• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.2
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• pp.139-152
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• 2010

This study presents graphic-user interface computer program for optimal compensation of differential column shortening with high field applicability. The implemented system can perform both relative and mixed compensation while satisfying both performance and construction constraints. In the proposed system the shape of the structure before and after compensation can be checked graphically, and the results of compensation of each stories can be printed in drawings which can be directly used as the report of column shortening. The field-applicability of the implemented system was verified by applying it to the four reinforced concrete residental buildings of 61, 42, 49 and 53 stories where compensation of differential column shortening had already been performed. Using the implemented system, compensation can be performed easily with the various constraint conditions and was able to acquire rational compensation results for the cases where conventional method was not successful.

• Journal of the Korea Concrete Institute
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• v.16 no.1 s.79
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• pp.36-42
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• 2004

Although steel-reinforced concrete(SRC) is widely used in a high-rise building, a methods used to predict the column shortening of SRC structural members has many problems in applying a theoretical equation which considers only the material characteristics of reinforced concrete. In this study, the degree of accuracy of the existing method calculating the column shortening of a high-rise building is examined. For this, first, the actual measurement data are chosen about the column shortening of a high-rise building established with SRC structural members. Then the column shortening of a SRC structural member is calculated through computer program. Finally, the comparison between the measurement data and the analytical ones is executed. According to this study, it can be concluded that there is little difference between the former and the latter. Therefore, the existing method can be used to evaluate the column shortening of a high-rise building using a SRC structural members.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.179-190
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• 2009

In the financial industry, the decision tree algorithm has been widely used for classification analysis. In this case one of the major difficulties is that there are so many explanatory variables to be considered for modeling. So we do need to find effective method for reducing the number of explanatory variables under condition that the modeling results are not affected seriously. In this research, we try to compare the various variable reducing methods and to find the best method based on the modeling accuracy for the tree algorithm. We applied the methods on the pension insurance of a insurance company for getting empirical results. As a result, we found that selecting variables by using the sensitivity analysis of neural network method is the most effective method for reducing the number of variables while keeping the accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.13-19
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• 2001

The conventional fractal decoding was required a vast amount computational complexity, since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested that each range block was classified to iterated and non-iterated regions. Non-iterated regions is called data dependency region, and if data dependency region extended, IFS regions are contractive. In this paper, a searched region of the domain is limited to the range regions that is similar with the domain blocks, and the domain region is more overlapped. As a result, data dependency region has maximum region, that is IFS regions can be minimum region. The minimizing method of domain region is defined to minimum domain(MD) which is minimum IFS region. Using the minimizing method of domain region, there is not influence PSNR(peak signal-to-noise ratio). And it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• Fire Science and Engineering
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• v.28 no.2
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• pp.14-19
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• 2014

A current standard exist only on the surface tension in the current domestic wetting agent technology standards, so it is difficult to the performance evaluation of the wetting agent through the standard. So this study presents the optimized performance evaluation methods by scale model experimental equipment in order to present techniques for performance evaluation of wetting agents. The purpose of this study is to investigate validity of experimental results of the self-designed scale model experiment equipment by a comparative analysis of experimental results of the NFPA 18 experiment and the experiment using the self-designed scale model experiment equipment. As a result of a comparative analysis of experimental results of the NFPA 18 experiment that evaluate only the permeation performance on the contton and the experiment using the self-designed scale model experiment equipment that evaluate the permeation performance and fire extinguishing performance on wood flour, the discrimination of the permeation performance was confirmed in both the NFPA 18 experiment and the self-designed scale model experiment equipment. And a result of self-designed experiment equipment have clear discriminatory more than NFPA 18 by internal temperature measurement using the thermocouples.

• Fire Science and Engineering
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• v.34 no.4
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• pp.59-68
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• 2020

In this study, the authors designed a reduced-scale railway vehicle fire, which was necessary for evaluating the fire safety of railway tunnels using a reduced model. To overcome the shortcomings of the methods used in conventional reduced-scale railway tunnel tests, the authors simulated the fire source of a railway vehicle using a methanol fire source for fire buoyancy, and a smoke cartridge for smoke visualization. Therefore, the heat release mass consumption rates of various methane trays were measured using a cone calorimeter (ISO 5660). The critical ventilation velocity in the railway tunnels was obtained using the designed fire source of the railway vehicle, which was evaluated by the measured temperature at the top of the tunnel as well as laser visualization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1484-1489
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• 2004

Given a video frame in terms of its 8${\times}$8 block-DCT coefncients, we wish to obtain a downsized or upsized version of this Dame also in terms of 8${\times}$8 block DCT coefficients. The DCT being a linear unitary transform is distributive over matrix multiplication. This fact has been used for downsampling video frames in the DCT domains in Dugad's, Mukherjee's, and Park's methods. The downsampling and upsampling schemes combined together preserve all the low-frequency DCT coefficients of the original image. This implies tremendous savings for coding the difference between the original frame (unsampled image) and its prediction (the upsampled image).This is desirable for many applications based on scalable encoding of video. In this paper, we extend the earlier works to various DCT sizes, when we downsample and then upsample of an image by a factor of two. Through experiment, we could improve the PSM values whenever we increase the DCT block size. However, because the complexity will be also increase, we can say there is a tradeoff. The experiment result would provide important data for developing fast algorithms of compressed-domain image/video resizing.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.2
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• pp.71-75
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• 2021

Despite the development of computational resources, the need to analyze models is increasing. The size of model has been increased to analyze the entire structure more accurately and precisely. As the analysis model becomes larger and more complex, the computation time increases exponentially. Various industries use many structures that have repeated patterns. We focus on these structures with repeated patterns and propose a dynamic analysis method to efficiently calculate these repeated structures. To devise an efficient method for repeated structures, the substructuring scheme and the degree of freedom-based reduction method are used in this study. We modify the existing reduction method in consideration of the characteristics of the repeating structure. In the proposed method, the entire structure was expressed as a combination of substructures, where each substructure was represented as an unit cell of repeated structures. The substructures were condensed and assembled using the substructuring scheme and the modified condensation method. Finally, numerical examples were demonstrated to verify the efficiency and accuracy of proposed method.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1055-1060
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• 2020

This study is a study on the analysis and measurement of the radar cross-sectional area of a miniature aircraft. Radar cross-sectional area for miniature aircraft in advance were analyzed using an electromagnetic analysis tool, and an actual miniature aircraft was manufactured and measured in an anechoic chamber. When measuring, the old model was used as reference data for RCS(radar cross section) characteristics and applied to the test result data of the actual reduced model. The measurement method improved the accuracy of the measurement by applying time gating to remove the influence on the components scattered inside the anechoic chamber. The RCS test results of the reduced model showed relatively high RCS characteristics in the microwave band, as the previous analysis results. In the future, we plan to utilize the method of RCS analysis and measurement for the target of the radar in the VHF(Very High Frequency)/UHF(Ultra High Frequency) band with a relatively large wavelength.

• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.323-335
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• 2023

In causal analysis of high dimensional data, it is important to reduce the dimension of covariates and transform them appropriately to control confounders that affect treatment and potential outcomes. The augmented inverse probability weighting (AIPW) method is mainly used for estimation of average treatment effect (ATE). AIPW estimator can be obtained by using estimated propensity score and outcome model. ATE estimator can be inconsistent or have large asymptotic variance when using estimated propensity score and outcome model obtained by parametric methods that includes all covariates, especially for high dimensional data. For this reason, an ATE estimation using an appropriate dimension reduction method and semiparametric model for high dimensional data is attracting attention. Semiparametric method or sparse sufficient dimensionality reduction method can be uesd for dimension reduction for the estimation of propensity score and outcome model. Recently, another method has been proposed that does not use propensity score and outcome regression. After reducing dimension of covariates, ATE estimation can be performed using matching. Among the studies on ATE estimation methods for high dimensional data, four recently proposed studies will be introduced, and how to interpret the estimated ATE will be discussed.