Earticle

본 연구에서는 원형 박판 구조물의 안정성에 대하여 해석 하였다. 임계하중은 하중을 점차적으로 증가하여 구조물이 파괴가 발생하여 안정성을 상실 하는 상태에서 가장 작은 하중을 의미한다. 판구조의 안정성을 임계하중의 크기로 기초를 두고 해석 하였다. 원형 박판구조의 차분해석은 일반 판구조와 같으므로 최근에 많은 연구의 대상이 되어왔다. 차분법은 복잡한 구조물에서도 물론, 다양한 경계조건을 포함하는 문제에 이르기까지 효과적인 수치방법이다. 본 연구에서는 기본 박판구조의 지배방정식을 유도하고 차분화 하여 직접적으로 접근하였다. 원 둘레 의 지점이 힌지 받침으로, 등분포 하중을 받고 있는 박판을 기하학적 비선형 해석으로 수행하여 원형 박판의 처짐 및 응력을 해석 하였다.

Merton’s (1974) model is one of the most important models for analyzing the credit risk of a company. This paper develops an iteration method for implementing Merton’s (1974) model and designs a simulation study to compare our method with the traditional implementation method. This paper also shows some drawbacks of the traditional implementation method.

In this paperwe have considered an integro-differential equation which describes the charged particle motion for certain configurations of oscillating magnetic fields. This equation contains variable coefficients with large expressions which complicate the application of any numerical method. We have used variational iteration method to find its numerical solution by developing MATHEMATICA modulae and solved a number of numerical examples. The results show high accuracy and efficiency ofour approach.

Most of the localization algorithms have performed localization utilizing absolute point-to-point distance estimates. If the sensor network is not cooperative, there’s no information about the strength of the original signal so that the location of a target node is hard to be found. It allows ratiometric location algorithm to be proposed. GPS algorithm give accurate location of unknown node, however it needs the absolute distance between the nodes. Ratiometric GPS iteration (RGPSi) localization method combines GPS and ratiometric algorithm for utilizing the benefits of two algorithms. RGPSi algorithm results in a little more position error and longer iteration than GPS algorithm. We introduce the method that helps ratiometric GPS iteration algorithm to be more accurate and reduce the iteration numbers through the angle of arrival localization algorithm. Not to add computation complexity to the RGPSi algorithm, nonlinear angle to location relationship is made linear. The proposed RGPSi combined with AOA algorithm shows more accurate position errors and less iteration numbers.

A novel image restoration method based on homology continuity is proposed in this paper. We view images as a collection of gray scale points, taking advantage of the homology continuity principle to combine each point and its fuzzy point derived by drop mass function to constitute the path direction and obtain distinct restore points. The gather of all the restore points is the sharply focused image of the original image. At last, we found every picture by iteration method is clearer than the last by experiment with the method proposed in the paper. The result verifies its feasibility.

In this paper we present a new iteration method for solving optimization problems governed by partial differential equations. We generalize the existing methods such as simple gradient methods and pseudo-time methods to get an efficient iteration method. Numerical tests show that the convergence of the new iteration method is much faster than those of the pseudo-time methods especially when the parameter $\sigma$ in the cost functional is small.

This paper studies the iteration method of solving a type of second-order three-point boundary value problem with non-linear term f, which depends on the first order derivative. By using the upper and lower method, we obtain the sufficient conditions of the existence and uniqueness of solutions. Furthermore, the monotone iterative sequences generated by the method contribute to the minimum solution and the maximum solution. And the error estimate formula is also given under the condition of unique solution. We apply the solving process to a special boundary value problem, and the result is interesting.

The aim of this paper is to present an explicit iteration method for finding a common fixed point of a finite family of strictly pseudocon-tractive mappings defined on q-uniformly smooth and uniformly convex Banach spaces.

Let K be a nonempty closed bounded convex subset of an arbitrary smooth Banach space X and T : KlongrightarrowK be a strictly hemi-contractive operator. Under some conditions we obtain that the Mann iteration method with errors both converges strongly to a unique fixed point of T and is almost T-stable on K. The results presented in this paper generalize the corresponding results in [l]-[7], [20] and others.

Let K be a nonempty convex subset of an arbitrary Banach space X and $T\;:\;K\;{\rightarrow}\;K$ be a uniformly continuous strictly hemi-contractive operator with bounded range. We prove that certain Ishikawa iteration scheme with errors both converges strongly to a unique fixed point of T and is almost T-stable on K. We also establish similar convergence and almost stability results for strictly hemi-contractive operator $T\;:\;K\;{\rightarrow}\;K$, where K is a nonempty convex subset of arbitrary uniformly smooth Banach space X. The convergence results presented in this paper extend, improve and unify the corresponding results in Chang [1], Chang, Cho, Lee & Kang [2], Chidume [3, 4, 5, 6, 7, 8], Chidume & Osilike [9, 10, 11, 12], Liu [19], Schu [25], Tan & Xu [26], Xu [28], Zhou [29], Zhou & Jia [30] and others.

Let K be a nonempty convex subset of an arbitrary Banach space X and $T\;:\;K\;{\rightarrow}\;K$ be a uniformly continuous strictly hemi-contractive operator with bounded range. We prove that certain Ishikawa iteration scheme with errors both converges strongly to a unique fixed point of T and is almost T-stable on K. We also establish similar convergence and almost stability results for strictly hemi-contractive operator $T\;:\;K\;{\rightarrow}\;K$, where K is a nonempty convex subset of arbitrary uniformly smooth Banach space X. The convergence results presented in this paper extend, improve and unify the corresponding results in Chang [1], Chang, Cho, Lee & Kang [2], Chidume [3, 4, 5, 6, 7, 8], Chidume & Osilike [9, 10, 11, 12], Liu [19], Schu [25], Tan & Xu [26], Xu [28], Zhou [29], Zhou & Jia [30] and others.

Let E be a real q-uniformly smooth Banach space which admits a weakly sequentially continuous duality map, and K a nonempty closed convex subset of E. Let T : K -> K be a mapping such that $F(T)\;=\;{x\;{\in}\;K\;:\;Tx\;=\;x}\;{\neq}\;0$ and (I - T) satisfies the accretive-type condition: $<x-Tx,j(x-x^*)>\;{\geq}\;{\lambda}$\mid$$\mid$x-Tx$\mid$$\mid$^2$, for all $x\;{\in}\;K,\;x^*\;{\in}\;F(T)$ and for some ${\lambda}\;>\;0$. The weak and strong convergence of the Ishikawa iteration method to a fixed point of T are investigated. An application of our results to the approximation of a solution of a certain linear operator equation is also given. Our results extend several important known results from the Mann iteration method to the Ishikawa iteration method. In particular, our results resolve in the affirmative an open problem posed by Naimpally and Singh (J. Math. Anal. Appl. 96 (1983), 437-446).

The induced currents on a uniform resistive strip by a H-polarized plane wave are obtained by the iteration method in the spectral domain and compared with the results by the moment method.

This paper presents an analytical approximate solution for a class of nonlinear quadratic optimal control problems. The proposed method consists of a Variational Iteration Method (VIM) together with a shooting method like procedure, for solving the extreme conditions obtained from the Pontryagin's Maximum Principle (PMP). This method is applicable for a large class of nonlinear quadratic optimal control problems. In order to use the proposed method, a control design algorithm with low computational complexity is presented. Through the finite iterations of algorithm, a suboptimal control law is obtained for the nonlinear optimal control problem. Two illustrative examples are given to demonstrate the simplicity and efficiency of the proposed method.

A full multigrid scheme was used in computing some eigenvalues of the Laplace eigenvalues problem with the Dirichlet bound-ary condition. We get a system of algebraic equations with an aid of finite difference method and apply subspace iteration method to the system to compute first some eigenvalues. The result shows that this is very effective in calculating some eigenvalues of this problem.

Calculating minimal cut sets is a typical quantification method used to evaluate the top event probability for a fault tree. If minimal cut sets cannot be calculated or if the accuracy of the quantification result is in doubt, the Monte Carlo method can provide an alternative for fault tree quantification. The Monte Carlo method for fault tree quantification tends to take a long time because it repeats the calculation for a large number of samples. Herein, proposal is made to improve the quantification algorithm of a fault tree with circular logic. We developed a top-down iteration algorithm that combines the characteristics of the top-down approach and the iteration approach, thereby reducing the computation time of the Monte Carlo method.

F-18-FPCIT는 뇌 선조체에 주로 분포된 도파민 운반체에 강한 친화력을 보이며, 이는 파킨슨 씨 병의 진단에 유용한 진단적 정보를 제공한다. 본 연구에서는 iteration과 subset에 따른 영상의 변화를 관찰하고 적정한 iteration과 subset의 범위를 제안해 보고자 한다. 영상의 획득은 ACR 팬텀과 뇌 질환이 없는 정상인의 뇌 영상을 획득하였다. 정상인의 뇌영상은 F-18-FPCIT를 정맥주사 후 3시간째 획득하였으며, iteration과 subset의 조건을 5가지로 구분하여 영상을 재구성하였다. 영상의 분석은 동일한 위치에 같은 크기의 ROI를 그려 평균, 최대, 최소의 SUV를 측정하였고, 이를 바탕으로 표준편차, 변이계수를 계산하였다. 또한 팬텀영상에서는 각 조건별 열소와 냉소의 SUV를 비교하여 어떠한 조건에서 실제와 가장 비슷한 SUV ratio를 재현하는지 조사하였다. 위 실험에서 얻어진 값은 Spearman test를 통해 유의성을 유무를 판별하였다. 따라 SUV는 증가하였고 이러한 추세는 Spearman test에서 유의성을 나타내었다. 표준편차 역시 iteration, subset조건이 증가함에 따라 값의 증가를 보였다. 산출된 값들은 통계적으로 유의하였다. 팬텀 연구에서는 6 iteraions, 16 iterations 에서 실제와 가장 비슷한 SUV ratio를 재현하였다. 하지만 iteration, subset 조건별로 얻어진 SUV ratio들은 통계적으로 유의하지 않았다.

Purpose: F-18-FPCIT that shows strong familiarity with DAT located at a neural terminal site offers diagnostic information about DAT density state in the region of the striatum especially Parkinson's disease. In this study, we altered the iteration and subset and measured SUV${\pm}$SD and Contrasts from phantom images which set up to specific iteration and subset. So, we are going to suggest the appropriate range of the iteration and subset. Materials and Methods: This study has been performed with 10 normal volunteers who don't have any history of Parkinson's disease or cerebral disease and Flangeless Esser PET Phantom from Data Spectrum Corporation. $5.3{\pm}0.2$ mCi of F-18-FPCIT was injected to the normal group and PET Phantom was assembled by ACR PET Phantom Instructions and it's actual ratio between hot spheres and background was 2.35 to 1. Brain and Phantom images were acquired after 3 hours from the time of the injection and images were acquired for ten minutes. Basically, SIEMENS Bio graph 40 True-point was used and True-X method was applied for image reconstruction method. The iteration and Subset were set to 2 iterations, 8 subsets, 3 iterations, 16 subsets, 6 iterations, 16 subsets, 8 iterations, 16 subsets and 8 iterations, 21 subsets respectively. To measure SUVs on the brain images, ROIs were drawn on the right Putamen. Also, Coefficient of variance (CV) was calculated to indicate the uniformity at each iteration and subset combinations. On the phantom study, we measured the actual ratio between hot spheres and back ground at each combinations. Same size's ROIs were drawn on the same slide and location. Results: Mean SUVs were 10.60, 12.83, 13.87, 13.98 and 13.5 at each combination. The range of fluctuation by sets were 22.36%, 10.34%, 1.1%, and 4.8% respectively. The range of fluctuation of mean SUV was lowest between 6 iterations 16 subsets and 8 iterations 16 subsets. CV showed 9.07%, 11.46%, 13.56%, 14.91% and 19.47% respectively. This means that the numerical value of the iteration and subset gets higher the image's uniformity gets worse. The range of fluctuation of CV by sets were 2.39, 2.1, 1.35, and 4.56. The range of fluctuation of uniformity was lowest between 6 iterations, 16 subsets and 8 iterations, 16 subsets. In the contrast test, it showed 1.92:1, 2.12:1, 2.10:1, 2.13:1 and 2.11:1 at each iteration and subset combinations. A Setting of 8 iterations and 16 subsets reappeared most close ratio between hot spheres and background. Conclusion: Findings on this study, SUVs and uniformity might be calculated differently caused by variable reconstruction parameters like filter or FWHM. Mean SUV and uniformity showed the lowest range of fluctuation at 6 iterations 16 subsets and 8 iterations 16 subsets. Also, 8 iterations 16 subsets showed the nearest hot sphere to background ratio compared with others. But it can not be concluded that only 6 iterations 16 subsets and 8 iterations 16 subsets can make right images for the clinical diagnosis. There might be more factors that can make better images. For more exact clinical diagnosis through the quantitative analysis of DAT density in the region of striatum we need to secure healthy people's quantitative values.

A nonlinear iterative scheme developed to reduce the computing time of the AFEN method was tested and applied to two benchmark problems. The new nonlinear method for the AFEN method is based on solving two-node problems and use of two nonlinear correction factors at every interface instead of one factor in the conventional scheme. The use of two correction factors provides higher-order accurate interface noes as well as currents which are used as the boundary conditions of the two-node problem. The numerical results show that this new method gives exactly the same solution as that of the original AEFEN method and the computing time is significantly reduced in comparison with the original AFEN method.

A numerically stable technique to remove tile limitation in choosing a shift in the subspace iteration method with shift is presented. A major difficulty of the subspace iteration method with shift is that because of singularity problem, a shift close to an eigenvalue can not be used, resulting in slower convergence. This study selves the above singularity problem using side conditions without sacrifice of convergence. The method is always nonsingular even if a shiht is an eigenvalue itself. This is one of tile significant characteristics of the proposed method. The nonsingularity is proved analytically. The convergence of the proposed method is at least equal to that of the subspace iteration method with shift, and the operation counts of above two methods are almost the same when a large number of eigenpairs are required. To show the effectiveness of the proposed method, two numerical examples are considered

In conventional hydrothermal coordination problem, the lambda-gamma iteration method is generally used for generation schedule. The procedure of classical lambda-gamma iteration method consists of 3 main loops and it is very complex. Therefore, it needs many iterative calculations. This paper proposes an advanced hydrothermal algorithm based on newly developed lambda-gamma iteration method. As lambda calculation loop is removed in the newly developed iteration method, iterative calculations are reduced and whole procedure is simplified. The proposed algorithm is verified on simple system.