951 resultados para SCALING


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The necessary and sufficient condition for the existence of the one-parameter scale function, the /Munction, is obtained exactly. The analysis reveals certain inconsistency inherent in the scaling theory, and tends to support Motts’ idea of minimum metallic conductivity.

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A perturbative scaling theory for calculating static thermodynamic properties of arbitrary local impurity degrees of freedom interacting with the conduction electrons of a metal is presented. The basic features are developments of the ideas of Anderson and Wilson, but the precise formulation is new and is capable of taking into account band-edge effects which cannot be neglected in certain problems. Recursion relations are derived for arbitrary interaction Hamiltonians up to third order in perturbation theory. A generalized impurity Hamiltonian is defined and its scaling equations are derived up to third order. The strategy of using such perturbative scaling equations is delineated and the renormalization-group aspects are discussed. The method is illustrated by applying it to the single-impurity Kondo problem whose static properties are well understood.

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The necessary and sufficient condition for the existence of the one-parameter scale function, the /Munction, is obtained exactly. The analysis reveals certain inconsistency inherent in the scaling theory, and tends to support Motts’ idea of minimum metallic conductivity.

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We present results of a study of the two-impurity Anderson model using a thermodynamic scaling theory developed recently. The model is characterized by the Coulomb energy U, the orbital energy epsilond, the d-level width Gamma, and the separation between impurities R. If Gamma<<−epsilond<~Gamma. Here we find that the single-impurity physics dominates the low-temperature behavior, and impurity-impurity interactions are perturbative. The qualitative features of the temperature-dependent susceptibility are discussed. Journal of Applied Physics is copyrighted by The American Institute of Physics.

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Grazing experiments are usually used to quantify and demonstrate the biophysical impact of grazing strategies, with the Wambiana grazing experiment being one of the longest running such experiments in northern Australia. Previous economic analyses of this experiment suggest that there is a major advantage in stocking at a fixed, moderate stocking rate or in using decision rules allowing flexible stocking to match available feed supply. The present study developed and applied a modelling procedure to use data collected at the small plot, land type and paddock scales at the experimental site to simulate the property-level implications of a range of stocking rates for a breeding-finishing cattle enterprise. The greatest economic performance was achieved at a moderate stocking rate of 10.5 adult equivalents 100 ha(-1). For the same stocking rate over time, the fixed stocking strategy gave a greater economic performance than strategies that involved moderate changes to stocking rates each year in response to feed supply. Model outcomes were consistent with previous economic analyses using experimental data. Further modelling of the experimental data is warranted and similar analyses could be applied to other major grazing experiments to allow the scaling of results to greater scales.

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Quality of Service (QoS) is a new issue in cloud-based MapReduce, which is a popular computation model for parallel and distributed processing of big data. QoS guarantee is challenging in a dynamical computation environment due to the fact that a fixed resource allocation may become under-provisioning, which leads to QoS violation, or over-provisioning, which increases unnecessary resource cost. This requires runtime resource scaling to adapt environmental changes for QoS guarantee. Aiming to guarantee the QoS, which is referred as to hard deadline in this work, this paper develops a theory to determine how and when resource is scaled up/down for cloud-based MapReduce. The theory employs a nonlinear transformation to define the problem in a reverse resource space, simplifying the theoretical analysis significantly. Then, theoretical results are presented in three theorems on sufficient conditions for guaranteeing the QoS of cloud-based MapReduce. The superiority and applications of the theory are demonstrated through case studies.

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Reverse osmosis (RO) brine produced at a full-scale coal seam gas (CSG) water treatment facility was characterized with spectroscopic and other analytical techniques. A number of potential scalants including silica, calcium, magnesium, sulphates and carbonates, all of which were present in dissolved and non-dissolved forms, were characterized. The presence of spherical particles with a size range of 10–1000 nm and aggregates of 1–10 microns was confirmed by transmission electron microscopy (TEM). Those particulates contained the following metals in decreasing order: K, Si, Sr, Ca, B, Ba, Mg, P, and S. Characterization showed that nearly one-third of the total silicon in the brine was present in the particulates. Further, analysis of the RO brine suggested supersaturation and precipitation of metal carbonates and sulphates during the RO process should take place and could be responsible for subsequently capturing silica in the solid phase. However, the precipitation of crystalline carbonates and sulphates are complex. X-ray diffraction analysis did not confirm the presence of common calcium carbonates or sulphates but instead showed the presence of a suite of complex minerals, to which amorphous silica and/or silica rich compounds could have adhered. A filtration study showed that majority of the siliceous particles were less than 220 nm in size, but could still be potentially captured using a low molecular weight ultrafiltration membrane.

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Planar curves arise naturally as interfaces between two regions of the plane. An important part of statistical physics is the study of lattice models. This thesis is about the interfaces of 2D lattice models. The scaling limit is an infinite system limit which is taken by letting the lattice mesh decrease to zero. At criticality, the scaling limit of an interface is one of the SLE curves (Schramm-Loewner evolution), introduced by Oded Schramm. This family of random curves is parametrized by a real variable, which determines the universality class of the model. The first and the second paper of this thesis study properties of SLEs. They contain two different methods to study the whole SLE curve, which is, in fact, the most interesting object from the statistical physics point of view. These methods are applied to study two symmetries of SLE: reversibility and duality. The first paper uses an algebraic method and a representation of the Virasoro algebra to find common martingales to different processes, and that way, to confirm the symmetries for polynomial expected values of natural SLE data. In the second paper, a recursion is obtained for the same kind of expected values. The recursion is based on stationarity of the law of the whole SLE curve under a SLE induced flow. The third paper deals with one of the most central questions of the field and provides a framework of estimates for describing 2D scaling limits by SLE curves. In particular, it is shown that a weak estimate on the probability of an annulus crossing implies that a random curve arising from a statistical physics model will have scaling limits and those will be well-described by Loewner evolutions with random driving forces.

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Scaling relations between the critical indices are derived for two similar systems exhibiting λ lines: binary liquid systems and ferromagnets under pressure. In addition to the usual scaling relations, this procedure gives information about other weakly divergent quantities like isothermal compressibility and thermal expansion. Suggestions for more detailed investigations are made.

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Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.

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This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as "doctors' opinions". Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities.

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In this paper, a new strategy for scaling burners based on "mild combustion" is evolved and adopted to scaling a burner from 3 to a 150 kW burner at a high heat release Late of 5 MW/m(3) Existing scaling methods (constant velocity, constant residence time, and Cole's procedure [Proc. Combust. Inst. 28 (2000) 1297]) are found to be inadequate for mild combustion burners. Constant velocity approach leads to reduced heat release rates at large sizes and constant residence time approach in unacceptable levels of pressure drop across the system. To achieve mild combustion at high heat release rates at all scales, a modified approach with high recirculation is adopted in the present studies. Major geometrical dimensions are scaled as D similar to Q(1/3) with an air injection velocity of similar to 100 m/s (Delta p similar to 600 mm water gauge). Using CFD support, the position of air injection holes is selected to enhance the recirculation rates. The precise role of secondary air is to increase the recirculation rates and burn LIP the residual CO in the downstream. Measurements of temperature and oxidizer concentrations inside 3 kW, 150 kW burner and a jet flame are used to distinguish the combustion process in these burners. The burner can be used for a wide range of fuels from LPG to producer gas as extremes. Up to 8 dB of noise level reduction is observed in comparison to the conventional combustion mode. Exhaust NO emissions below 26 and 3 ppm and temperatures 1710 and 1520 K were measured for LPG and producer gas when the burner is operated at stoichiometry. (c) 2004 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

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This paper studies:(i)the long-time behaviour of the empirical distribution of age and normalized position of an age-dependent critical branching Markov process conditioned on non-extinction;and (ii) the super-process limit of a sequence of age-dependent critical branching Brownian motions.

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We study the energy current in a model of heat conduction, first considered in detail by Casher and Lebowitz. The model consists of a one-dimensional disordered harmonic chain of n i.i.d. random masses, connected to their nearest neighbors via identical springs, and coupled at the boundaries to Langevin heat baths, with respective temperatures T_1 and T_n. Let EJ_n be the steady-state energy current across the chain, averaged over the masses. We prove that EJ_n \sim (T_1 - T_n)n^{-3/2} in the limit n \to \infty, as has been conjectured by various authors over the time. The proof relies on a new explicit representation for the elements of the product of associated transfer matrices.