8 resultados para Nonlinear static analysis

em University of Queensland eSpace - Australia


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We show that the simple quasi-static technique, also called the adiabatic mapping technique, can be used to determine the energetics of rotation of methyl and methoxy groups in amorphous poly(vinyl methyl ether) even though the latter process is too slow to be amenable to direct molecular dynamics simulation. For the methyl group rotation, we find that the mean and standard deviation of the simulated rotational barrier heights agree well with experimental data from quasi-elastic neutron scattering. In the case of the methoxy groups we find that just 4% of the groups contribute more than 90% of the observed dielectric relaxation strength. The groups which make the most contribution are those which, by virtue of their particular conformation and local environment, have two alternative positions of similar energy.

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The results of empirical studies are limited to particular contexts, difficult to generalise and the studies themselves are expensive to perform. Despite these problems, empirical studies in software engineering can be made effective and they are important to both researchers and practitioners. The key to their effectiveness lies in the maximisation of the information that can be gained by examining existing studies, conducting power analyses for an accurate minimum sample size and benefiting from previous studies through replication. This approach was applied in a controlled experiment examining the combination of automated static analysis tools and code inspection in the context of verification and validation (V&V) of concurrent Java components. The combination of these V&V technologies was shown to be cost-effective despite the size of the study, which thus contributes to research in V&V technology evaluation.

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Information security devices must preserve security properties even in the presence of faults. This in turn requires a rigorous evaluation of the system behaviours resulting from component failures, especially how such failures affect information flow. We introduce a compositional method of static analysis for fail-secure behaviour. Our method uses reachability matrices to identify potentially undesirable information flows based on the fault modes of the system's components.

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Summary form only given. The Java programming language supports concurrency. Concurrent programs are harder to verify than their sequential counterparts due to their inherent nondeterminism and a number of specific concurrency problems such as interference and deadlock. In previous work, we proposed a method for verifying concurrent Java components based on a mix of code inspection, static analysis tools, and the ConAn testing tool. The method was derived from an analysis of concurrency failures in Java components, but was not applied in practice. In this paper, we explore the method by applying it to an implementation of the well-known readers-writers problem and a number of mutants of that implementation. We only apply it to a single, well-known example, and so we do not attempt to draw any general conclusions about the applicability or effectiveness of the method. However, the exploration does point out several strengths and weaknesses in the method, which enable us to fine-tune the method before we carry out a more formal evaluation on other, more realistic components.

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This paper investigates the performance analysis of separation of mutually independent sources in nonlinear models. The nonlinear mapping constituted by an unsupervised linear mixture is followed by an unknown and invertible nonlinear distortion, are found in many signal processing cases. Generally, blind separation of sources from their nonlinear mixtures is rather difficult. We propose using a kernel density estimator incorporated with equivariant gradient analysis to separate the sources with nonlinear distortion. The kernel density estimator parameters of which are iteratively updated to minimize the output independence expressed as a mutual information criterion. The equivariant gradient algorithm has the form of nonlinear decorrelation to perform the convergence analysis. Experiments are proposed to illustrate these results.

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This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.