• Communications of Mathematical Education
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• v.34 no.3
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• pp.325-354
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• 2020

This study utilized longitudinal data from the 2013 year (Secondary Middle School) to 2017 year (Secondary High School) of the Seoul Education Termination Study. Using the latent growth model and the piecewise growth model, we investigated the changes in mathematics academic achievement, internal factors(self-concept, self-control, self-assessment of life satisfaction), and external factors(school climate, guardians) as students' grades increased, and examined whether internal factors and external factors influence the changes in mathematics academic achievement. We examined whether internal and external factors influence the change in academic achievement. As a result of analysis, it was found that mathematics academic achievement remained unchanged from the first grade of middle school to the second grade of middle school, and steadily increased from the second grade of middle school to the first grade of high school, and then decreased slightly in the second grade of high school. The internal and external factors had little change. It has been found that self-concept, self-control as internal factors, and school climate as external factors influence changes in mathematics academic achievement.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.10a
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• pp.292-296
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• 2008

A new method of evaluating critical damage values of commercial materials is presented in this paper. The method is based on the previous study of the methodology [1] of acquisition of true stress-strain curves or flow stress curves over large strain from the tensile test in which the flow stress is described by the Hollomon law-like form, that is, by the strain dependent strength coefficient and the strain hardening exponent. The strain hardening exponent is calculated from the true strain at the necking point to meet the Considere condition. The strength coefficient is assumed to be constant before necking and represented by a piecewise linear function of strain after necking. With the predicted flow stress, a tensile test is simulated by a rigid-plastic finite element method with higher accuracy of less than 0.5% error between experiments and predictions. The instant when the fracture begins and thus the critical damage is obtained is determined by observing the stress variation at the necked region. It is assumed that the fracture due to damage begins when the pattern of stress around the necked region changes radically. The method is applied to evaluate the critical damage of a low carbon steel.

• Structural Engineering and Mechanics
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• v.73 no.6
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• pp.651-666
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• 2020

In this study, the spatial variation mechanisms of large far-field earthquakes at engineering scales are first investigated with data from the 2008 Ms 8.0 Wenchuan earthquake. And a novel 'coherency cut-off frequency' is proposed to distinguish the spatial variations in ground motions in the low-frequency and high-frequency ranges. Then, a practical piecewise coherency model is developed to estimate and characterize the spatial variation in earthquake ground motions, including the effects of source-to-site distances, site conditions and neighboring topography on these variations. Four particular earthquake records from dense seismograph arrays are used to investigate values of the coherency cut-off frequency for different source-to-site distances. On the basis of this analysis, the model is established to simulate the spatial variations, whose parameters are suitable for both near- and far-field earthquake conditions. Simulations are conducted to validate the proposed model and method. The results show that compared to the existing models, the proposed model provides an effective method for simulating the spatial correlations of ground motions at local sites with known source-to-site distances.

• Journal of Ocean Engineering and Technology
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• v.31 no.3
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• pp.189-195
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• 2017

A three-dimensional higher order boundary element method based on the B-spline is presented. The method accurately models piecewise continuous bodies and induced velocity potentials using B-spline tensor product representations, and it is capable of obtaining accurate pointwise values for the potential and its derivatives, especially in the trailing edge and tip region of the lift generating body, which may be difficult or impossible to evaluate with constant panel methods. In addition, we implement a wake roll-up and examine the tip vortex formation in the near wake region. The results are compared with existing numerical results and the results of experiments performed out at the cavitation tunnel of Chungnam National University.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.577-582
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• 2002

Neural network can be trained to approximate an arbitrary nonlinear function of multivariate data like the mini-mill crown values in Automatic Shape Control. The trained weights of neural network can evaluate or generalize the process data outside the training vectors. Sometimes, the blind modeling of the process data is necessary to compare with the scattered analytical model of mini-mill process in isolated electro-mechanical forms. To come up with a viable model, we propose the blind neural-based range-division domain-clustering piecewise-linear modeling scheme. The basic ideas are: 1) dividing the range of target data, 2) clustering the corresponding input space vectors, 3)training the neural network with clustered prototypes to smooth out the convergence and 4) solving the resulting matrix equations with a pseudo-inverse to alleviate the ill-conditioning problem. The simulation results support the effectiveness of the proposed scheme and it opens a new way to the data analysis technique. By the comparison with the statistical regression, it is evident that the proposed scheme obtains better modeling error uniformity and reduces the magnitudes of errors considerably. Approximatly 10-fold better performance results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1785-1801
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• 2017

In recent years, image encryption algorithms have been developed rapidly in order to ensure the security of image transmission. With the assistance of our previous work, this paper proposes a novel chaotic image encryption algorithm based on self-adaptive model and feedback mechanism to enhance the security and improve the efficiency. Different from other existing methods where the permutation is performed by the self-adaptive model, the initial values of iteration are generated in a novel way to make the distribution of initial values more uniform. Unlike the other schemes which is on the strength of the feedback mechanism in the stage of diffusion, the piecewise linear chaotic map is first introduced to produce the intermediate values for the sake of resisting the differential attack. The security and efficiency analysis has been performed. We measure our scheme through comprehensive simulations, considering key sensitivity, key space, encryption speed, and resistance to common attacks, especially differential attack.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.29-51
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• 2004

In this paper, we propose a new mixed finite element method, called the characteristics-mixed method, for approximating the solution to Burgers' equation. This method is based upon a space-time variational form of Burgers' equation. The hyperbolic part of the equation is approximated along the characteristics in time and the diffusion part is approximated by a mixed finite element method of lowest order. The scheme is locally conservative since fluid is transported along the approximate characteristics on the discrete level and the test function can be piecewise constant. Our analysis show the new method approximate the scalar unknown and the vector flux optimally and simultaneously. We also show this scheme has much smaller time-truncation errors than those of standard methods. Numerical example is presented to show that the new scheme is easily implemented, shocks and boundary layers are handled with almost no oscillations. One of the contributions of the paper is to show how the optimal error estimates in $L^2(\Omega)$ are obtained which are much more difficult than in the standard finite element methods. These results seem to be new in the literature of finite element methods.

• Nuclear Engineering and Technology
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• v.24 no.3
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• pp.319-328
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• 1992

The Galerkin formulation of the finite element method is applied to the integral law of the first-order form of the one-group neutron transport equation in one-dimensional spherical geometry. Piecewise linear or quadratic Lagrange polynomials are utilized in the integral law for the angular flux to establish a set of linear algebraic equations. Numerical analyses are performed for the scalar flux distribution in a heterogeneous sphere as well as for the criticality problem in a uniform sphere. For the criticality problems in the uniform sphere, the results of the finite element method, with the use of continuous finite elements in space and angle, are compared with the exact solutions. In the heterogeneous problem, the scalar flux distribution obtained by using discontinuous angular and spatical finite elements is in good agreement with that from the ANISN code calculation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3112-3127
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• 2018

Since time series clustering is performed without prior information, it is used for exploratory data analysis. In particular, clusters of time series with similar shapes can be used in various fields, such as business, medicine, finance, and communications. However, existing time series clustering algorithms have a problem in that time series with different shapes are included in the clusters. The reason for such a problem is that the existing algorithms do not consider the limitations on the size of the generated clusters, and use a dimension reduction method in which the information loss is large. In this paper, we propose a method to alleviate the disadvantages of existing methods and to find a better quality of cluster containing similarly shaped time series. In the data preprocessing step, we normalize the time series using z-transformation. Then, we use piecewise aggregate approximation (PAA) to reduce the dimension of the time series. In the clustering step, we use density-based spatial clustering of applications with noise (DBSCAN) to create a precluster. We then use a modified K-means algorithm to refine the preclusters containing differently shaped time series into subclusters containing only similarly shaped time series. In our experiments, our method showed better results than the existing method.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.6
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• pp.607-612
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• 2012

The wear problem of wheel flange occurs at sharp curves of rail. This paper proposes a procedure for optimum design of a wheel profile wherein flange wear is reduced by improving an interaction between wheel and rail. Application of optimization method to design problem mainly depends on characteristics of design space. This paper compared local optimization method with global optimization according to sensitivity value of objective function for design variables to find out which optimization method is appropriable to minimize wear of wheel flange. Wheel profile is created by a piecewise cubic Hermite interpolating polynomial and dynamic performances are analyzed by a railway dynamic analysis program, VAMPIRE. From the optimization results, it is verified that the global optimization method such as genetic algorithm is more suitable to wheel profile optimization than the local optimization of SQP (Sequential Quadratic Programming) in case of considering the lack of empirical knowledge for initial design value.