Value Terms (value + term)

Distribution by Scientific Domains

Selected Abstracts

Shifted SSOR preconditioning technique for electromagnetic wave scattering problems

J. Q. Chen
Abstract To efficiently solve large dense complex linear system arising from electric field integral equations (EFIE) formulation of electromagnetic scattering problems, the multilevel fast multipole method (MLFMM) is used to accelerate the matrix-vector product operations. The symmetric successive over-relaxation (SSOR) preconditioner is constructed based on the near-field matrix of the EFIE and employed to speed up the convergence rate of iterative methods. This technique can be greatly improved by shifting the near-field matrix of the EFIE with the principle value term of the magnetic field integral equation (MFIE) operator. Numerical results demonstrate that this method can reduce both the number of iterations and the computational time significantly with low cost for construction and implementation of preconditioners. 2009 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 1035,1039, 2009; Published online in Wiley InterScience ( DOI 10.1002/mop.24254 [source]

Integrating genetic algorithms and spreadsheets: a capital budgeting application

R. H. Berry
The role of the tax system in generating interactions between the post-tax cash flows of different projects is discussed. When such interactions can occur, the capital budgeting process should be based around project combinations rather than individual projects. Evaluation of a project combination in net present value terms can easily be done using a spreadsheet. If the number of individual projects is large, then project combinations can be generated and an optimum combination of projects searched for using a genetic algorithm. The genetic algorithm approach has an advantage over alternative computational approaches, such as mixed integer programming, because of the more understandable representation of the problem it allows. Copyright 2007 John Wiley & Sons, Ltd. [source]

Endogenous Growth, Increasing Returns and Externalities: An Alternative Interpretation of the Evidence

Jesus Felipe
A number of recent papers have used aggregate production functions in an attempt to measure the degree of returns to scale and possible external effects in US manufacturing industries. In this paper I argue that the methods used and the results obtained are deceptive. The reason is that underlying every aggregate production function is the income accounting identity that relates output in value terms to the sum of wages and profits. This identity can be transformed, depending on the empirical paths of the wage and profit rates and of the factor shares, into different mathematical forms which resemble neoclassical production functions. Estimation of these forms, as is done in the literature discussed in the paper, poses serious problems for the interpretation of the results. [source]

Dynamic general equilibrium analysis of improved weed management in Australia's winter cropping systems,

Glyn Wittwer
A recent analysis indicated that the direct financial cost of weeds to Australia's winter grain sector was approximately $A1.2bn in 1998,1999. Costs of this magnitude represent a large recurring productivity loss in an agricultural sector that is sufficient to impact significantly on regional economies. Using a multi-regional dynamic computable general equilibrium model, we simulate the general equilibrium effects of a hypothetical successful campaign to reduce the economic costs of weeds. We assume that an additional $50m of R&D spread over five years is targeted at reducing the additional costs and reduced yields arising from weeds in various broadacre crops. Following this R&D effort, one-tenth of the losses arising from weeds is temporarily eliminated, with a diminishing benefit in succeeding years. At the national level, there is a welfare increase of $700m in discounted net present value terms. The regions with relatively high concentrations of winter crops experience small temporary macroeconomic gains. [source]