• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.1-7
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• 1996

The grouping of parts into families and machines into cells poses an important problem for the improvement of productivity and quality in the design and planning of the flexible manufacturing system(FMS). This paper proposes a new algorithm of forming machine-part groups in case of the bottleneck machine problem and shows the numerical example. This algorithm could be applied to the large scale machine-part grouping problem.

• Structural Engineering and Mechanics
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• v.41 no.4
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• pp.559-573
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• 2012

An adaptive modeling and simulation technique is introduced for the effective and reliable fluid-structure interaction analysis using MSC/Dytran for large-scale complex pressurized liquid containment. The proposed method is composed of a series of the global rigid sloshing analysis and the locally detailed fluid-structure analysis. The critical time at which the system exhibits the severe liquid sloshing response is sought through the former analysis, while the fluid-structure interaction in the local region of interest at the critical time is analyzed by the latter analysis. Differing from the global coarse model, the local fine model considers not only the complex geometry and flexibility of structure but the effect of internal pressure. The locally detailed FSI problem is solved in terms of multi-material volume fractions and the flow and pressure fields obtained by the global analysis at the critical time are specified as the initial conditions. An in-house program for mapping the global analysis results onto the fine-scale local FSI model is developed. The validity and effectiveness of the proposed method are verified through an illustrative numerical experiment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.210-211
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• 2018

In general, the dam break problem is demonstrated to simulate open-channel disturbance due to large violent waves. These days, the large violent waves at shore and coastline can be seen frequently such like tsunami. The conventional computational fluid dynamics program based on Grid system, can be used to simulate this problem with large deformation of free surface in the restricted condition due to its limitation. The particle method based on fully Lagrangian approach is able to simulate large deformation of free surface by tracking each particles. In this study, the simulation of disturbance of mobile-bed due to large violent waves was investigated by using particle method.

• Journal of Mechanical Science and Technology
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• v.19 no.3
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• pp.913-923
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• 2005

The dynamic mixed model (DMM) combined with a box filter of Zang et. al. (1993) has been generalized for passive scalar transport and applied to large eddy simulation of turbulent channel flows with Prandtl number up to 10. Results from a priori test showed that DMM is capable of predicting both subgrid-scale (SGS) scalar flux and dissipation rather accurately for the Prandtl numbers considered. This would suggest that the favorable feature of DMM, originally developed for the velocity field, works equally well for scalar transport problem. The validity of the DMM has also been tested a posteriori. The results of the large eddy simulation showed that DMM is superior to the dynamic Smagorinsky model in the prediction of scalar field and the model performance of DMM depends to a lesser degree on the ratio of test to grid filter widths, unlike in the a priori test.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.322-327
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• 2017

The classification problem in the field of Natural Language Processing has been studied for a long time. Continuing forward with our previous research, which classifies large-scale text using Convolutional Neural Networks (CNN), we implemented Recurrent Neural Networks (RNN), Long-Short Term Memory (LSTM) and Gated Recurrent Units (GRU). The experiment's result revealed that the performance of classification algorithms was Multinomial Naïve Bayesian Classifier < Support Vector Machine (SVM) < LSTM < CNN < GRU, in order. The result can be interpreted as follows: First, the result of CNN was better than LSTM. Therefore, the text classification problem might be related more to feature extraction problem than to natural language understanding problems. Second, judging from the results the GRU showed better performance in feature extraction than LSTM. Finally, the result that the GRU was better than CNN implies that text classification algorithms should consider feature extraction and sequential information. We presented the results of fine-tuning in deep neural networks to provide some intuition regard natural language processing to future researchers.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.140-146
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• 2002

We consider a class of large-scale interconnected time delay systems and investigate a decentralized robust passive control problem. sufficient conditions for unforced interconnected uncertain systems with time delay to be robustly stable with extended strictly passivity is given in terms of algebraic Riccati inequality and linear matrix inequality. The decentralized robust passive control problem for norm-bounded and positive real uncertainty is shown to be converted to extended strictly positive real control problem for a modified system which contains neither time delay nor uncertainty.

• Journal of the military operations research society of Korea
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• v.26 no.1
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• pp.34-46
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• 2000

The object of this study is to construct a model for an optimal allocation of short surface to air missile defending our targets most efficiently from hostile aircraft´s attack. For the purpose of this, we analyze and establish facility allocation concept of existing models, apply set covering theory appropriate to problem´s properties, present the process of calculating the probability of target being protected, apply Sherali-Kim´s branching variable selection strategy, and then construct the model. As constructed model apply the reducing problem with application, we confirm that we can apply the large scale, real problem.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.36-39
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• 1998

It is very difficult for the large-scale retailers, who deal with tens of thousands of items, to price all the items dynamically reflecting all the constraints and policies. In spite of its importance, the prices are determined by human experts because the process of setting the prices of all the items is not established yet. To solve this problem, we adopt a mixed model that combines three typical pricing models: cost-plus model, competition-oriented model, and demand-oriented model. Since each model an be converted to a set of constraints in point and interval forms, solving the pricing problem with the three groups of models requires an algorithm which can solve the problem with weighted constraints of intervals and points. So we have devised an algorithm named “Point Determination Algorithm”. From the rules that represents tile models, the constraints are extracted to be solvable by tile Point Determination Algorithm. A prototype KAPA (Knowledge Assisted pricing Advisor) is developed with this idea using the expert system environment UNIK - a tool developed by KAIST. According to the experiment with 76 items in comparison with 53 human pricing experts we confirmed that the KAPA can perform highly consistent with human experts. This implies KAPA system is applicable to pricing millions of items dynamically.

• Journal of Korean Port Research
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• v.12 no.1
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• pp.9-17
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• 1998

The evaluation structure of complex problems is composed of multi-attributes and hierarchy. A many studies were existed on this problems, but that based on the assumption that the evaluation elements were independent. The actual evaluation problems have the complexity, ambiguity and interlinkage among the elements. In this situation, the fuzzy evaluation process is very effective in settling the complex problems. For evaluation of large scale hierarchical MADM problem, the fuzzy evaluation algorithm is developed in this paper, and that is centering on the identification of fuzzy measures. In this study, we newly identified the weight and interaction among the evaluation attributes. The results of this study are as follows: we can identified the hierarchical structure of the evaluation problem which is composed of the evaluation structure, function and hierarchy; we improved the existed weighting method which could be accomplished by normalizing process, considering the uncertainty and new weight integrating method which come from Dempster-Shafer theory. And we take into account the interaction properties among more than 3 evaluation attributes, which can be compared with the existed studies in which only 2 evaluation attributes taked into account.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1596-1604
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• 2013

Coordinating operation between large-scale wind power and thermal units in multiple time scale is an important problem to keep power balance, especially for the power grids mainly made up of large coal-fired units. The paper proposes a novel operation mode of multi-scale unit commitment (abbr. UC) that includes mid-term UC and day-ahead UC, which can take full advantage of insufficient flexibility and improve wind power accommodation. First, we introduce the concepts of multi-scale UC and then illustrate the benefits of introducing mid-term UC to the wind-coal intensive grid. The paper then formulates the mid-term UC model, proposes operation performance indices and validates the optimal operation mode by simulation cases. Compared with day-ahead UC only, the multi-scale UC mode could reduce the total generation cost and improve the wind power net benefit by decreasing the coal-fired units' on/off operation. The simulation results also show that the maximum total generation benefit should be pursued rather than the wind power utilization rate in wind-coal intensive system.