907 resultados para Link variables method
Resumo:
This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the proposed system there is no need for using offline estimation. The proposed method consists of two steps: a noise controller which is based on an FxLMS algorithm, and a variable step size (VSS) LMS algorithm which is used to adapt the modeling filter with the secondary path. In order to increase performance of the algorithm in a faster convergence and accurate performance, we stop the VSS-LMS algorithm at the optimum point. The results of computer simulation shown in this paper indicate effectiveness of the proposed method.
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While academic interest in destination branding has been gathering momentum since the field commenced in the late 1990s, one important gap in this literature that has received relatively little attention to date is the measurement of destination brand performance. This paper sets out one method for assessing the performance of a destination brand over time. The intent is to present an approach that will appeal to marketing practitioners, and which is also conceptually sound. The method is underpinned by Decision Set Theory and the concept of Consumer-Based Brand Equity (CBBE), while the key variables mirror the branding objectives used by many destination marketing organisations (DMO). The approach is demonstrated in this paper to measure brand performance for Australia in the New Zealand market. It is suggested the findings provide indicators of both i) the success of previous marketing communications, and ii) future performance, which can be easily communicated to a DMO’s stakeholders.
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We directly constructed reduced graphene oxide–titanium oxide nanotube (RGO–TNT) film using a single-step, combined electrophoretic deposition–anodization (CEPDA) method. This method, based on the simultaneous anodic growth of tubular TiO2 and the electrophoretic-driven motion of RGO, allowed the formation of an effective interface between the two components, thus improving the electron transfer kinetics. Composites of these graphitic carbons with different levels of oxygen-containing groups, electron conductivity and interface reaction time were investigated; a fine balance of these parameters was achieved.
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The aim of this study was to investigate the influence of low-dose bovine colostrum protein concentrate (CPC) supplementation on selected immune variables in cyclists. Twenty-nine highly trained male road cyclists completed an initial 40-km time trial (TT(40)) and were then randomly assigned to either a supplement (n = 14, 10 g bovine CPC/day) or placebo group (n = 15, 10 g whey protein concentrate/day). After 5 wk of supplementation, the cyclists completed a second TT(40). They then completed 5 consecutive days of high-intensity training (HIT) that included a TT(40), followed by a final TT(40) in the following week. Venous blood and saliva samples were collected immediately before and after each TT(40), and upper respiratory illness symptoms were recorded over the experimental period. Compared with the placebo group, bovine CPC supplementation significantly increased preexercise serum soluble TNF receptor 1 during the HIT period (bovine CPC = 882 +/- 233 pg/ml, placebo = 468 +/- 139 pg/ml; P = 0.039). Supplementation also suppressed the postexercise decrease in cytotoxic/suppressor T cells during the HIT period (bovine CPC = -1.0 +/- 2.7%, placebo = -9.2 +/- 2.8%; P = 0.017) and during the following week (bovine CPC = 1.4 +/- 2.9%, placebo = -8.2 +/- 2.8%; P = 0.004). Bovine CPC supplementation prevented a postexercise decrease in serum IgG(2) concentration at the end of the HIT period (bovine CPC = 4.8 +/- 6.8%, P = 0.88; placebo = -9.7 +/- 6.9%, P = 0.013). There was a trend toward reduced incidence of upper respiratory illness symptoms in the bovine CPC group (P = 0.055). In summary, low-dose bovine CPC supplementation modulates immune parameters during normal training and after an acute period of intense exercise, which may have contributed to the trend toward reduced upper respiratory illness in the bovine CPC group.
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In order to develop more inclusive products and services, designers need a means of assessing the inclusivity of existing products and new concepts. Following previous research on the development of scales for inclusive design at University of Cambridge, Engineering Design Centre (EDC) [1], this paper presents the latest version of the exclusion audit method. For a specific product interaction, this estimates the proportion of the Great British population who would be excluded from using a product or service, due to the demands the product places on key user capabilities. A critical part of the method involves rating of the level of demand placed by a task on a range of key user capabilities, so the procedure to perform this assessment was operationalised and then its reliability was tested with 31 participants. There was no evidence that participants rated the same demands consistently. The qualitative results from the experiment suggest that the consistency of participants’ demand level ratings could be significantly improved if the audit materials and their instructions better guided the participant through the judgement process.
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Recent empirical studies of gender discrimination point to the importance of accurately controlling for accumulated labour market experience. Unfortunately in Australia, most data sets do not include information on actual experience. The current paper using data from the National Social Science Survey 1984, examines the efficacy of imputing female labour market experience via the Zabalza and Arrufat (1985) method. The results suggest that the method provides a more accurate measure of experience than that provided by the traditional Mincer proxy. However, the imputation method is sensitive to the choice of identification restrictions. We suggest a novel alternative to a choice between arbitrary restrictions.
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Fractional reaction–subdiffusion equations are widely used in recent years to simulate physical phenomena. In this paper, we consider a variable-order nonlinear reaction–subdiffusion equation. A numerical approximation method is proposed to solve the equation. Its convergence and stability are analyzed by Fourier analysis. By means of the technique for improving temporal accuracy, we also propose an improved numerical approximation. Finally, the effectiveness of the theoretical results is demonstrated by numerical examples.
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Fractional partial differential equations have been applied to many problems in physics, finance, and engineering. Numerical methods and error estimates of these equations are currently a very active area of research. In this paper we consider a fractional diffusionwave equation with damping. We derive the analytical solution for the equation using the method of separation of variables. An implicit difference approximation is constructed. Stability and convergence are proved by the energy method. Finally, two numerical examples are presented to show the effectiveness of this approximation.
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The space and time fractional Bloch–Torrey equation (ST-FBTE) has been used to study anomalous diffusion in the human brain. Numerical methods for solving ST-FBTE in three-dimensions are computationally demanding. In this paper, we propose a computationally effective fractional alternating direction method (FADM) to overcome this problem. We consider ST-FBTE on a finite domain where the time and space derivatives are replaced by the Caputo–Djrbashian and the sequential Riesz fractional derivatives, respectively. The stability and convergence properties of the FADM are discussed. Finally, some numerical results for ST-FBTE are given to confirm our theoretical findings.
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Balcony acoustic treatments can be demonstrated to provide important benefits in reducing road traffic noise within the balcony space and consequently internally for any adjacent room. The actual effect on road traffic noise is derived from a multitude of variables that can be broadly categorized into (a) acoustical and (b) geometrical for two distinct propagation volumes being (i) the street space, and (ii) the balcony space. A series of recent research activities in this area has incorporated the use of a combined image and diffuse source model, which can be used to predict the effect of balconies on road traffic noise for large number of scenarios. This paper investigates and presents a method and capability to summarize predictive data into user friendly guidelines aimed for use by acoustical professionals and architects and possible implementation in building design policies for environmental noise. The paper concludes with a presentation of the likely format of a potential design guide.
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A quasi-maximum likelihood procedure for estimating the parameters of multi-dimensional diffusions is developed in which the transitional density is a multivariate Gaussian density with first and second moments approximating the true moments of the unknown density. For affine drift and diffusion functions, the moments are exactly those of the true transitional density and for nonlinear drift and diffusion functions the approximation is extremely good and is as effective as alternative methods based on likelihood approximations. The estimation procedure generalises to models with latent factors. A conditioning procedure is developed that allows parameter estimation in the absence of proxies.
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Topic modeling has been widely utilized in the fields of information retrieval, text mining, text classification etc. Most existing statistical topic modeling methods such as LDA and pLSA generate a term based representation to represent a topic by selecting single words from multinomial word distribution over this topic. There are two main shortcomings: firstly, popular or common words occur very often across different topics that bring ambiguity to understand topics; secondly, single words lack coherent semantic meaning to accurately represent topics. In order to overcome these problems, in this paper, we propose a two-stage model that combines text mining and pattern mining with statistical modeling to generate more discriminative and semantic rich topic representations. Experiments show that the optimized topic representations generated by the proposed methods outperform the typical statistical topic modeling method LDA in terms of accuracy and certainty.
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Biological systems involving proliferation, migration and death are observed across all scales. For example, they govern cellular processes such as wound-healing, as well as the population dynamics of groups of organisms. In this paper, we provide a simplified method for correcting mean-field approximations of volume-excluding birth-death-movement processes on a regular lattice. An initially uniform distribution of agents on the lattice may give rise to spatial heterogeneity, depending on the relative rates of proliferation, migration and death. Many frameworks chosen to model these systems neglect spatial correlations, which can lead to inaccurate predictions of their behaviour. For example, the logistic model is frequently chosen, which is the mean-field approximation in this case. This mean-field description can be corrected by including a system of ordinary differential equations for pair-wise correlations between lattice site occupancies at various lattice distances. In this work we discuss difficulties with this method and provide a simplication, in the form of a partial differential equation description for the evolution of pair-wise spatial correlations over time. We test our simplified model against the more complex corrected mean-field model, finding excellent agreement. We show how our model successfully predicts system behaviour in regions where the mean-field approximation shows large discrepancies. Additionally, we investigate regions of parameter space where migration is reduced relative to proliferation, which has not been examined in detail before, and our method is successful at correcting the deviations observed in the mean-field model in these parameter regimes.
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Recent fire research into the behaviour of light gauge steel frame (LSF) wall systems has devel-oped fire design rules based on Australian and European cold-formed steel design standards, AS/NZS 4600 and Eurocode 3 Part 1.3. However, these design rules are complex since the LSF wall studs are subjected to non-uniform elevated temperature distributions when the walls are exposed to fire from one side. Therefore this paper proposes an alternative design method for routine predictions of fire resistance rating of LSF walls. In this method, suitable equations are recommended first to predict the idealised stud time-temperature pro-files of eight different LSF wall configurations subject to standard fire conditions based on full scale fire test results. A new set of equations was then proposed to find the critical hot flange (failure) temperature for a giv-en load ratio for the same LSF wall configurations with varying steel grades and thickness. These equations were developed based on detailed finite element analyses that predicted the axial compression capacities and failure times of LSF wall studs subject to non-uniform temperature distributions with varying steel grades and thicknesses. This paper proposes a simple design method in which the two sets of equations developed for time-temperature profiles and critical hot flange temperatures are used to find the failure times of LSF walls. The proposed method was verified by comparing its predictions with the results from full scale fire tests and finite element analyses. This paper presents the details of this study including the finite element models of LSF wall studs, the results from relevant fire tests and finite element analyses, and the proposed equations.
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Database security techniques are available widely. Among those techniques, the encryption method is a well-certified and established technology for protecting sensitive data. However, once encrypted, the data can no longer be easily queried. The performance of the database depends on how to encrypt the sensitive data, and an approach for searching and retrieval efficiencies that are implemented. In this paper we analyze the database queries and the data properties and propose a suitable mechanism to query the encrypted database. We proposed and analyzed the new database encryption algorithm using the Bloom Filter with the bucket index method. Finally, we demonstrated the superiority of the proposed algorithm through several experiments that should be useful for database encryption related research and application activities.