as to minimize the degradation of the system performance. Afterwards, power allocation is performed for each subcarrier based on the water-filling method to enhance the performance improvement. By using the trade-off relationship between the system capacity and the fairness, the modified version of proposed scheme is also investigated.

• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.3
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• pp.156-165
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• 2004

Concentrations of substrates, glucose, and ammionia in biological processes have been on-line monitored by using glucose-flow injection (FIA) and ammonia-FIA systems. Based on the on-line monitored data the concentrations of substrates have been controlled by an on-off controller, a PID controller, and a neural network (NN) based controller. A simulation program has been developed to test the control quality of each controller and to estimate the control parameters. The on-off controller often produced high oscillations at the set point due to its low robustness. The control quality of a PID controller could have been improved by a high analysis frequency and by a short residence time of sample in a FIA system. A NN-based controller with 3 layers has been developed, and a 3(input)-2(hidden)-1(output) network structure has been found to be optimal for the NN-based controller. The performance of the three controllers has been tested in a simulated process as well as in a cultivation process of Saccharomyces cerevisiae, and the performance has also been compared to simulation results. The NN-based controller with the 3-2-1 network structure was robust and stable against some disturbances, such as a sudden injection of distilled water into a biological process.

• Journal of the Ergonomics Society of Korea
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• v.29 no.6
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• pp.843-851
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• 2010

This study aims to systematically develop a usability evaluation model using the Structural Equation Model (SEM) from experiment of usability on using vehicle. Vehicle developers have been adding many functions for enhance the user satisfaction. But it will be made the trade-off problem of usability and design elements of vehicle interior from attempt to make best usability satisfaction in a restricted space. To solve the trade-off problem, we set a new solution criterion from usability evaluation model. The usability experiment is based on major activity pool from derived user's acts pattern in vehicle for make more accurate usability evaluation model. And this model was built with twenty-nine measurement variables for the evaluation of usability of vehicle user. As a result, the proposed SEM model showed statistical significance as well as a high level of R Square (0.7144). This model shows the relationships of detailed usability and design elements. According to the result, this study introduces the criterion to secure the best satisfaction of usability and design elements.

• ETRI Journal
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• v.37 no.3
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• pp.541-550
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• 2015

In this paper, we propose a classification-based approach for hybridizing statistical machine translation and rulebased machine translation. Both the training dataset used in the learning of our proposed classifier and our feature extraction method affect the hybridization quality. To create one such training dataset, a previous approach used auto-evaluation metrics to determine from a set of component machine translation (MT) systems which gave the more accurate translation (by a comparative method). Once this had been determined, the most accurate translation was then labelled in such a way so as to indicate the MT system from which it came. In this previous approach, when the metric evaluation scores were low, there existed a high level of uncertainty as to which of the component MT systems was actually producing the better translation. To relax such uncertainty or error in classification, we propose an alternative approach to such labeling; that is, a cut-off method. In our experiments, using the aforementioned cut-off method in our proposed classifier, we managed to achieve a translation accuracy of 81.5% - a 5.0% improvement over existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.105-111
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• 1999

This Paper is about how to deside the best parameter of PID controller, using Genetic Algorithms and Neural Networks. Control by Genetic Algorithms, which is off-line pass, has weakness for disturbance. So we want to improve like followings by adding Neural Network to controller and putting it on line. First we find PID parameter by Genetic Algorithms in forward pass of Neural Network and set the best output condition according to the increasing number of generation. Second, we explain the adaptability for disturbance with simulation by correcting parameter by backpropagation learning rule by using the learning ability of Neural Network.

• Nuclear Engineering and Technology
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• v.36 no.2
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• pp.142-152
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• 2004

The liquid entrainment and vapor pull-through offtake model of RELAP5/MOD3 had been developed for SBLOCA (Small Break Loss of Coolant Accident). The RELAP5/MOD3 model for horizontal volumes accounts for the phase separation phenomena and computes the flux of mass and energy through a branch when stratified conditions occur in the horizontal pipe. In the case of CANDU reactor, this model should be used in the coolant flow of 95 feeders connected to the reactor header component under the horizontal stratification in header. The current RELAP5 model can treat the only 3 directions junctions; vertical upward, downward, and side oriented junctions, and thus improvements for the liquid entrainment and vapor pull-through model were needed for considering the exact angles. The RELAP5 off-take model was modified and generalized by considering the geometric effect of branching angles. Based on the previous experimental results, the critical height correlation was reconstructed by use of the branch line connection angle and validation analyses were also performed using SET. The new model can be applied to vertical upward, downward and angled branch, and the accuracy of the new correlations is more improved than that of RELAP5.