Support Vector Machines Study on English Isolated-Word-Error Classification and Regression

Abstract: A better understanding on word classification and regression could lead to a better detection and correction technique. We used different features or attributes to represent a machine-printed English word and support vector machines is used to evaluate those features into two class types of word: correct and wrong word. Our proposed support vectors model classified the words by using fewer words during the training process because those training words are to be considered as personalized words. Those wrong words could be replaced by correct words predicted by the regression process. Our results are very encouraging when compared with neural networks, Hamming distance or minimum edit distance technique; with further improvement in sight

Process modelling of the thermoset composites

The process modelling of autoclave composites has received much attention over the years. This thesis concentrates on two types of processes namely the prepreg processing method and the resin infusion processing method. The work focuses on the modelling and simulation of the resin flow, heat transfer and cure processes of the composites during processing. The Hercules 3501-6/AS4 composite was chosen for the simulation and the data for its thermal properties was obtained from Loos and Springer [12]. The composite is considered as a multilayered system consisting of prepregs or dry fibre layers with alternate layers of resin. A similarity analysis for the prepreg process was carried out allowing the velocity field, in both the prepreg and the resin, to be analytically determined. This then permitted the temperature and the degree of cure to be computed numerically. A similar, but different analysis was then carried out for the resin film infusion process, allowing the temperature and rate of cure to be computed directly. The simulation results of the prepreg case of Hercules 3501-6/AS4 were compared to known experimental results and good agreement has been found. Experimental work was performed on the flow dynamics of the resin infusion case and good agreement has also been observed.The process modelling of autoclave composites has received much attention over the years. This thesis concentrates on two types of processes namely the prepreg processing method and the resin infusion processing method. The work focuses on the modelling and simulation of the resin flow, heat transfer and cure processes of the composites during processing. The Hercules 3501-6/AS4 composite was chosen for the simulation and the data for its thermal properties was obtained from Loos and Springer [12]. The composite is considered as a multilayered system consisting of prepregs or dry fibre layers with alternate layers of resin. A similarity analysis for the prepreg process was carried out allowing the velocity field, in both the prepreg and the resin, to be analytically determined. This then permitted the temperature and the degree of cure to be computed numerically. A similar, but different analysis was then carried out for the resin film infusion process, allowing the temperature and rate of cure to be computed directly. The simulation results of the prepreg case of Hercules 3501-6/AS4 were compared to known experimental results and good agreement has been found. Experimental work was performed on the flow dynamics of the resin infusion case and good agreement has also been observed

The higher accuracy fourth-order IADE algorithm

This study develops the novel fourth-order iterative alternating decomposition explicit (IADE)method of Mitchell and Fair weather (IADEMF4) algorithm for the solution of the one-dimensional linear heat equation with Dirichlet boundary conditions.The higher order finite difference scheme is developed by representing the spatial derivative in the heat equation with the fourth-order finite difference Crank-Nicolson approximation.This leads to the formation of pentadiagonal matrices in the systems of linear equations. The algorithm also employs the higher accuracy of the Mitchell and Fair weather variant.Despite the scheme’s higher computational complexity, experimental results show that it is not only capable of enhancing the accuracy of the original corresponding method of second-order (IADEMF2), but its solutions are also in very much agreement with the exact solutions. Besides, it is unconditionally stable and has proven to be convergent. The IADEMF4 is also found to be more accurate, more efficient, and has better rate of convergence than the bench marked fourth-order classical iterative methods, namely, the Jacobi (JAC4), the Gauss-Seidel (GS4), and the successive over-relaxation (SOR4) method