Fourier–Galerkin domain truncation method for Stokes’ first problem with Oldroyd four-constant liquid

AbstractUsing the Fourier–Galerkin method with domain truncation strategy, Stokes’ first problem for Oldroyd four-constant liquid on a semi-infinite interval is studied. It is shown that the Fourier–Galerkin approximations are convergent on the bounded interval. Moreover, an efficient and accurate algorithm based on the Fourier–Galerkin approximations is developed and implemented in solving the differential equations related to the present problem. Also, the effects of non-Newtonian parameters on the flow characteristics are obtained and analyzed. The method developed here is so general that it can be used to study the mathematical models that involve the flow of viscous fluids with shear rate-dependent properties: For example, models dealing with polymer processing, tribology & lubrication, and food processing

Fourier-Galerkin Domain Truncation Method For Stokes\u27 First Problem With Oldroyd Four-Constant Liquid

Using the Fourier-Galerkin method with domain truncation strategy, Stokes\u27 first problem for Oldroyd four-constant liquid on a semi-infinite interval is studied. It is shown that the Fourier-Galerkin approximations are convergent on the bounded interval. Moreover, an efficient and accurate algorithm based on the Fourier-Galerkin approximations is developed and implemented in solving the differential equations related to the present problem. Also, the effects of non-Newtonian parameters on the flow characteristics are obtained and analyzed. The method developed here is so general that it can be used to study the mathematical models that involve the flow of viscous fluids with shear rate-dependent properties: For example, models dealing with polymer processing, tribology & lubrication, and food processing. © 2007 Elsevier Ltd. All rights reserved

Automated detection of lung nodules in computed tomography images: a review

Lung nodules refer to a range of lung abnormalities the detection of which can facilitate early treatment for lung patients. Lung nodules can be detected by radiologists through examining lung images. Automated detection systems that locate nodules of various sizes within lung images can assist radiologists in their decision making. This paper presents a study of the existing methods on automated lung nodule detection. It introduces a generic structure for lung nodule detection that can be used to represent and describe the existing methods. The structure consists of a number of components including: acquisition, pre-processing, lung segmentation, nodule detection, and false positives reduction. The paper describes the algorithms used to realise each component in different systems. It also provides a comparison of the performance of the existing approaches.S.L.A. Lee, A.Z. Kouzani and E.J. H