996 resultados para Nonlinear contributions


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Shelton, Edward Mason; p.548 Sherwood Arboretum; p.550 Soutter, William; pp.563-564 Styles or gardens and designed landscapes; pp.575-576 Summer-house; pp.579-580 Trapnell, Walter George; p.602 Tropical Gardens; pp.604-605 Wickham Park; p.642 Wijaya, Made; p.642 Williams, George; p.644 Williams, Keith A.W.; p.644 Verandah Garadening; p.614

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Nonlinear filter generators are common components used in the keystream generators for stream ciphers and more recently for authentication mechanisms. They consist of a Linear Feedback Shift Register (LFSR) and a nonlinear Boolean function to mask the linearity of the LFSR output. Properties of the output of a nonlinear filter are not well studied. Anderson noted that the m-tuple output of a nonlinear filter with consecutive taps to the filter function is unevenly distributed. Current designs use taps which are not consecutive. We examine m-tuple outputs from nonlinear filter generators constructed using various LFSRs and Boolean functions for both consecutive and uneven (full positive difference sets where possible) tap positions. The investigation reveals that in both cases, the m-tuple output is not uniform. However, consecutive tap positions result in a more biased distribution than uneven tap positions, with some m-tuples not occurring at all. These biased distributions indicate a potential flaw that could be exploited for cryptanalysis

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Exclusion processes on a regular lattice are used to model many biological and physical systems at a discrete level. The average properties of an exclusion process may be described by a continuum model given by a partial differential equation. We combine a general class of contact interactions with an exclusion process. We determine that many different types of contact interactions at the agent-level always give rise to a nonlinear diffusion equation, with a vast variety of diffusion functions D(C). We find that these functions may be dependent on the chosen lattice and the defined neighborhood of the contact interactions. Mild to moderate contact interaction strength generally results in good agreement between discrete and continuum models, while strong interactions often show discrepancies between the two, particularly when D(C) takes on negative values. We present a measure to predict the goodness of fit between the discrete and continuous model, and thus the validity of the continuum description of a motile, contact-interacting population of agents. This work has implications for modeling cell motility and interpreting cell motility assays, giving the ability to incorporate biologically realistic cell-cell interactions and develop global measures of discrete microscopic data.

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The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

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For the first time in human history, large volumes of spoken audio are being broadcast, made available on the internet, archived, and monitored for surveillance every day. New technologies are urgently required to unlock these vast and powerful stores of information. Spoken Term Detection (STD) systems provide access to speech collections by detecting individual occurrences of specified search terms. The aim of this work is to develop improved STD solutions based on phonetic indexing. In particular, this work aims to develop phonetic STD systems for applications that require open-vocabulary search, fast indexing and search speeds, and accurate term detection. Within this scope, novel contributions are made within two research themes, that is, accommodating phone recognition errors and, secondly, modelling uncertainty with probabilistic scores. A state-of-the-art Dynamic Match Lattice Spotting (DMLS) system is used to address the problem of accommodating phone recognition errors with approximate phone sequence matching. Extensive experimentation on the use of DMLS is carried out and a number of novel enhancements are developed that provide for faster indexing, faster search, and improved accuracy. Firstly, a novel comparison of methods for deriving a phone error cost model is presented to improve STD accuracy, resulting in up to a 33% improvement in the Figure of Merit. A method is also presented for drastically increasing the speed of DMLS search by at least an order of magnitude with no loss in search accuracy. An investigation is then presented of the effects of increasing indexing speed for DMLS, by using simpler modelling during phone decoding, with results highlighting the trade-off between indexing speed, search speed and search accuracy. The Figure of Merit is further improved by up to 25% using a novel proposal to utilise word-level language modelling during DMLS indexing. Analysis shows that this use of language modelling can, however, be unhelpful or even disadvantageous for terms with a very low language model probability. The DMLS approach to STD involves generating an index of phone sequences using phone recognition. An alternative approach to phonetic STD is also investigated that instead indexes probabilistic acoustic scores in the form of a posterior-feature matrix. A state-of-the-art system is described and its use for STD is explored through several experiments on spontaneous conversational telephone speech. A novel technique and framework is proposed for discriminatively training such a system to directly maximise the Figure of Merit. This results in a 13% improvement in the Figure of Merit on held-out data. The framework is also found to be particularly useful for index compression in conjunction with the proposed optimisation technique, providing for a substantial index compression factor in addition to an overall gain in the Figure of Merit. These contributions significantly advance the state-of-the-art in phonetic STD, by improving the utility of such systems in a wide range of applications.

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The enhanced social profile of not-for-profit organisations (NFPs) and the role of volunteers have resulted in calls for NFPs to be more accountable and to disclose information relating to such contributions. In this study we identify, locate and categorise the extent of disclosures made in relation to volunteer contributions. We find that disclosure was more prevalent on NFP websites compared to digital annual report disclosures. We find that more NFPs provided disclosure on the activities of their volunteers than other items pertaining to volunteers. The valuation of volunteer contributions was the least likely to be disclosed. The findings contribute to international debate over the inclusion of volunteer contributions in the assessment of a NFP’s accountability over its resources and ultimately the enhancement of its sustainability.

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Voluminous (≥3·9 × 105 km3), prolonged (∼18 Myr) explosive silicic volcanism makes the mid-Tertiary Sierra Madre Occidental province of Mexico one of the largest intact silicic volcanic provinces known. Previous models have proposed an assimilation–fractional crystallization origin for the rhyolites involving closed-system fractional crystallization from crustally contaminated andesitic parental magmas, with <20% crustal contributions. The lack of isotopic variation among the lower crustal xenoliths inferred to represent the crustal contaminants and coeval Sierra Madre Occidental rhyolite and basaltic andesite to andesite volcanic rocks has constrained interpretations for larger crustal contributions. Here, we use zircon age populations as probes to assess crustal involvement in Sierra Madre Occidental silicic magmatism. Laser ablation-inductively coupled plasma-mass spectrometry analyses of zircons from rhyolitic ignimbrites from the northeastern and southwestern sectors of the province yield U–Pb ages that show significant age discrepancies of 1–4 Myr compared with previously determined K/Ar and 40Ar/39Ar ages from the same ignimbrites; the age differences are greater than the errors attributable to analytical uncertainty. Zircon xenocrysts with new overgrowths in the Late Eocene to earliest Oligocene rhyolite ignimbrites from the northeastern sector provide direct evidence for some involvement of Proterozoic crustal materials, and, potentially more importantly, the derivation of zircon from Mesozoic and Eocene age, isotopically primitive, subduction-related igneous basement. The youngest rhyolitic ignimbrites from the southwestern sector show even stronger evidence for inheritance in the age spectra, but lack old inherited zircon (i.e. Eocene or older). Instead, these Early Miocene ignimbrites are dominated by antecrystic zircons, representing >33 to ∼100% of the dated population; most antecrysts range in age between ∼20 and 32 Ma. A sub-population of the antecrystic zircons is chemically distinct in terms of their high U (>1000 ppm to 1·3 wt %) and heavy REE contents; these are not present in the Oligocene ignimbrites in the northeastern sector of the Sierra Madre Occidental. The combination of antecryst zircon U–Pb ages and chemistry suggests that much of the zircon in the youngest rhyolites was derived by remelting of partially molten to solidified igneous rocks formed during preceding phases of Sierra Madre Occidental volcanism. Strong Zr undersaturation, and estimations for very rapid dissolution rates of entrained zircons, preclude coeval mafic magmas being parental to the rhyolite magmas by a process of lower crustal assimilation followed by closed-system crystal fractionation as interpreted in previous studies of the Sierra Madre Occidental rhyolites. Mafic magmas were more probably important in providing a long-lived heat and material flux into the crust, resulting in the remelting and recycling of older crust and newly formed igneous materials related to Sierra Madre Occidental magmatism.

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The computation of compact and meaningful representations of high dimensional sensor data has recently been addressed through the development of Nonlinear Dimensional Reduction (NLDR) algorithms. The numerical implementation of spectral NLDR techniques typically leads to a symmetric eigenvalue problem that is solved by traditional batch eigensolution algorithms. The application of such algorithms in real-time systems necessitates the development of sequential algorithms that perform feature extraction online. This paper presents an efficient online NLDR scheme, Sequential-Isomap, based on incremental singular value decomposition (SVD) and the Isomap method. Example simulations demonstrate the validity and significant potential of this technique in real-time applications such as autonomous systems.

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Three recent papers published in Chemical Engineering Journal studied the solution of a model of diffusion and nonlinear reaction using three different methods. Two of these studies obtained series solutions using specialized mathematical methods, known as the Adomian decomposition method and the homotopy analysis method. Subsequently it was shown that the solution of the same particular model could be written in terms of a transcendental function called Gauss’ hypergeometric function. These three previous approaches focused on one particular reactive transport model. This particular model ignored advective transport and considered one specific reaction term only. Here we generalize these previous approaches and develop an exact analytical solution for a general class of steady state reactive transport models that incorporate (i) combined advective and diffusive transport, and (ii) any sufficiently differentiable reaction term R(C). The new solution is a convergent Maclaurin series. The Maclaurin series solution can be derived without any specialized mathematical methods nor does it necessarily involve the computation of any transcendental function. Applying the Maclaurin series solution to certain case studies shows that the previously published solutions are particular cases of the more general solution outlined here. We also demonstrate the accuracy of the Maclaurin series solution by comparing with numerical solutions for particular cases.

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Objective: This study documents the mental health status of people from Burmese refugee backgrounds, recently arrived in Australia; then examines the contributions of gender, premigration and postmigration factors in predicting mental health. Method: Structured interviews, including a demographic questionnaire, the Harvard Trauma Questionnaire, Postmigration Living Difficulties Checklist and Hopkins Symptom Checklist assessed premigration trauma, postmigration living difficulties, depression, anxiety, somatisation and traumatisation symptoms in a sample of 70 adults across five Burmese ethnic groups. Results: Substantial proportions of participants reported psychological distress in symptomatic ranges including: posttraumatic stress disorder (9%); anxiety (20%), and; depression (36%), as well as significant symptoms of somatisation (37%). Participants reported multiple and severe premigration traumas. Postmigration living difficulties of greatest concern included communication problems and worry about family not in Australia. Gender did not predict mental health. Level of exposure to traumatic events and postmigration living difficulties each made unique and relatively equal contributions to traumatisation symptoms. Postmigration living difficulties made unique contributions to depression, anxiety and somatisation symptoms. Conclusions: While exposure to traumatic events impacted on participants’ mental wellbeing, postmigration living difficulties had greater salience in predicting mental health outcomes of people from Burmese refugee backgrounds. Reported rates of posttraumatic stress disorder symptoms were consistent with a large review of adults across seven western countries. High levels of somatisation pointed to a nuanced expression of distress. Findings have implications for service provision in terms of implementing appropriate interventions to effectively meet the needs of this newly arrived group in Australia.

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The electron collection efficiency in dye-sensitized solar cells (DSCs) is usually related to the electron diffusion length, L = (Dτ)1/2, where D is the diffusion coefficient of mobile electrons and τ is their lifetime, which is determined by electron transfer to the redox electrolyte. Analysis of incident photon-to-current efficiency (IPCE) spectra for front and rear illumination consistently gives smaller values of L than those derived from small amplitude methods. We show that the IPCE analysis is incorrect if recombination is not first-order in free electron concentration, and we demonstrate that the intensity dependence of the apparent L derived by first-order analysis of IPCE measurements and the voltage dependence of L derived from perturbation experiments can be fitted using the same reaction order, γ ≈ 0.8. The new analysis presented in this letter resolves the controversy over why L values derived from small amplitude methods are larger than those obtained from IPCE data.

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Shelton, E.M. (p.548); Sherwood Arboretum (p.550); Soutter, William (pp.563-4); Styles (pp.575-6); Summer-House (579-580); Trapnell, W.G. (p.602); Tropical Gardens (pp.604-5);Verandah Gardening (p.614); Wickham Park (p.642); Wijaya, Made (p.642); Williams, George (p.644); Williams Keith A (p.644).

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In this paper, we consider the variable-order Galilei advection diffusion equation with a nonlinear source term. A numerical scheme with first order temporal accuracy and second order spatial accuracy is developed to simulate the equation. The stability and convergence of the numerical scheme are analyzed. Besides, another numerical scheme for improving temporal accuracy is also developed. Finally, some numerical examples are given and the results demonstrate the effectiveness of theoretical analysis. Keywords: The variable-order Galilei invariant advection diffusion equation with a nonlinear source term; The variable-order Riemann–Liouville fractional partial derivative; Stability; Convergence; Numerical scheme improving temporal accuracy