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International Journal of Engineering, Mathematical and Physical Sciences

ISSN: 2517-9934

Total 8 content found

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Positive Solutions for a Class of Semipositone Discrete Boundary Value Problems with Two Parameters

Year: 2010 Volume: 4 Issue: 10 1388 - 1394 Pages

Abstract: In this paper, the existence, multiplicity and noexistence of positive solutions for a class of semipositone discrete boundary value problems with two parameters is studied by applying nonsmooth critical point theory and sub-super solutions method.

A New Approach for Classifying Large Number of Mixed Variables

Year: 2010 Volume: 4 Issue: 10 1382 - 1387 Pages

Abstract: The issue of classifying objects into one of predefined groups when the measured variables are mixed with different types of variables has been part of interest among statisticians in many years. Some methods for dealing with such situation have been introduced that include parametric, semi-parametric and nonparametric approaches. This paper attempts to discuss on a problem in classifying a data when the number of measured mixed variables is larger than the size of the sample. A propose idea that integrates a dimensionality reduction technique via principal component analysis and a discriminant function based on the location model is discussed. The study aims in offering practitioners another potential tool in a classification problem that is possible to be considered when the observed variables are mixed and too large.

Cubic Trigonometric B-Spline Applied to Linear Two-Point Boundary Value Problems of Order Two

Year: 2010 Volume: 4 Issue: 10 1376 - 1381 Pages

Abstract: Linear two-point boundary value problems of order two are solved using cubic trigonometric B-spline interpolation method (CTBIM). Cubic trigonometric B-spline is a piecewise function consisting of trigonometric equations. This method is tested on some problems and the results are compared with cubic B-spline interpolation method (CBIM) from the literature. CTBIM is found to approximate the solution slightly more accurately than CBIM if the problems are trigonometric.

Blind Image Deconvolution by Neural Recursive Function Approximation

Year: 2010 Volume: 4 Issue: 10 1368 - 1375 Pages

Abstract: This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.

A Comparison of Some Splines-Based Methods for the One-dimensional Heat Equation

Year: 2010 Volume: 4 Issue: 10 1364 - 1367 Pages

Abstract: In this paper, collocation based cubic B-spline and extended cubic uniform B-spline method are considered for solving one-dimensional heat equation with a nonlocal initial condition. Finite difference and θ-weighted scheme is used for time and space discretization respectively. The stability of the method is analyzed by the Von Neumann method. Accuracy of the methods is illustrated with an example. The numerical results are obtained and compared with the analytical solutions.

A Cell-centered Diffusion Finite Volume Scheme and it's Application to Magnetic Flux Compression Generators

Year: 2010 Volume: 4 Issue: 10 1358 - 1363 Pages

Abstract: A cell-centered finite volume scheme for discretizing diffusion operators on distorted quadrilateral meshes has recently been designed and added to APMFCG to enable that code to be used as a tool for studying explosive magnetic flux compression generators. This paper describes this scheme. Comparisons with analytic results for 2-D test cases are presented, as well as 2-D results from a test of a "realistic" generator configuration.

Feasibility Investigation of Near Infrared Spectrometry for Particle Size Estimation of Nano Structures

Year: 2010 Volume: 4 Issue: 10 1355 - 1357 Pages

Abstract: Determination of nano particle size is substantial since the nano particle size exerts a significant effect on various properties of nano materials. Accordingly, proposing non-destructive, accurate and rapid techniques for this aim is of high interest. There are some conventional techniques to investigate the morphology and grain size of nano particles such as scanning electron microscopy (SEM), atomic force microscopy (AFM) and X-ray diffractometry (XRD). Vibrational spectroscopy is utilized to characterize different compounds and applied for evaluation of the average particle size based on relationship between particle size and near infrared spectra [1,4] , but it has never been applied in quantitative morphological analysis of nano materials. So far, the potential application of nearinfrared (NIR) spectroscopy with its ability in rapid analysis of powdered materials with minimal sample preparation, has been suggested for particle size determination of powdered pharmaceuticals. The relationship between particle size and diffuse reflectance (DR) spectra in near infrared region has been applied to introduce a method for estimation of particle size. Back propagation artificial neural network (BP-ANN) as a nonlinear model was applied to estimate average particle size based on near infrared diffuse reflectance spectra. Thirty five different nano TiO2 samples with different particle size were analyzed by DR-FTNIR spectrometry and the obtained data were processed by BP- ANN.

On Uniqueness and Continuous Dependence in the Theory of Micropolar Thermoelastic Mixtures

Year: 2010 Volume: 4 Issue: 10 1350 - 1354 Pages

Abstract: This paper studies questions of continuous data dependence and uniqueness for solutions of initial boundary value problems in linear micropolar thermoelastic mixtures. Logarithmic convexity arguments are used to establish results with no definiteness assumptions upon the internal energy.