189 resultados para asymptotic preserving


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Uanda house is of historical importance to Queensland both in terms of its architectural design and its social history. Uanda is a low set, single story house built in 1928, located in the inner city Brisbane suburb of Wilston. Architecturally, the house has a number of features that distinguish it from the surrounding bungalow influenced inter-war houses. The house has been described as a Queensland style house with neo-Georgian influences. Historically, it is associated with the entry of women into the profession of architecture in Queensland. Uanda is the only remaining intact work of architect/draftswoman Nellie McCredie and one of a very few examples of works by pioneering women architects in Queensland. The house was entered into the Queensland Heritage Register, in 2000, after an appeal against Brisbane City Council’s refusal of an application to demolish the house was disputed in the Queensland Planning and Environment court in 1998/1999. In the court’s report, Judge Robin QC, DCJ, stated that, “The importance of preserving women's history and heritage, often previously marginalised or lost, is now accepted at government level, recognising that role models are vital for bringing new generations of women into the professions and public life.” While acknowledging women’s contribution to the profession of architecture is an important endeavour, it also has the potential to isolate women architects as separate to a mainstream history of architecture. As Julie Willis writes, it can imply an atypical, feminine style of architecture. What is the impact or potential implications of recognising heritage buildings designed by women architects? The Judge also highlights the absence of a recorded history of unique Brisbane houses and questions the authority of the heritage register. This research looks at these points of difference through a case study of the Uanda house. The paper will investigate the processes of adding the house to the heritage register, the court case and existing research on Nellie McCredie and Uanda House.

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Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

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This paper demonstrates the use of a spreadsheet in exploring non-linear difference equations that describe digital control systems used in radio engineering, communication and computer architecture. These systems, being the focus of intensive studies of mathematicians and engineers over the last 40 years, may exhibit extremely complicated behaviour interpreted in contemporary terms as transition from global asymptotic stability to chaos through period-doubling bifurcations. The authors argue that embedding advanced mathematical ideas in the technological tool enables one to introduce fundamentals of discrete control systems in tertiary curricula without learners having to deal with complex machinery that rigorous mathematical methods of investigation require. In particular, in the appropriately designed spreadsheet environment, one can effectively visualize a qualitative difference in the behviour of systems with different types of non-linear characteristic.

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We present a text watermarking scheme that embeds a bitstream watermark Wi in a text document P preserving the meaning, context, and flow of the document. The document is viewed as a set of paragraphs, each paragraph being a set of sentences. The sequence of paragraphs and sentences used to embed watermark bits is permuted using a secret key. Then, English language sentence transformations are used to modify sentence lengths, thus embedding watermarking bits in the Least Significant Bits (LSB) of the sentences’ cardinalities. The embedding and extracting algorithms are public, while the secrecy and security of the watermark depends on a secret key K. The probability of False Positives is extremely small, hence avoiding incidental occurrences of our watermark in random text documents. Majority voting provides security against text addition, deletion, and swapping attacks, further reducing the probability of False Positives. The scheme is secure against the general attacks on text watermarks such as reproduction (photocopying, FAX), reformatting, synonym substitution, text addition, text deletion, text swapping, paragraph shuffling and collusion attacks.

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In this paper the renormalization group (RG) method of Chen, Goldenfeld, and Oono [Phys. Rev. Lett., 73 (1994), pp.1311-1315; Phys. Rev. E, 54 (1996), pp.376-394] is presented in a pedagogical way to increase its visibility in applied mathematics and to argue favorably for its incorporation into the corresponding graduate curriculum.The method is illustrated by some linear and nonlinear singular perturbation problems. Key word. © 2012 Society for Industrial and Applied Mathematics.

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This paper introduces a straightforward method to asymptotically solve a variety of initial and boundary value problems for singularly perturbed ordinary differential equations whose solution structure can be anticipated. The approach is simpler than conventional methods, including those based on asymptotic matching or on eliminating secular terms. © 2010 by the Massachusetts Institute of Technology.

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With nine examples, we seek to illustrate the utility of the Renormalization Group approach as a unification of other asymptotic and perturbation methods.

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We have developed a technique that circumvents the process of elimination of secular terms and reproduces the uniformly valid approximations, amplitude equations, and first integrals. The technique is based on a rearrangement of secular terms and their grouping into the secular series that multiplies the constants of the asymptotic expansion. We illustrate the technique by deriving amplitude equations for standard nonlinear oscillator and boundary-layer problems. © 2008 The American Physical Society.

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In this paper the method of renormalization group (RG) [Phys. Rev. E 54, 376 (1996)] is related to the well-known approximations of Rytov and Born used in wave propagation in deterministic and random media. Certain problems in linear and nonlinear media are examined from the viewpoint of RG and compared with the literature on Born and Rytov approximations. It is found that the Rytov approximation forms a special case of the asymptotic expansion generated by the RG, and as such it gives a superior approximation to the exact solution compared with its Born counterpart. Analogous conclusions are reached for nonlinear equations with an intensity-dependent index of refraction where the RG recovers the exact solution. © 2008 Optical Society of America.

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We examine the effect of a kinetic undercooling condition on the evolution of a free boundary in Hele--Shaw flow, in both bubble and channel geometries. We present analytical and numerical evidence that the bubble boundary is unstable and may develop one or more corners in finite time, for both expansion and contraction cases. This loss of regularity is interesting because it occurs regardless of whether the less viscous fluid is displacing the more viscous fluid, or vice versa. We show that small contracting bubbles are described to leading order by a well-studied geometric flow rule. Exact solutions to this asymptotic problem continue past the corner formation until the bubble contracts to a point as a slit in the limit. Lastly, we consider the evolving boundary with kinetic undercooling in a Saffman--Taylor channel geometry. The boundary may either form corners in finite time, or evolve to a single long finger travelling at constant speed, depending on the strength of kinetic undercooling. We demonstrate these two different behaviours numerically. For the travelling finger, we present results of a numerical solution method similar to that used to demonstrate the selection of discrete fingers by surface tension. With kinetic undercooling, a continuum of corner-free travelling fingers exists for any finger width above a critical value, which goes to zero as the kinetic undercooling vanishes. We have not been able to compute the discrete family of analytic solutions, predicted by previous asymptotic analysis, because the numerical scheme cannot distinguish between solutions characterised by analytic fingers and those which are corner-free but non-analytic.

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The applications of organic semiconductors in complex circuitry such as printed CMOS-like logic circuits demand miniaturization of the active structures to the submicrometric and nanoscale level while enhancing or at least preserving the charge transport properties upon processing. Here, we addressed this issue by using a wet lithographic technique, which exploits and enhances the molecular order in polymers by spatial confinement, to fabricate ambipolar organic field effect transistors and inverter circuits based on nanostructured single component ambipolar polymeric semiconductor. In our devices, the current flows through a precisely defined array of nanostripes made of a highly ordered diketopyrrolopyrrole-benzothiadiazole copolymer with high charge carrier mobility (1.45 cm2 V-1 s-1 for electrons and 0.70 cm2 V-1 s-1 for holes). Finally, we demonstrated the functionality of the ambipolar nanostripe transistors by assembling them into an inverter circuit that exhibits a gain (105) comparable to inverters based on single crystal semiconductors.

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Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).

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This paper proposes a simulation-based density estimation technique for time series that exploits information found in covariate data. The method can be paired with a large range of parametric models used in time series estimation. We derive asymptotic properties of the estimator and illustrate attractive finite sample properties for a range of well-known econometric and financial applications.

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Introduction Australia is contributing to the global problem of antimicrobial resistance with one of the highest rates of antibiotic use amongst OECD countries. Data from the Australian primary healthcare sector suggests unnecessary antibiotics were prescribed for conditions that will resolve without it. If left unchecked, this will result in more resistant micro-organisms, against which antibiotics will be useless. There is a lack of understanding about what is influencing decisions to use antibiotics – what factors influences general practitioners (GPs) to prescribe antibiotics, consumers to seek antibiotics, and pharmacists to fill old antibiotic prescriptions? It is also not clear how these individuals trade-off between the possible benefits that antibiotics may provide in the immediate/short term, against the longer term societal risk of antimicrobial resistance. Method This project will investigate (a) what factors drive decisions to use antibiotics for GPs, pharmacists and consumers, and (b) how these individuals discount the future. Factors will be gleaned from published literature and from a qualitative phase using semi-structured interviews, to inform the development of Discrete Choice Experiments (DCEs). Three DCEs will be constructed – one for each group of interest – to allow investigation of which factors are more important in influencing (a) GPs to prescribe antibiotics, (b) consumers to seek antibiotics, and (c) pharmacists to fill legally valid but old or repeat prescriptions of antibiotics. Regression analysis will be conducted to understand the relative importance of these factors. A Time Trade Off exercise will be developed to investigate how these individuals discount the future, and whether GPs and pharmacists display the same extent of discounting the future, as consumers. Expected Results Findings from the DCEs will provide an insight into which factors are more important in driving decision making in antibiotic use for GPs, pharmacists and consumers. Findings from the Time Trade Off exercise will show what individuals are willing to trade for preserving the miracle of antibiotics. Conclusion The emergence of antibiotic resistance is inevitable. This research will expand on what is currently known about influencing desired behaviour change in antibiotic use, in the fight against antibiotic resistance. Real World Implications Research findings will contribute to existing national programs to bring about a reduction in inappropriate use of antibiotic in Australia. Specifically, influencing (1) how key messages and public health campaigns are crafted to increase health literacy, and (2) clinical education and empowerment of GPs and pharmacists to play a more responsive role as stewards of antibiotic use in the community.

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Rapid recursive estimation of hidden Markov Model (HMM) parameters is important in applications that place an emphasis on the early availability of reasonable estimates (e.g. for change detection) rather than the provision of longer-term asymptotic properties (such as convergence, convergence rate, and consistency). In the context of vision- based aircraft (image-plane) heading estimation, this paper suggests and evaluates the short-data estimation properties of 3 recursive HMM parameter estimation techniques (a recursive maximum likelihood estimator, an online EM HMM estimator, and a relative entropy based estimator). On both simulated and real data, our studies illustrate the feasibility of rapid recursive heading estimation, but also demonstrate the need for careful step-size design of HMM recursive estimation techniques when these techniques are intended for use in applications where short-data behaviour is paramount.