A relationship is found between the solutions to the quadratic matrix equation X (T) DX + AX + X (T) B + C = 0, where all the matrix coefficients are n x n matrices, and the neutral subspaces of the 2n x 2n matrix . T...
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A relationship is found between the solutions to the quadratic matrix equation X (T) DX + AX + X (T) B + C = 0, where all the matrix coefficients are n x n matrices, and the neutral subspaces of the 2n x 2n matrix . This relationship is used to design an algorithm for solving matrix equations of the indicated type. Numerical results obtained with the help of the proposed algorithm are presented.
In this paper, we consider an elliptic equation with strongly varying coefficients. Interest in the study of these equations is connected with the fact that this type of equation is obtained when using the fictitious ...
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In this paper, we consider an elliptic equation with strongly varying coefficients. Interest in the study of these equations is connected with the fact that this type of equation is obtained when using the fictitious domain method. In this paper, we propose a special method for the numerical solution of elliptic equations with strongly varying coefficients. A theorem is proved for the rate of convergence of the iterative process developed. A computational algorithm and numerical calculations are developed to illustrate the effectiveness of the proposed method.
Our main purpose in this study was to quantify biological tissue in computed tomography (CT) examinations with the aim of developing a skull and a chest patient equivalent phantom (PEP), both specific to infants, aged...
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ISBN:
(纸本)9780819498267
Our main purpose in this study was to quantify biological tissue in computed tomography (CT) examinations with the aim of developing a skull and a chest patient equivalent phantom (PEP), both specific to infants, aged between 1 and 5 years old. This type of phantom is widely used in the development of optimization procedures for radiographic techniques, especially in computed radiography (CR) systems. In order to classify and quantify the biological tissue, we used a computational algorithm developed in Matlab (R). The algorithm performed a histogram of each CT slice followed by a Gaussian fitting of each tissue type. The algorithm determined the mean thickness for the biological tissues (bone, soft, fat, and lung) and also converted them into the corresponding thicknesses of the simulator material (aluminum, PMMA, and air). We retrospectively analyzed 148 CT examinations of infant patients, 56 for skull exams and 92 were for chest. The results provided sufficient data to construct a phantom to simulate the infant chest and skull in the posterior anterior or anterior posterior (PA/AP) view. Both patient equivalent phantoms developed in this study can be used to assess physical variables such as noise power spectrum (NPS) and signal to noise ratio (SNR) or perform dosimetric control specific to pediatric protocols.
Protein structure determination by cryo-electron microscopy (EM) has made significant progress in the past decades. Resolutions of EM maps have been improving as evidenced by recently reported structures that are solv...
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Protein structure determination by cryo-electron microscopy (EM) has made significant progress in the past decades. Resolutions of EM maps have been improving as evidenced by recently reported structures that are solved at high resolutions close to 3 angstrom. computational methods play a key role in interpreting EM data. Among many computational procedures applied to an EM map to obtain protein structure information, in this article we focus on reviewing computational methods that model protein three-dimensional (3D) structures from a 3D EM density map that is constructed from two-dimensional (2D) maps. The computational methods we discuss range from de novo methods, which identify structural elements in an EM map, to structure fitting methods, where known high resolution structures are fit into a low-resolution EM map. A list of available computational tools is also provided. (C) 2013 Elsevier Inc. All rights reserved.
This article addresses model development and computational algorithm design for the probit-based asymmetric stochastic user equilibrium (SUE) problem with elastic demand. Two variational inequality (VI) models are fir...
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This article addresses model development and computational algorithm design for the probit-based asymmetric stochastic user equilibrium (SUE) problem with elastic demand. Two variational inequality (VI) models are first proposed for the SUE problem and then existence and uniqueness of their solutions are examined. These two VI models are, in reality, built by means of a probit-based stochastic network loading (SNL) map. Since there is no computational procedure available for calculating the SNL map, we thus propose a two-stage Monte Carlo simulation-based method to estimate the SNL map. To compromise computational time with accuracy in the estimation, a lower bound of sample size required by the Monte Carlo simulation is also investigated. Based on these two VI models and Monte Carlo simulation-based method, we design two hybrid predictioncorrection (PC) cost averaging (CA) algorithms for solving the SUE problem. Finally, two numerical examples are carried out to assess performance of the proposed algorithms.
The optimal control of nonlinear partial differential equations (PDEs) is an open problem with applications that include fluid, thermal, biological, and chemical systems. Receding horizon control is a kind of optimal ...
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The optimal control of nonlinear partial differential equations (PDEs) is an open problem with applications that include fluid, thermal, biological, and chemical systems. Receding horizon control is a kind of optimal feedback control, and its performance index has amoving initial time and a moving terminal time. In this study, we develop a design method of receding horizon control for systems described by nonlinear parabolic PDEs. The objective of this study is to develop a novel algorithm for numerically solving the receding horizon control problem for nonlinear parabolic PDEs. The effectiveness of the proposed method is verified by numerical simulations.
Block detection is one of the important steps in all discontinuous methods of analysis such as discontinuous deformation analysis and discrete element method. It is in fact a pre-processing step for these methods. Thi...
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Block detection is one of the important steps in all discontinuous methods of analysis such as discontinuous deformation analysis and discrete element method. It is in fact a pre-processing step for these methods. This paper describes a new approach to the problem of geometrically defining polyhedral rock blocks created by the intersection of planar discontinuities in a rock mass. An approach is developed based on the concept of using matrices with integer elements that mostly represent vertices, edges, or face numbers and their connections. Using square matrices with integer elements and performing edge/face regularization reduce the size of the matrices because of elimination of unnecessary faces, edges, and vertices;speed and accuracy of block tracing operation will be increased. This algorithm is able to trace and identify all kinds of blocks including convex and concave blocks formed by limited or unlimited fractures. The simplicity of the procedure makes it very attractive. The algorithm was programmed in C#.Net by over 8100 code lines;several examples are presented to show application of the algorithm in different situations. Copyright (c) 2011 John Wiley & Sons, Ltd.
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