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Proposed Idea (proposed + idea)
Selected AbstractsThe buckling mode extracted from the LDLT -decomposed large-order stiffness matrixINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 7 2002Fumio Fujii Abstract The present study proposes an innovated eigenanalysis-free idea to extract the buckling mode only from the LDLT -decomposed stiffness matrix in large-scale bifurcation analysis. The computational cost for extracting the critical eigenvector is negligible, because the decomposition of the stiffness matrix will continually be repeated during path-tracing to solve the stiffness equations. A numerical example is computed to illustrate that the proposed idea is tough enough even for multiple bifurcation. Copyright © 2002 John Wiley & Sons, Ltd. [source] A preconditioning proposal for ill-conditioned Hermitian two-level Toeplitz systemsNUMERICAL LINEAR ALGEBRA WITH APPLICATIONS, Issue 2-3 2005D. Noutsos Abstract Large 2-level Toeplitz systems arise in many applications and thus an efficient strategy for their solution is often needed. The already known methods require the explicit knowledge of the generating function , of the considered system Tnm(,)x=b, an assumption that usually is not fulfilled in real applications. In this paper, we extend to the 2-level case a technique proposed in the literature in such a way that, from the knowledge of the coefficients of Tnm(,), we determine optimal preconditioning strategies for the solution of our systems. More precisely, we propose and analyse an algorithm for the economical computation of minimal features of , that allow us to select optimal preconditioners. Finally, we perform various numerical experiments which fully confirm the effectiveness of the proposed idea. Copyright © 2004 John Wiley & Sons, Ltd. [source] Minimizing operating points for way point tracking of an unstable nonlinear plantASIAN JOURNAL OF CONTROL, Issue 1 2010Guangyu Liu Abstract Stability analysis of way point tracking of an open loop unstable nonlinear system is overwhelmingly ignored in the literature. Taking a spherical inverted pendulum as an example, the stability issue of way point tracking for an unstable nonlinear system is properly addressed and solved by incorporating nonlinear stabilizing controllers that could minimize the number of operating points. The underlying principle in stability analysis of way point tracking easily extends to other unstable nonlinear systems. Effectiveness of the proposed idea is evaluated in computer simulation. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] Active Learning through Modeling: Introduction to Software Development in the Business Curriculum,DECISION SCIENCES JOURNAL OF INNOVATIVE EDUCATION, Issue 2 2004Boris Roussev ABSTRACT Modern software practices call for the active involvement of business people in the software process. Therefore, programming has become an indispensable part of the information systems component of the core curriculum at business schools. In this paper, we present a model-based approach to teaching introduction to programming to general business students. The theoretical underpinnings of the new approach are metaphor, abstraction, modeling, Bloom's classification of cognitive skills, and active learning. We employ models to introduce the basic programming constructs and their semantics. To this end, we use statecharts to model object's state and the environment model of evaluation as a virtual machine interpreting the programs written in JavaScript. The adoption of this approach helps learners build a sound mental model of the notion of computation process. Scholastic performance, student evaluations, our experiential observations, and a multiple regression statistical test prove that the proposed ideas improve the course significantly. [source] Using ARX and NARX approaches for modeling and prediction of the process behavior: application to a reactor-exchangerASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, Issue 6 2008Yahya Chetouani Abstract Chemical industries are characterized often by nonlinear processes. Therefore, it is often difficult to obtain nonlinear models that accurately describe a plant in all regimes. The main contribution of this work is to establish a reliable model of a process behavior. The use of this model should reflect the normal behavior of the process and allow distinguishing it from an abnormal one. Consequently, the black-box identification based on the neural network (NN) approach by means of a nonlinear autoregressive with exogenous input (NARX) model has been chosen in this study. A comparison with an autoregressive with exogenous input (ARX) model based on the least squares criterion is carried out. This study also shows the choice and the performance of ARX and NARX models in the training and test phases. Statistical criteria are used for the validation of the experimental data of these approaches. The identified neural model is implemented by training a multilayer perceptron artificial neural network (MLP-ANN) with input,output experimental data. An analysis of the inputs number, hidden neurons and their influence on the behavior of the neural predictor is carried out. In order to illustrate the proposed ideas, a reactor-exchanger is used. Satisfactory agreement between identified and experimental data is found and results show that the neural model predicts the evolution of the process dynamics in a better way. Copyright © 2008 Curtin University of Technology and John Wiley & Sons, Ltd. [source] | ||||||||||