• 유체기계공업학회:학술대회논문집
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• 2002.12a
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• pp.111-115
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• 2002

The objective of this work is to develop improved slip factor model and correction method to predict flow through impeller in forward-curved centrifugal fan by investigating the validity of various slip factor models. Both steady and unsteady three-dimensional CFD analyses were performed with a commercial code tn validate the slip factor model and the correction method. The results show that the improved slip factor model presented in this paper could provide more accurate predictions for forward-curved centrifugal impeller than the other slip factor models since the presented model takes into account the effect of blade curvature. The comparison with CFD results also shows that the improved slip factor model coupled with the present correction method provides accurate predictions for mass-averaged absolute circumferential velocity at the exit of impeller near and above the flow rate of peaktotal pressure coefficient.

• Journal of Multimedia Information System
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• v.8 no.4
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• pp.203-210
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• 2021

Deep leaning convolutional neural networks (CNN) have successfully been applied to image super-resolution (SR). Despite their great performances, SR techniques tend to focus on a certain upscale factor when training a particular model. Algorithms for single model multi-scale networks can easily be constructed if images are upscaled prior to input, but sub-pixel convolution upsampling works differently for each scale factor. Recent SR methods employ multi-scale and multi-path learning as a solution. However, this causes unshared parameters and unbalanced parameter distribution across various scale factors. We present a multi-scale single-path upsample module as a solution by exploiting the advantages of sub-pixel convolution and interpolation algorithms. The proposed model employs sub-pixel convolution for the highest scale factor among the learning upscale factors, and then utilize 1-dimension interpolation, compressing the learned features on the channel axis to match the desired output image size. Experiments are performed for the single-path upsample module, and compared to the multi-path upsample module. Based on the experimental results, the proposed algorithm reduces the upsample module's parameters by 24% and presents slightly to better performance compared to the previous algorithm.

• East Asian mathematical journal
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• v.33 no.1
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• pp.23-36
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• 2017

We study an optimization problem for HARA utility function under a multi-scale Heston's stochastic volatility model. We investigate a practical strategy that do not depend on the incorporated factor which is unobservable in the market.

• Journal of the Korea Society for Simulation
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• v.11 no.1
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• pp.59-70
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• 2002

This article presents the results of research to develop a descriptive model of firm-level productivity that will allow a myriad of factor interactions to be directly accounted for. The model is a linked set of equations that attempt to capture how changes in one-factor influences the level of another factor. and ultimately bottom-line performance. The model is coded in SIMAN. It is used to determine the best use of an infusion of funds should they go for additional automation, or training etc. An application of the model to U.S. industry is presented based on parameter values obtained through a national survey.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.63-81
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• 1995

This paper presents a model and algorithm for solving the multi-factor plant layout problem. The model can incorporate more than two factors that may be either quantitative or qualitative. The algorithm is based on simulated annealing, which has been successfully applied for the solution of combinatorial problems. A set of problems previously used by various authors is solved to demonstrate the effectiveness of the proposed methods. The results indicate that the proposed methods can yield good quality for each of eleven test problems.

• Management & Information Systems Review
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• v.25
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• pp.371-386
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• 2008

In this study, the hypothesized model of internet user satisfaction in e-commerce environment is developed and the relationships among constructs in the model are examined. A Confirmatory factor analysis is employed to analyze the relationships between the multiple dependent variables and independent variables.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2669-2671
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• 2001

In this paper, we propose design a Multi-Fuzzy Inference model structure. In order to determine structure of the proposed Multi-Fuzzy Inference model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.8 s.251
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• pp.741-748
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• 2006

This paper numerically investigates the effects of pass arrangement on the flow distribution characteristics and the performance of a multi-pass multi-branch heat exchanger. Four cases of pass arrangement (2, 4, 6, 8 pass) are chosen to select a proper pass arrangement. A JF factor is used as an evaluation characteristic value to consider the heat transfer and the pressure drop. The present results indicate that 4-pass heat exchanger shows the best performance, and the design parameters in 4-pass heat exchanger are optimized. The design parameters are the locations of the inlet, outlet and separator, and are optimized using a response surface methodology. The JF factor of the optimum model is increased by about 9.3%, compared to that of the reference model (2-pass heat exchanger).

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.370-370
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• 2000

In this paper, we design a Multi-Fuzzy model by means of HCM clustering and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy ate identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy mode] and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

• Journal of Environmental Science International
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• v.12 no.6
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• pp.605-613
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• 2003

In order to make use of the protection effect against wind by the vegetation, it examined whether it should make what vegetation form and arrangement using the 2-dimensional non-hydrostatic model. When the foliage shielding factor increases, it becomes hard to take in protection effect against wind in a residential section. When it makes height of vegetation high, it becomes hard to take in protection effect against wind with height. In the comparison in the case where vegetation high is gradually made low toward wind-stream from a vegetation, and the case of making it low gradually, although former tends to receive the protection effect against wind by the vegetation, attenuation of wind velicity becomes large. In the comparison in the case where foliage shielding factor and distribution of density of leaf are gathered gradually toward wind-stream from a vegetation. It has been understood to evaluate to height the influence that the vegetation multi-layer model by which the heat revenue and expenditure in the direction of the vegetation height is considered is used, and to characterize the vegetation group by the parameter setting.