63 resultados para universal scaling

em Queensland University of Technology - ePrints Archive


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his paper identifies some scaling relationships between solar activity and geomagnetic activity. We examine the scaling properties of hourly data for two geomagnetic indices (ap and AE), two solar indices (solar X-rays Xl and solar flux F10.7), and two inner heliospheric indices (ion density Ni and flow speed Vs) over the period 1995–2001 by the universal multifractal approach and the traditional multifractal analysis. We found that the universal multifractal model (UMM) provides a good fit to the empirical K(q) and τ(q) curves of these time series. The estimated values of the Lévy index α in the UMM indicate that multifractality exists in the time series for ap, AE, Xl, and Ni, while those for F10.7 and Vs are monofractal. The estimated values of the nonconservation parameter H of this model confirm that these time series are conservative which indicate that the mean value of the process is constant for varying resolution. Additionally, the multifractal K(q) and τ(q) curves, and the estimated values of the sparseness parameter C1 of the UMM indicate that there are three pairs of indices displaying similar scaling properties, namely ap and Xl, AE and Ni, and F10.7 and Vs. The similarity in the scaling properties of pairs (ap,Xl) and (AE,Ni) suggests that ap and Xl, AE and Ni are better correlated—in terms of scaling—than previous thought, respectively. But our results still cannot be used to advance forecasting of ap and AE by Xl and Ni, respectively, due to some reasons

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Team games conceptualized as dynamical systems engender a view of emergent decision-making behaviour under constraints, although specific effects of instructional and body-scaling constraints have yet to be verified empirically. For this purpose, we studied the effects of task and individual constraints on decision-making processes in basketball. Eleven experienced female players performed 350 trials in 1 vs. 1 sub-phases of basketball in which an attacker tried to perturb the stable state of a dyad formed with a defender (i.e. break the symmetry). In Experiment 1, specific instructions (neutral, risk taking or conservative) were manipulated to observe effects on emergent behaviour of the dyadic system. When attacking players were given conservative instructions, time to cross court mid-line and variability of the attacker's trajectory were significantly greater. In Experiment 2, body-scaling of participants was manipulated by creating dyads with different height relations. When attackers were considerably taller than defenders, there were fewer occurrences of symmetry-breaking. When attackers were considerably shorter than defenders, time to cross court mid-line was significantly shorter than when dyads were composed of athletes of similar height or when attackers were considerably taller than defenders. The data exemplify how interacting task and individual constraints can influence emergent decision-making processes in team ball games.

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Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

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Leucodepletion, the removal of leucocytes from blood products improves the safety of blood transfusion by reducing adverse events associated with the incidental non-therapeutic transfusion of leucocytes. Leucodepletion has been shown to have clinical benefit for immuno-suppressed patients who require transfusion. The selective leucodepletion of blood products by bed side filtration for these patients has been widely practiced. This study investigated the economic consequences in Queensland of moving from a policy of selective leucodepletion to one of universal leucodepletion, that is providing all transfused patients with blood products leucodepleted during the manufacturing process. Using an analytic decision model a cost-effectiveness analysis was conducted. An ICER of $16.3M per life year gained was derived. Sensitivity analysis found this result to be robust to uncertainty in the parameters used in the model. This result argues against moving to a policy of universal leucodepletion. However during the course of the study the policy decision for universal leucodepletion was made and implemented in Queensland in October 2008. This study has concluded that cost-effectiveness is not an influential factor in policy decisions regarding quality and safety initiatives in the Australian blood sector.

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The Australian Government has committed $970 million over 5 years to fund the expansion of preschool education and has established a National Early Childhood Education Partnership Agreement with States and Territories to achieve universal preschool access by 2013. The Partnership Agreement acknowledges the role of State and Territory Government in preschool education, and different approaches to preschool provision. It also recognises differences in current preschool participation rates across states and territories. This paper offers snapshots of a number of different models of preschool provision, spanning traditional sessional approaches to some integrated and innovative approaches within the long day care context. The paper explores the newer long day care model and offers recommendations for the delivery of preschool education within this different context.

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University students are a high risk population for mental health problems, yet few seek professional help when experiencing problems. This study explored the potential role of an online intervention for promoting wellbeing in university students, by investigating students' help-seeking behaviour, intention to use online interventions and student content preference for such interventions; 254 university students responded to an online survey designed for this study. As predicted, students were less likely to seek help as levels of psychological distress increased. Conversely, intention to use an online intervention increased at higher levels of distress, with 39.1%, 49.4% and 57.7% of low, moderate and severely distressed students respectively indicating they would use an online program supporting student well-being. Results suggest that online interventions may be a useful way to provide help to students in need who otherwise may not seek formal help.

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This document presents the newly updated strategic directions for strengthening nursing and midwifery services (SDNM) for the period 2011–2015. Complementing and building on the 2002–2008 SDNM, it seeks to provide policymakers, practitioners and other stakeholders at every level with a flexible framework for broad-based, collaborative action to enhance the capacity of nurses and midwives to contribute to: * universal coverage * people-centred health care * policies affecting their practice and working conditions, and the * scaling up of national health systems to meet global goals and targets. The SDNM for 2011–2015 draws on several key World Health Assembly resolutions, and are underpinned by the associated global policy recommendations and codes of practice. (1,2) After two years of extensive research and consultation, a SDNM task force was developed, and a consensus on a range of specific activities revolving around 13 objectives in five interrelated key results areas (KRAs), was achieved: n health system and service strengthening n policy and practice * education, training and career development * workforce management and * partnership. Stakeholders, although free to prioritize certain parts of the framework to meet their own particular needs, are encouraged to adhere to the cornerstone of collaborative action, namely the common goal enshrined in the core SDNM 2011–2015 vision statement: improved health outcomes for individuals, families and communities through the provision of competent, culturally sensitive, evidence-based nursing and midwifery services.

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This paper reports on a unique approach to inclusive practice that responds to several critical issues highlighted in the first Universal Design (UD) Conference in Yokohama as well as in more recent literature on universal design. The approach, as explained in the paper, involves a not-for-profit community organization, university researchers, and a design action group comprising practitioners from across the design disciplines, together with other specialist consultants, developing a voluntary capacity an independent housing model for people with disabilities and their families or caretakers. With a focus on relationships and "a system that places human beings at the centre in all respects", this paper presents the approach and the ermerging theoretical framework which addresses three issues that afacan and Erbug (2009) propose hinder the integration of universal design with design practice, namely: theory-practice inconsistency involving the lack of flow-on of universal design awareness into design practice; a way of thinking that exhibits very little empathy with and understanding of the requirements of diverse users; and poorly implemented and coordinated collaboration and communication involving designers and other professionals (pp. 731 - 732).

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Monitoring and assessing environmental health is becoming increasingly important as human activity and climate change place greater pressure on global biodiversity. Acoustic sensors provide the ability to collect data passively, objectively and continuously across large areas for extended periods of time. While these factors make acoustic sensors attractive as autonomous data collectors, there are significant issues associated with large-scale data manipulation and analysis. We present our current research into techniques for analysing large volumes of acoustic data effectively and efficiently. We provide an overview of a novel online acoustic environmental workbench and discuss a number of approaches to scaling analysis of acoustic data; collaboration, manual, automatic and human-in-the loop analysis.

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A scaling analysis is performed for the transient boundary layer established adjacent to an inclined flat plate following a ramp cooling boundary condition. The imposed wall temperature decreases linearly up to a specific value over a specific time. It is revealed that if the ramp time is sufficiently large then the boundary layer reaches quasi-steady mode before the growth of the temperature is finished. However, if the ramp time is shorter then the steady state of the boundary layer may be reached after the growth of the temperature is completed. In this case, the ultimate steady state is the same as if the start up had been instantaneous. Note that the cold boundary layer adjacent to the plate is potentially unstable to Rayleigh-Bénard instability if the Rayleigh number exceeds a certain critical value for this cooling case. The onset of instability may set in at different stages of the boundary layer development. A proper identification of the time when the instability may set in is discussed. A numerical verification of the time for the onset of instability is presented in this study. Different flow regimes based on the stability of the boundary layer have also been discussed with numerical results.