855 resultados para Weighted Corner Sobolev Spaces
Resumo:
This thesis consists of three articles on Orlicz-Sobolev capacities. Capacity is a set function which gives information of the size of sets. Capacity is useful concept in the study of partial differential equations, and generalizations of exponential-type inequalities and Lebesgue point theory, and other topics related to weakly differentiable functions such as functions belonging to some Sobolev space or Orlicz-Sobolev space. In this thesis it is assumed that the defining function of the Orlicz-Sobolev space, the Young function, satisfies certain growth conditions. In the first article, the null sets of two different versions of Orlicz-Sobolev capacity are studied. Sufficient conditions are given so that these two versions of capacity have the same null sets. The importance of having information about null sets lies in the fact that the sets of capacity zero play similar role in the Orlicz-Sobolev space setting as the sets of measure zero do in the Lebesgue space and Orlicz space setting. The second article continues the work of the first article. In this article, it is shown that if a Young function satisfies certain conditions, then two versions of Orlicz-Sobolev capacity have the same null sets for its complementary Young function. In the third article the metric properties of Orlicz-Sobolev capacities are studied. It is usually difficult or impossible to calculate a capacity of a set. In applications it is often useful to have estimates for the Orlicz-Sobolev capacities of balls. Such estimates are obtained in this paper, when the Young function satisfies some growth conditions.
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A method of analysing a 3-dimensional corner reflector antenna of arbitrary apex angle is given. Expressions have been obtained for the far field of the 3-dimensional corner reflector fed by a dipole. The radiation resistance and the directive gain of the antenna have been calculated. The method described is applicable even when the feed dipole is arbitrarily oriented. It is found that the radiation along a prescribed direction can be circularly polarised (right or left) by suitably orienting the feed dipole.
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In this paper I conduct a Foucauldian discourse analysis of a political speech given by Brendon Nelson in 2006 when the Australian Minister for Defence in the Howard Coalition Government. The speech connects conceptualisations of terror, globalization, education and literacy as part of a whole of government security strategy. The analysis examines this speech as an example of a liberal way of governing the conduct of diverse and unpredictable populations. My analysis suggests that the apparatus of government has been strategically used in order to biopolitically contain the rise of complex social forces and protect a set of homogenous cultural values. The purposes of education and uses of literacy are seen as instruments for the inscription of a coded set of values understood to be synonymous with civil society.
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This chapter addresses the relevance of composing for young children in creating spaces for social agency. It begins with a working definition of agency, outlines forms of agency and what might constrain it. Referring to case studies of particular children, it then goes on to discuss key themes, which illuminate what is possible and what is at stake when children compose. These overlapping themes include identity (sense of self, belonging), positioning (helping, initiating, befriending, “being bright”), voices (made through sound effects, singing, language style, and appropriating from popular culture and digital worlds), play (appropriating, imagining, designing, and creating), and resistance (not participating, staying silent, moving). Two main cases are drawn upon, those of Ta’Von and Gareth, who demonstrate agency in terms of finding spaces of belonging and meaning-making occasions in the classroom and playground. Vignettes from other children are referred to in order to illustrate common themes.
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This paper argues that the staffroom is an important professional learning space where beginning teachers interact to understand who they are and the nature of their professional work. The authors highlight the theoretical importance of space and place in the construction and negotiation of beginning teacher subjectivities. To illustrate the staffroom as a particular place where important professional learning could occur the authors use two narratives based on the lived experiences of two beginning teachers, one in a primary context, the other secondary. The authors conclude by calling for greater research attention to the significance of the staffroom and its interaction with teacher subjectivities. At the level of practice we also call for the teaching profession to recognise staffrooms as important sites of professional learning and places that should support induction and mentoring of beginning teachers. Such recognition could enhance the retention, satisfaction, and effectiveness of new and experienced teachers alike.
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Learning automata are adaptive decision making devices that are found useful in a variety of machine learning and pattern recognition applications. Although most learning automata methods deal with the case of finitely many actions for the automaton, there are also models of continuous-action-set learning automata (CALA). A team of such CALA can be useful in stochastic optimization problems where one has access only to noise-corrupted values of the objective function. In this paper, we present a novel formulation for noise-tolerant learning of linear classifiers using a CALA team. We consider the general case of nonuniform noise, where the probability that the class label of an example is wrong may be a function of the feature vector of the example. The objective is to learn the underlying separating hyperplane given only such noisy examples. We present an algorithm employing a team of CALA and prove, under some conditions on the class conditional densities, that the algorithm achieves noise-tolerant learning as long as the probability of wrong label for any example is less than 0.5. We also present some empirical results to illustrate the effectiveness of the algorithm.
Resumo:
The removal of noise and outliers from health signals is an important problem in jet engine health monitoring. Typically, health signals are time series of damage indicators, which can be sensor measurements or features derived from such measurements. Sharp or sudden changes in health signals can represent abrupt faults and long term deterioration in the system is typical of gradual faults. Simple linear filters tend to smooth out the sharp trend shifts in jet engine signals and are also not good for outlier removal. We propose new optimally designed nonlinear weighted recursive median filters for noise removal from typical health signals of jet engines. Signals for abrupt and gradual faults and with transient data are considered. Numerical results are obtained for a jet engine and show that preprocessing of health signals using the proposed filter significantly removes Gaussian noise and outliers and could therefore greatly improve the accuracy of diagnostic systems. [DOI: 10.1115/1.3200907].
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PURPOSE To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. METHODS We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. RESULTS We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. CONCLUSIONS We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.
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Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes under a single service class and multiple queues, and present a multi-layered pricing scheme. We propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. The pricing policy used depends on a weighted average queue length at each node. This helps in reducing frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using our scheme over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our approach exhibits a throughput improvement in the range of 34 to 69 percent in all cases studied (over all routes) over the above scheme.
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In this paper, we study approximatively τ-compact and τ-strongly Chebyshev sets, where τ is the norm or the weak topology. We show that the metric projection onto τ-strongly Chebyshev sets are norm-τ continuous. We characterize approximatively τ-compact and τ-strongly Chebyshev hyperplanes and use them to characterize factor reflexive proximinal subspaces in τ-almost locally uniformly rotund spaces. We also prove some stability results on approximatively τ-compact and τ-strongly Chebyshev subspaces.
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In this paper, we show existence and uniqueness of a solution to a functional differential equation with infinite delay. We choose an appropriate Frechet space so as to cover a large class of functions to be used as initial functions to obtain existence and uniqueness of solutions.