• New & Renewable Energy
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• v.7 no.3
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• pp.36-45
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• 2011

Prediction of demand for workforce in new and renewable energy is precondition for sustainable growth of an industry. The purpose of this research is to review prediction methods and case studies of workforce in new and renewable energy industry. This research compares the three methods in the focused on possibility of applying in renewable energy industry; survey, input-output and labor function estimation methods. Also, three cases are reviewed in the focused on applied method; Korea, America and Australia. As a result, the survey method was wildly used in the new and renewable industry. Also the improvement rates of work force are difference depending on the methodology. This result can be applied to set up the policy of human resource development of renewable energy.

• Journal of applied mathematics & informatics
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• v.4 no.1
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• pp.1-16
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• 1997

In this paper we study efficient parallel implementation for hybrid iterative methods BICGSTAB and BICGSTAB $(\ell)$ with ${Well}=2$ on the CRAY C90 and the efficiency of their parallel performance is evaluated. numerical experiments suggest that on the CRAY C90 a parallel inner product algorithm called PDOTB be used for the par-allelization of hybrid iterative methods containing sensitive values of inner products. Lastly it is shown that the number of iterations in which parallel hybrid iterative methods satisfy a certain convergence criterion depends on the number of processors to be used.

• Journal of applied mathematics & informatics
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• v.33 no.1_2
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• pp.61-76
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• 2015

In this paper, a fifth order extension of Potra's third order iterative method is proposed for solving nonlinear equations. A convergence theorem along with the error bounds is established. The method takes three functions and one derivative evaluations giving its efficiency index equals to 1.495. Some numerical examples are also solved and the results obtained are compared with some other existing fifth order methods. Next, the interval extension of both third and fifth order Potra's method are developed by using the concepts of interval analysis. Convergence analysis of these methods are discussed to establish their third and fifth orders respectively. A number of numerical examples are worked out using INTLAB in order to demonstrate the efficacy of the methods. The results of the proposed methods are compared with the results of the interval Newton method.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.139-159
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• 2000

In this manuscript we study perturbed Newton-like methods for the solution of nonlinear operator equations in a Banach space and their discretized versions in connection with the mesh independence principle. This principle asserts that the behavior of the discretized process is asymptotically the same as that for the original iteration and consequently, the number of steps required by the two processes to converge to within a given tolerance is essentially the same. So far this result has been proved by others using Newton's method for certain classes of boundary value problems and even more generally by considering a Lipschitz uniform discretization. In some of our earlierpapers we extend these results to include Newton-like methods under more general conditions. However, all previous results assume that the iterates can be computed exactly. This is mot true in general. That in why we use perturbed Newton-like methods and even more general conditions. Our results, on the one hand, extend, and on the other hand, make more practical and applicable all previous results.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.4
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• pp.162-172
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• 2021

This paper proposes stochastic methods to find an approximate solution for the L²-Wasserstein least squares problem of Gaussian measures. The variable for the problem is in a set of positive definite matrices. The first proposed stochastic method is a type of classical stochastic gradient methods combined with projection and the second one is a type of variance reduced methods with projection. Their global convergence are analyzed by using the framework of proximal stochastic gradient methods. The convergence of the classical stochastic gradient method combined with projection is established by using diminishing learning rate rule in which the learning rate decreases as the epoch increases but that of the variance reduced method with projection can be established by using constant learning rate. The numerical results show that the present algorithms with a proper learning rate outperforms a gradient projection method.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2733-2746
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• 2018

The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.21 no.1
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• pp.1-16
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• 2017

The Allen-Cahn equation is solved numerically by operator splitting Fourier spectral methods. The basic idea of the operator splitting method is to decompose the original problem into sub-equations and compose the approximate solution of the original equation using the solutions of the subproblems. The purpose of this paper is to characterize higher order operator splitting schemes and propose several higher order methods. Unlike the first and the second order methods, each of the heat and the free-energy evolution operators has at least one backward evaluation in higher order methods. We investigate the effect of negative time steps on a general form of third order schemes and suggest three third order methods for better stability and accuracy. Two fourth order methods are also presented. The traveling wave solution and a spinodal decomposition problem are used to demonstrate numerical properties and the order of convergence of the proposed methods.

• The Plant Pathology Journal
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• v.34 no.3
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• pp.236-240
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• 2018

Crop yield is critically related to the physiological responses and disease resistance of the crop, which could be strongly affected by high temperature conditions. We observed the changes in the growth of barley under higher than ambient air-temperature conditions using a temperature gradient field chamber (TGFC) during winter and spring. Before the stem extension stage of barley growth, Cladosporium sp. spontaneously appeared in the TGFC. The severity of disease became serious under warmer temperature conditions. Further, the stomata closed as the severity of the disease increased; however, stomatal conductance at the initial stage of disease was higher than that of the normal leaves. This was likely due to the Iwanov effect, which explains that stressed plants rapidly and transiently open their stomata before longer-term closure. In this study, we tested three optical methods: soil-plant analysis development (SPAD) chlorophyll index, photochemical reflectance index (PRI), and maximum quantum yield (Fv/Fm). These rapid evaluation methods have not been used in studies focusing on disease stress, although some studies have used these methods to monitor other stresses. These three indicative parameters revealed that diseased barley exhibited lower values of these parameters than normal, and with the increase in disease severity, these values declined further. Our results will be useful in efficient monitoring and evaluation of crop diseases under future warming conditions.

• Journal of Korean Medical classics
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• v.23 no.2
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• pp.235-270
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• 2010

This paper studies the main treatment methods, Ikgi(益氣) and Seung-yang(升陽) applied frequently by Lee Jema(李濟馬) on the exterior disease of So-eumin(少陰人), one of the four constitutions. The methodology of this paper is to understand the pharmacology of "Dong-uisusebowon(東醫壽世保元)" by examining the formulas applied by Lee Jema. I have examined the organization of formulas in "Dong-uisusebowon(東醫壽世保元)" beforehand to categorize the formulas applicable in this study according to an objective standard. I have analyzed the prescriptions applied to So-eumin exterior disease. As a result, I could see that in the case of Ulgwang(鬱狂) syndrome, Ikgi(益氣) and Seung-yang(升陽) methods were mainly applied, but as the disease progressed, Seung-yang(升陽) was withdrawn while Ikgi(益氣) was stressed. Likewise, in the case of Mang-yang(亡陽), both methods were mainly adopted, but as the patients got worse, the level of Seung-yang(升陽) was maintained and that of Ikgi(益氣) was elevated with the addition of Buja(附子). Through this process, we could verify the overall action of Ikgi(益氣), Seung-yang(升陽) and Buja(附子). Originally, the two methods of Ikgi(益氣) and Seung-yang(升陽) are intimately related, but by analyzing the overall functions of the two methods, we could see that Seung-yang(升陽) and Buja(附子) support the Yang gi of the interior of So-eumin, while Ikgi(益氣) resolves inner stagnation of Yang gi and emits the cold pathogen of the exterior. Also, in the course of treatment, Ikgi(益氣) could only be realized after securing Seung-yang(升陽).

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.65-80
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• 2008

Small scale time-course microarray experiments are those which have a small number of time points. They comprise about 80 percent of all time-course microarray experiments conducted up to 2005. Several statistical methods for the small scale time-course microarray experiments have been proposed. In this paper we applied three methods, namely, QR method, maSigPro method and STEM, to a real time-course microarray experiment which had six time points. We compared the performance of these three methods based on a simulation study and concluded that STEM outperformed, in general, in terms of power when the FDR was set to be 5%.