• Management & Information Systems Review
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• v.37 no.2
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• pp.87-108
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• 2018

This article explores the international trade flow of Bangladesh's ready-made garments (RMG). We first suggest the brief history and an international structure of trade among countries by using the trade volume. Then we implemented a gravity model regression with the sample of 38 major partner countries in order to investigate the potential export market for the RMG industry. The fixed effect and random effect model for the panel data during the period of 1990 to 2011 are estimated. Our result shows that Bangladesh's RMG exports are affected positively by the size of economy, inflation, exchange rate, foreign direct investment(FDI) and trade openness. On the other hand, the distance between trading partners are related negatively with the trade volume. We used the estimated coefficients from the panel regression in order to predict RMG export potential of Bangladesh. This might show which country is the promising export market for Bangladesh RMG industry. We found that Bangladesh has the highest potential of RMG export with Japan and USA, which seem to have considerable room for export growth if trade barriers and constraints are removed. We added some policy implications for encouraging the RMG export of Bangladesh by using the results from the analysis.

• Journal of IKEEE
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• v.18 no.2
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• pp.272-281
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• 2014

In electrical impedance tomography (EIT), modified Newton Raphson (mNR) method is widely used inverse algorithm for static image reconstruction due to its convergence speed and estimation accuracy. The unknown conductivity distribution is estimated iteratively by minimizing a cost functional such that the residual error namely the difference in measured and calculated voltages is reduced. Although, mNR method has good estimation performance, EIT inverse problem still suffers from ill-conditioned and ill-posedness nature. To mitigate the ill-posedness, generally, regularization methods are adopted. The inverse solution is highly dependent on the choice of regularization parameter. In most cases, the regularization parameter has a constant value and is chosen based on experience or trail and error approach. In situations, when the internal distribution changes or with high measurement noise, the solution does not get converged with the use of constant regularization parameter. Therefore, in this paper, in order to improve the image reconstruction performance, we propose a new scheme to determine the regularization parameter. The regularization parameter is computed based on residual error and updated every iteration. The proposed scheme is tested with numerical simulations and laboratory phantom experiments. The results show an improved reconstruction performance when using the proposed regularization scheme as compared to constant regularization scheme.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.3
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• pp.361-371
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• 2000

RC structure is the composite material system combined concrete and steel showing different plastic behavior. Especially, concrete shows very complex plastic behavior. Therefore, for plastic analysis of RC structures, we have to model carefully each plastic behavior of concrete and steel member. But, because of divergency as well as difficulties and dimensions of modelling, it takes a lot of time and labor or sometimes it is impossible to perform plastic analysis of RC structures. In this study, for simplified plastic analysis of RC structures, we propose material transformation method by homogeneous and isotropic material which have the same plastic property as RC. We generate homogeneous and isotropic material showing the same moment-curvature curves (bi-linear stress-strain relation) as RC members, using bi-linear moment-curvature relation by yielding moment, yielding curvature and ultimate moment, ultimate curvature of RC member. Finally, we prove compatibility in the study by comparing plastic analysis results for various analysis models using transformed material models and RC model.

• Journal of IKEEE
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• v.20 no.2
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• pp.152-162
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• 2016

Electrical resistivity tomography (ERT) is a technique to reconstruct the internal resistivity distribution using the measured voltages on the surface electrodes. ERT inverse problem suffers from ill-posedness nature, so regularization methods are used to mitigate ill-posedness. The reconstruction performance varies depending on the type of regularization method. In this paper, an interacting dual-mode regularization method is proposed with two different regularization methods, L1-norm regularization and total variation (TV) regularization, to achieve robust reconstruction performance. The interacting dual-mode regularization method selects the suitable regularization method and combines the regularization methods based on computed mode probabilities depending on the actual conditions. The proposed method is tested with numerical simulations and the results demonstrate an improved reconstruction performance.

• Journal of the Korea Concrete Institute
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• v.28 no.5
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• pp.571-579
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• 2016

RS-LMC (Rapid Setting Latex Modified Concrete) has been widely used as repair material for bridge deck overlay or rehabilitation, because the overlaid pavement could be opened to the traffic after 3 hours of curing. Although the field performance of RS-LMC generally indicates that it has an excellent bonding to the substrate and shows a long term performance, the crack by vibration of vehicles have been happened on the overlay of bridges in technical reports. In this study, experimental research was carried out to evaluate the vibration properties of RS-LMC overlays by using P.S.T (Pavement Shaking Table). Total 12 specimens were tested and the variables are Latex-cement ratio (L/C) and amplitude of vibration. The result shows that the number of cracks and the total length of cracks are reduced as the increase of Latex-cement ratio (L/C) until 15%. And the crack occurs at a very small strain than the proposed values by Walter, D, G and design codes.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.805-814
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• 2013

This paper proposes a robust hand segmentation method using view-invariant characteristic of a wrist-mounted camera, and deals with a hand shape recognition system based on segmented hand information. We actively utilize the advantage of the proposed camera device that provides view-invariant images physically, and segment hand region using a Bayesian rule based on adaptive histograms. We construct HSV histograms from RGB histograms, and update HSV histograms using hand region information from a current image. We also propose a user adaptation method by which hand models gradually approach user-dependent models from user-independent models as the user uses the system. The proposed method was evaluated using 16 Korean manual alphabet, and we obtained increases of 27.91% in recognition success rate.

• Geophysics and Geophysical Exploration
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• v.18 no.3
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• pp.105-114
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• 2015

A long-term resistivity monitoring system has been developed for saturated cores in room temperature and humidity condition. A 3-channel water-pump continuously drops the water onto the top of saturated core sample surrounded by shrinkable tube as well as on the paper filters of the electrodes at both sides of the core sample, by which one can monitor the resistivity changes with maintaining full saturation of the rock core for a week or longer. Monitoring the resistivity changes has been performed with 3 kinds of rock samples including biotite gneiss, andesitic tuff, and shale for 9 days using the system. Consequently, it is proposed two hypothesis that conversion speed of temperature coefficient has close relation to the thermal properties of the rock sample and that the ratio of resistance between dry and saturated conditions for a rock sample can be related to the effective porosity of the sample. The ratio between dry and saturated resistance for the three rock types are 48, 705, and 2, while effective porosity was 3.7%, 3.3%, and 13.0%, respectively.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.11
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• pp.1220-1228
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• 2010

In this paper, we suggest a scheme to develop an efficient discrete nonlinear model based on polynomial structure for a RF power amplifier(PA). We describe a procedure to extract a discrete nonlinear model such as Taylor series or memory polynomial by sampling the input and output signal of RF PA. The performance of the model is analyzed varying the model parameters such as sample rate, nonlinear order, and memory depth. The results show that the relative error of the model is converged if the parameters are larger than specific values. We suggest an efficient modeling scheme considering complexity of the discrete model depending on the values of the model parameters. Modeling efficiency index(MEI) is defined, and it is used to extract optimum values for the model parameters. The suggested scheme is applied to discrete modeling of various RF PAs with various input signals such as WCDMA, WiBro, etc. The suggested scheme can be applied to the efficient design of digital predistorter for the wideband transmitter.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4C
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• pp.159-167
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• 2012

In this study, laboratory model pile-load test and finite element analysis were carried out to compare and analyze the strain behaviour around the model pile tip. In order to simulate the pile load, both the LCM(load control method)and DCM(displacement control method) were introduced to determine which one is appropriate for the FE simulation. In contrast to the previous simulation method, two interface elements around the model pile were used to consider the slip effect in the finite element analysis and its results were compared to the model test. Through this study it was found that the degree of non-associated flow was a dominant factor in terms of numerical solution convergence. In addition, an improved FE mesh was required to obtain the symmetric distribution of the maximum shear strain contour.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.911-923
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• 2016

Machine learning becomes increasingly important in the big data era. Logistic regression is a type of classification in machine leaning, and has been widely used in various fields, including medicine, economics, marketing, and social sciences. Rhipe that integrates R and Hadoop environment, has not been discussed by many researchers owing to the difficulty of its installation and MapReduce implementation. In this paper, we present the MapReduce implementation of Gradient Descent algorithm and Newton-Raphson algorithm for logistic regression using Rhipe. The Newton-Raphson algorithm does not require a learning rate, while Gradient Descent algorithm needs to manually pick a learning rate. We choose the learning rate by performing the mixed procedure of grid search and binary search for processing big data efficiently. In the performance study, our Newton-Raphson algorithm outpeforms Gradient Descent algorithm in all the tested data.