• Journal of Fisheries and Marine Sciences Education
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• v.27 no.4
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• pp.963-972
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• 2015

This study examined the impact of variables(collaboration, convergence motive, convergence thinking) on the creativity problem solving of engineering college students. 522 students among engineering colleges in Pusan and Ulsan were sampled. For the statistical analysis, analysis of covariance structure by AMOS 18.0 was applied. Results from structural equation modeling analyses indicated that a hypothesized model produced a better fit to the data than a comparative structural model. The hypothesized model shows the following results. On the basis of the hypothesized model, collaboration effected to directly convergence motive and creative problem solving, and convergence motive effected to directly convergence thinking, convergence motive effected to directly creative problem solving, convergence thinking effected to directly creative problem solving, and collaboration effected to indirectly convergence thinking by convergence motive. Therefore this study suggested the collaboration, convergence motive and convergence thinking are significantly variables to facilitate the creative problem solving for knowledge fusion in engineering.

• Communications of the Korean Mathematical Society
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• v.33 no.3
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• pp.767-786
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• 2018

In this paper, we introduce new iterative schemes by using the modified Ishikawa iteration for two hybrid multivalued mappings in a Hilbert space. We then obtain weak convergence theorem under suitable conditions. We use CQ and shrinking projection methods with Ishikawa iteration for obtaining strong convergence theorems. Furthermore, we give examples and numerical results for supporting our main results.

• Bulletin of the Korean Mathematical Society
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• v.54 no.3
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• pp.917-933
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• 2017

In this paper, seven equivalent conditions of complete moment convergence and complete integral convergence for negatively orthant dependent (NOD, in short) sequences are shown under two cases: identical distribution and stochastic domination. The results obtained in the paper improve and generalize the corresponding ones of Liang et al. [10]). In addition, an extension of the Baum-Katz complete convergence theorem: six equivalent conditions of complete convergence is established.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.18-24
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• 2020

The purpose of this paper is an analysis of the difference between convergence majors and single majors in the convergence core competency and educational performance. We used survey data for the analysis of the convergence core competencies, the results of the midterm and final exams for the education performance. Analysis targets are 10 students in big data business intelligence at Seokyeong University as convergence majors and 11 students in business administration as single majors. The target course was an analysis of economic data provided in the second semester of 2019. And the lecture contents were analysis of big data using R programming. The survey was conducted on December 5, 2019. The convergence core competences were creative thinking, critical thinking, understanding convergence knowledge, problem solving ability, communication skills, cooperation ability, use of convergence tools, consideration, and responsibility. As results of homogeneity tests, we found that there was no significant difference in all competencies, but there were very significant differences in the educational performance evaluated by the midterm and final exams. Therefore we can see willingness to convergence of single majors was no different from that of convergence majors, but had not led to practice. It is desirable to activate and support convergence courses.

• Journal of the Chungcheong Mathematical Society
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• v.25 no.2
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• pp.267-275
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• 2012

We present new results for the local convergence of Newton's method to a unique solution of an equation in a Banach space setting. Under a flexible gamma-type condition [12], [13], we extend the applicability of Newton's method by enlarging the radius and decreasing the ratio of convergence. The results can compare favorably to other ones using Newton-Kantorovich and Lipschitz conditions [3]-[7], [9]-[13]. Numerical examples are also provided.

• The Pure and Applied Mathematics
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• v.15 no.1
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• pp.47-55
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• 2008

Local convergence results for three Newton-like methods in Banach space are provided. A comparison is given between the three convergence radii. Then we show that using the largest convergence radius we can pick an initial guess from with we start the corresponding iteration. It turns out that after a finite number of steps we can always use the iterate found as the starting guess for a faster method, since this iterate will be inside the convergence domain of the new method.

• Journal of the Korean Mathematical Society
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• v.54 no.3
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• pp.877-896
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• 2017

In this paper, the complete convergence and complete moment convergence for a class of random variables satisfying the Rosenthal type inequality are investigated. The sufficient and necessary conditions for the complete convergence and complete moment convergence are provided. As applications, the Baum-Katz type result and the Marcinkiewicz-Zygmund type strong law of large numbers for a class of random variables satisfying the Rosenthal type inequality are established. The results obtained in the paper extend the corresponding ones for some dependent random variables.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.13-23
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• 2009

Some strong convergence theorems of explicit iteration scheme for asymptotically nonexpansive semi-groups in Banach spaces are established. The results presented in this paper extend and improve some recent results in [T. Suzuki. On strong convergence to common fixed points of nonexpansive semigroups in Hilbert spaces, Proc. Amer. Math. Soc. 131(2002)2133-2136; H. K. Xu. A strong convergence theorem for contraction semigroups in Banach spaces, Bull. Aust. Math. Soc. 72(2005)371-379; N. Shioji and W. Takahashi. Strong convergence theorems for continuous semigroups in Banach spaces, Math. Japonica. 1(1999)57-66; T. Shimizu and W. Takahashi. Strong convergence to common fixed points of families of nonexpansive mappings, J. Math. Anal. Appl. 211(1997)71-83; N. Shioji and W. Takahashi. Strong convergence theorems for asymptotically nonexpansive mappings in Hilbert spaces, Nonlinear Anal. TMA, 34(1998)87-99; H. K. Xu. Approximations to fixed points of contraction semigroups in Hilbert space, Numer. Funct. Anal. Optim. 19(1998), 157-163.]

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.4
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• pp.239-246
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• 2003

Application of the filtered-x Least Mean Square(LMS) adaptive filter to active noise control requires to estimate the transfer characteristics between the output and the error signal of the adaptive controller. In this paper, we derive the filtered-x adaptive noise control algorithm and analyze its convergence behavior when the acoustic noise consists of multiple sinusoids. The results of the convergence analysis of the filtered-x LMS algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Simulation results are presented to support the theoretical convergence analysis.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.8
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• pp.856-867
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• 1990

In this paper, the convergence and the learning accuracy of the back-propagation (BP) method in neural network are investigated by 1) analyzing the reason for decelerating the convergence of BP method and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative and 2) proposing the modified logistic activation function by defining, the convergence factor based on the analysis. Learning on the output patterns of binary as well as analog forms are tested by the proposed method. In binary output patter, the test results show that the convergence is accelerated and the learning accuracy is improved, and the weights and thresholds are converged so that the stability of neural network can be enhanced. In analog output patter, the results show that with extensive initial transient phenomena the learning error is decreased according to the convergence factor, subsequently the learning accuracy is enhanced.