• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.397-397
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• 2011

In a low aspect ratio (LAR) tokamak reactor with a superconducting toroidal field (TF) coil, the radial build of TF coil and the shield play a key role in determining the size of a reactor. For self-consistent determination of the reactor components and physics parameters, a system analysis code is coupled with one-dimensional radiation transport code. Conceptual design study of a compact superconducting LAR tokamak reactor with aspect ratio less than 2.5 was conducted and the optimum radial build was identified. It is shown that the use of an improved shielding material and high temperature superconducting magnets with high critical current density opens up the possibility of a fusion power plant with compact size and small re-circulating power simultaneously at low aspect ratio, and that by using an inboard neutron reflector instead of breeding blanket, tritium self-sufficiency is possible with outboard blanket only and thus compact sized reactor is viable.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.25-27
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• 2005

This paper deals with the comparison and analysis of brushless DC (BLDC) motor with radial and polar anisotropic plastic magnet. The open-circuit field distributions and back-emf for BLDC motor with polar plastic magnet are established analytically and the results are validated extensively by comparison with finite element (FE) analyses. On the basis of two dimensional (2-D) analytical solutions, this paper predicts open-circuit field characteristics according to design parameters and makes a comparison between BLDC motor with polar plastic magnet and it with radial plastic magnet in terms of required magnet volume and harmonic of air-gap flux density waveform.

• Solar Energy
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• v.2 no.1
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• pp.24-32
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• 1982

In this paper, temperature distributions in radial fin of rectangular profile for steady-state with no heat generation are obtained by one-dimensional analytical method, finite difference method and experiment respectively. Heat flow rate and fin efficiency from the fin model are obtained by analytical method. Consequently, temperature distributions in radial fin can certify that are similar to exact solution. From theoretical analysis, the effects according to heat flow rate and fin efficiency are related to variation of parameters which are fin thickness ${\delta}_o$, fin base temperature $T_o$, thermal conductivity K with same basic dimensions and the effects are studied and compared.

• Advances in concrete construction
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• v.15 no.2
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• pp.127-135
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• 2023

The present paper develops application of TSDT and MCST to analysis of a FG cylindrical micro-shell. The present model may be used as a sensor applicable in badminton net to detect contact. The radial and axial displacement components are described based on TSDT for more accurate analysis. The effect of small scales is accounted based on MCST. The solution is presented for a SS boundary condition to account the influence of various important parameters. A comparative analysis is presented to examine the effect of order of employed shear deformation theory on the axial and radial displacements.

• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.11 no.3
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• pp.9-17
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• 1982

In this paper, temperature distributions in radial fin of hyperbolic profile for steady -state with no heat generation are obtained by one-dimensional analytical method, finite difference method and experiment respectively. Heat flow rate and fin efficiency from the fin model are obtained by analytical method. To compare the exact solutions obtained by theoretical analysis with the results obtained by finite difference method, cylindrical shape is selected. Particularly, equations of finite difference method for cylindrical shape with irregular boundary are rearranged and formulated. Consequently, temperature distributions in radial fin can certify that are similar to exact solutions. From theoretical analysis, the effects according to heat flow rate and fin efficiency are related to variation of parameters which are fin thickness ${\delta}_o$, fin base temperature $T_o$, thermal conductivity K with same basic dimensions and the fleets are studied and compared.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.263-272
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• 2024

A model based on genetic algorithm optimization, GA-SVM, is proposed to warn university students of their status. This model improves the predictive effect of support vector machines. The genetic optimization algorithm is used to train the hyperparameters and adjust the kernel parameters, kernel penalty factor C, and gamma to optimize the support vector machine model, which can rapidly achieve convergence to obtain the optimal solution. The experimental model was trained on open-source datasets and validated through comparisons with random forest, backpropagation neural network, and GA-SVM models. The test results show that the genetic algorithm-optimized radial basis kernel support vector machine model GA-SVM can obtain higher accuracy rates when used for early warning in university learning.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.93-98
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• 2010

Recently, as digital photogrammetry bas been widely used in various fields including construction, it is also being applied to several industries. It is essential for interior orientation to determine accurate focal length of camera, lens distortion, location of principal point in order to apply high quality digital camera to digital photogrammetry. In this study we conducted interior orientation for zoom lens camera with regular time and zoom factors and analyzed change of radial distortion parameters and location of principal point to evaluate interior orientation stability. As a result, radial distortion parameters($k_1,k_2$) are converged into zero by increasing zoom factors. There are correlation between the change of location of point and zoom factors. The displacement of $x_p$, $y_p$ increase as zoom factors rise high.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1272-1278
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• 1999

A fault is considered as a variation of physical parameters; therefore the design of fault detection and identification(FDI) can be reduced to the parameter identification of a non linear system and to the association of the set of the estimated parameters with the mode of faults. Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to fault diagnosis. In this paper, we proposes an FDI system for nonlinear systems using neuro-fuzzy inference system. The proposed diagnostic system consists of two neuro-fuzzy inference systems which operate in two different modes (parallel and series-parallel mode). It generates the parameter residuals associated with each modes of faults which can be further processed by additional RBF (Radial Basis Function) network to identify the faults. The proposed FDI scheme has been tested by simulation on two-tank system.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.96.1-96.1
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• 2011

Halo coronal mass ejections (HCMEs) are major cause of the geomagnetic storms. To minimize the projection effect by coronagraph observations, we consider two CME cone models: an ice-cream cone model and an asymmetric cone model. These models allow us to determine three dimensional parameters of HCMEs such as radial speed, angular width, and the angle between sky plane and cone axis. In this study, we compare these parameters obtained from both models using 50 well-observed HCMEs from 2001 to 2002. Then we obtain the root mean square error (RMS error) between measured projection speeds and estimated ones for the models. As a result, we find that the radial speeds obtained from the models are well correlated with each other (R=0.89), and the correlation coefficient of angular width is 0.68. The correlation coefficient of the angle between sky plane and cone axis is 0.42, which is much smaller than what is expected. The reason may be due to the fact that the source locations of the asymmetric cone model are assumed to be near the center. The average RMS error of the asymmetric cone model (86.2km/s) is slightly smaller than that of the ice-cream cone model (88.6km/s).

• Computers and Concrete
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• v.29 no.6
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• pp.433-444
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• 2022

Concrete's compressive strength is widely studied in order to understand many qualities and the grade of the concrete mixture. Conventional civil engineering tests involve time and resources consuming laboratory operations which results in the deterioration of concrete samples. Proposing efficient non-destructive models for the prediction of concrete compressive strength will certainly yield advancements in concrete studies. In this study, the efficiency of using radial basis function neural network (RBFNN) which is not common in this field, is studied for the concrete compressive strength prediction. Complementary studies with back propagation neural network (BPNN), which is commonly used in this field, have also been carried out in order to verify the efficiency of RBFNN for compressive strength prediction. A total of 13 input parameters, including novel ones such as cement's and fly ash's compositional information, have been employed in the prediction models with RBFNN and BPNN since all these parameters are known to influence concrete strength. Three different train: test ratios were tested with both models, while different hidden neurons, epochs, and spread values were introduced to determine the optimum parameters for yielding the best prediction results. Prediction results obtained by RBFNN are observed to yield satisfactory high correlation coefficients and satisfactory low mean square error values when compared to the results in the previous studies, indicating the efficiency of the proposed model.