• Journal of the Korean Geotechnical Society
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• v.20 no.7
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• pp.207-215
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• 2004

In this study, the upper bound theory is applied to a reinforced slope to develop an limit state analysis method. As processing of this upper bound theory in formulating finite element, the basic idea of numerical method can be obtained from a macroscopic point of view with an anisotropic homogeneous material. The reinforced soil strength reliability depends on properties of reinforcements which consist of the interaction of interfaces between back fill and reinforcements. Both soil's mechanical property and overall behaviour of reinforced soil can be controlled via arranging geometry and relative proportions of reinforced soil. Therefore, the upper bound theory can not only predict the particular limit state action of reinforced soil slope but also is efficiently able to estimate the local plastic failure.

• KIEAE Journal
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• v.12 no.1
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• pp.105-112
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• 2012

When a building is planned and designed, the design should be able to minimize the cost during the whole life cycle of the building. This study has begun to analyze LCC about the alternative design which is applicable to renewable energy facility construction. It is reviewed domestic and foreign papers about the trend of LCC technology and it is determined the analytical method to analyze the LCC of renewable energy. Regarding the review of alternatives, it is chosen the three alternatives which are able to designed combing the renewable energy facilities and it is performed the LCC analysis about each alternative. Alternative 1 is Photovoltaic + Solar Thermal + Photovoltaic /Wind Power, Alternative 2 is Geothermal + Photovoltaic, and Alternative 3 is Photovoltaic + Solar Thermal. The LCC analysis is present value method, its analytical period is 40 years and it is applied 3.2% of real discount rate. As a result, it is proved that Alternative 1 and Alternative 3 are not able to collectible the early investment cost during the analytical period and Alternative 2 is analyzed that its pay-back period of early investment cost is about 31 years. As the final outcome of this study on case analysis, it is more advantageous to use the combination of Geothermal and Photovoltaic energy than to use the other combination in LCC aspect.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.440-458
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• 2019

Based on a 3D body data and pattern comparison analysis, this study developed a formal jacket pattern for men in their late 30s. In order to select the representative type of men in their late 30s, factor analysis and cluster analysis were conducted on data form 319 men, 35 to 39 years old using the anthropometric data from The 7th Size Korea (2015) as the representative body type. The surface of the body surface was developed using a 3D human shape of a male in his 30s in The 6th Size Korea (2010). Then the shape was changed to a flat pattern that confirmed the necessary elements for setting the shape and dimension. Cluster analysis revealed type B as the representative type because it showed the best shape characteristics for men in the late 30s. The drafting method of the final research pattern is as follows. Jacket length: stature/2.5cm, back length: stature/5+8.5cm (constant)], armhole depth: [stature/ 7-1.5cm (constant)], back width: [C/9+9.5cm (constant)]+1cm (ease), front width: [C/9+8.5cm (constant)]+1cm (ease), armscye depth: C/8, front waist darts: 1cm, front closure amount: 2cm.

• Progress in Medical Physics
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• v.28 no.3
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• pp.77-82
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• 2017

We proposed the objective ROC analysis method based on the setting of threshold value for evaluation of single photon emission computed tomography (SPECT) image. This proposed ROC analysis method uses the quantification computational threshold value to each signal on the SPECT image. The SPECT images for this study were acquired by using Monte Carlo n-particle extended simulation code (MCNPX, Ver. 2.6.0, Los Alamos National Laboratory, USA). The basic SPECT detectors and specific water phantom were realized in the simulation, and we could get the simulation results by the simulation operation. We tried to analyze the reconstructed images using threshold value application based objective ROC method. We can get the accuracy information of reconstructed region in the image. This proposed ROC technique can be helpful when we have to evaluate the weak signal for the NM image. In this study, the proposed threshold value based computational ROC analysis method can provide better objectivity than the conventional ROC analysis method.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.2
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• pp.83-100
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• 1980

This study was intended to computerize the structural analysis of two-dimensional continuum by finite element method, and to provide a preparatory basis for more sophisticated and more generalized computer programs of this kind. A computer program, applicable to any shape of two-dimensional continuum, was formulated on the basis of 16-degree-of- freedom rectangular element. Various computational aspects pertaining to the implementation of finite element method were reviewed and settled in the course of programming. The validity of the program was checked through several case studies. To assess the accuracy and the convergence characteristics of the method, the results computed by the program were compared with solutions by other methods, namely the analytical Navier's method and the framework method. Through actual programming and analysis of the computed results, the following facts were recognized; 1) The stiffness matrix should necessarily be assembled in a condensed form in order to make it possible to discretize the continuum into practically adequate number of elements without using back-up storage. 2) For minimization of solution time, in-core solution of the equilibrium equation is essential. LDLT decomposition is recommended for stiffness matrices condensed by the compacted column storage scheme. 3) As for rectangular plates, the finite element method shows better performances both in the accuracy and in the rate of convergence than the framework method. As the number of elements increases, the error of the finite element method approaches around 1%. 4) Regardless of the structural shape, there is a uniform tendency in convergence characteristics dependent on the shape of element. Square elements show the best performance. 5) The accuracy of computation is independent of the interpolation function selected.

• Journal of the Society of Disaster Information
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• v.3 no.1
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• pp.37-53
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• 2007

Various difficult problems occur due to insufficient bearing capacity or excessive settlements when constructing roads or large complexes. Accurate predictions on the final settlement and consolidation time can help in choosing the ground improvement method and thus enables to save time and expense of the whole project. Asaoka's method is probably the most frequently used for settlement prediction which are based on Terzaghi's one dimensional consolidation theory. Empirical formulae such as Hyperbolic method and Hoshino's method are also often used. However, it is known that the settlement predicted by these methods do not match with the actual settlements. Furthermore these methods cannot be used at design stage when there is no measured data. To find an elaborate method in predicting settlement in embankments using various test results and actual settlement data from domestic sites, Back-Propagation Neural Network(BPNN) and Recurrent Neural Network(RNN) were employed and the most suitable model structures were obtained. Predicted settlement values by the developed models were compared with the measured values as well as numerical analysis results. Analysis of the results showed that RNN yielded more compatible predictions with actual data than BPNN and predictions using cone penetration resistance were closer to actual data than predictions using SPT results. Also, it was found that the developed method were very competitive with the numerical analysis considering the number of input data, complexity and effort in modelling. It is believed that RNN using cone penetration test results can make a highly efficient tool in predicting settlements if enough field data can be obtained.

• Structural Engineering and Mechanics
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• v.18 no.3
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• pp.303-314
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• 2004

An artificial neural network (ANN) application is presented for flexural and axial vibration analysis of elastic beams with various support conditions. The first three natural frequencies of beams are obtained using multi layer neural network based back-propagation error learning algorithm. The natural frequencies of beams are calculated for six different boundary conditions via direct solution of governing differential equations of beams and Rayleigh's approximate method. The training of the network has been made using these data only flexural vibration case. The trained neural network, however, had been tested for cantilever beam (C-F), and both end free (F-F) in case the axial vibration, and clamped-clamped (C-C), and Guided-Pinned (G-P) support condition in case the flexural vibrations which were not included in the training set. The results found by using artificial neural network are sufficiently close to the theoretical results. It has been demonstrated that the artificial neural network approach applied in this study is highly successful for the purposes of free vibration analysis of elastic beams.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2179-2189
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• 2010

This paper deals with analytical techniques for performance evaluation of small scaled wind power generator with outer permanent magnet rotor. In part (1), using transfer relations theorem, magnetic field distribution characteristics by PM and armature reaction field are derived. Moreover, electrical parameters such as back-EMF, inductance and resistance are calculated from the obtained field characteristic equations. The proposed analytical techniques are validated by nonlinear finite element method using commercial software 'Maxwell' and performance experiments of the manufactured generator. In part (2), generating characteristics analysis such as constant speed characteristics and constant resistive load characteristics, and performance evaluation according to variation of wind speed will be accomplished using the derived electrical parameters.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.62-67
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• 1997

This paper reprdsents a new scheme of neural network control system analysis the robustues of robot manipulator using digital signal processors. Digtal signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In additions, DSPs are a s fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Durng past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. The proposed neuro network control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.120-126
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• 2007

A principal components analysis of the entire median HRIRs in the CIPIC HRTF database reveals that the individual HRIRs can be adequately reconstructed by a linear combination of several orthonormal basis functions. The basis functions cover the inter-individual and inter-elevation variations in median HRIRs. There are elevation-dependent tendencies in the weights of basis functions, and the basis functions can be ordered according to the magnitude of standard deviation of the weights at each elevation. We propose a HRIR customization method via tuning of the weights of 3 dominant basis functions corresponding to the 3 largest standard deviations at each elevation. Subjective listening test results show that both front-back reversal and vertical perception can be improved with the customized HRIRs.