94 resultados para % of sample area
em Queensland University of Technology - ePrints Archive
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We study sample-based estimates of the expectation of the function produced by the empirical minimization algorithm. We investigate the extent to which one can estimate the rate of convergence of the empirical minimizer in a data dependent manner. We establish three main results. First, we provide an algorithm that upper bounds the expectation of the empirical minimizer in a completely data-dependent manner. This bound is based on a structural result due to Bartlett and Mendelson, which relates expectations to sample averages. Second, we show that these structural upper bounds can be loose, compared to previous bounds. In particular, we demonstrate a class for which the expectation of the empirical minimizer decreases as O(1/n) for sample size n, although the upper bound based on structural properties is Ω(1). Third, we show that this looseness of the bound is inevitable: we present an example that shows that a sharp bound cannot be universally recovered from empirical data.
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This chapter contains sections titled: Introduction ICZM and sustainable development of coastal zone International legal framework for ICZM Implementation of international legal obligations in domestic arena Concluding remarks References
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Background The Environments for Healthy Living (EFHL) study is a repeated sample, longitudinal birth cohort in South East Queensland, Australia. We describe the sample characteristics and profile of maternal, household, and antenatal exposures. Variation and data stability over recruitment years were examined. Methods Four months each year from 2006, pregnant women were recruited to EFHL at routine antenatal visits on or after 24 weeks gestation, from three public maternity hospitals. Participating mothers completed a baseline questionnaire on individual, familial, social and community exposure factors. Perinatal data were extracted from hospital birth records. Descriptive statistics and measures of association were calculated comparing the EFHL birth sample with regional and national reference populations. Data stability of antenatal exposure factors was assessed across five recruitment years (2006–2010 inclusive) using the Gamma statistic for ordinal data and chi-squared for nominal data. Results Across five recruitment years 2,879 pregnant women were recruited which resulted in 2904 live births with 29 sets of twins. EFHL has a lower representation of early gestational babies, fewer still births and a lower percentage of low birth weight babies, when compared to regional data. The majority of women (65%) took a multivitamin supplement during pregnancy, 47% consumed alcohol, and 26% reported having smoked cigarettes. There were no differences in rates of a range of antenatal exposures across five years of recruitment, with the exception of increasing maternal pre-pregnancy weight (p=0.0349), decreasing rates of high maternal distress (p=0.0191) and decreasing alcohol consumption (p<0.0001). Conclusions The study sample is broadly representative of births in the region and almost all factors showed data stability over time. This study, with repeated sampling of birth cohorts over multiple years, has the potential to make important contributions to population health through evaluating longitudinal follow-up and within cohort temporal effects.
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In this paper I describe and analyse the socio-educational significance of a theatre arts approach to learning for young adults in Jamaica, implemented by the Area Youth Foundation (AYF). Briefly outlining the genesis and development of the AYF, I provide snapshots of the experiences and destinations of some of its young participants. The paper discusses AYF workshops to show how the pedagogy was shaped by the expressive arts and based on the critical praxis approach systematized by Paulo Freire in adult education and Augusto Boal in theatre. Based on interviews with AYF’s leader and some of the learners, I discuss how the foundation’s motto, “Youth Empowerment Through the Arts,” is played out in workshops and creative productions that are simultaneously learner-driven and teacher-guided, with the powerful impact of inspiring politically thoughtful creativity and skills in youths from less-privileged communities.
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A new approach is proposed for obtaining a non-linear area-based equivalent model of power systems to express the inter-area oscillations using synchronised phasor measurements. The generators that remain coherent for inter-area disturbances over a wide range of operating conditions define the areas, and the reduced model is obtained by representing each area by an equivalent machine. The parameters of the reduced system are identified by processing the obtained measurements, and a non-linear Kalman estimator is then designed for the estimation of equivalent area angles and frequencies. The simulation of the approach on a two-area system shows substantial reduction of non-inter-area modes in the estimated angles. The proposed methods are also applied to a ten-machine system to illustrate the feasibility of the approach on larger and meshed networks.
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Large area, highly uniform vertically aligned carbon nanotips (VACNTP) and other nanostructures have been grown on silicon (100) substrates with Ni catalyst in the low-temperature, low-frequency, high-density inductively coupled plasmas (ICP) of methane-hydrogen-argon gas mixtures. The control strategies for the morphology, crystalline structure and chemical states of the resulting nanostructures by varying the growth conditions are proposed. XRD and Roman analyses confirm that the nanotips are well graphitized, which is favorable for the field emission applications.
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The transfer of chemical vapor deposited graphene is a crucial process, which can affect the quality of the transferred films and compromise their application in devices. Finding a robust and intrinsically clean material capable of easing the transfer of graphene without interfering with its properties remains a challenge. We here propose the use of an organic compound, cyclododecane, as a transfer material. This material can be easily spin coated on graphene and assist the transfer, leaving no residues and requiring no further removal processes. The effectiveness of this transfer method for few-layer graphene on a large area was evaluated and confirmed by microscopy, Raman spectroscopy, x-ray photoemission spectroscopy, and four-point probe measurements. Schottky-barrier solar cells with few-layer graphene were fabricated on silicon wafers by using the cyclododecane transfer method and outperformed reference cells made by standard methods.
Associations between area-level disadvantage and DMFT among a birth cohort of Indigenous Australians
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Background Individual-level factors influence DMFT, but little is known about the influence of community environment. This study examines associations between community-level influences and DMFT among a birth cohort of Indigenous Australians aged 16–20 years. Methods Data were collected as part of Wave 3 of the Aboriginal Birth Cohort study. Fifteen community areas were established and the sample comprised 442 individuals. The outcome variable was mean DMFT with explanatory variables including diet and community disadvantage (access to services, infrastructure and communications). Data were analysed using multilevel regression modelling. Results In a null model, 13.8% of the total variance in mean DMFT was between community areas, which increased to 14.3% after adjusting for sex, age and diet. Addition of the community disadvantage variable decreased the variance between areas by 4.8%, indicating that community disadvantage explained one-third of the area-level variance. Residents of under-resourced communities had significantly higher mean DMFT (β=3.86, 95% CI 0.02¬, 7.70) after adjusting for sex, age and diet. Conclusions Living in under-resourced communities was associated with greater DMFT among this disadvantaged population, indicating that policies aiming to reduce oral health-related inequalities among vulnerable groups may benefit from taking into account factors external to individual-level influences.
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In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us to understand the impact of estimation error on the performance of in-sample optimal portfolios. Key Words: minimum-variance frontier; efficiency set constants; finite sample distribution
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The effect of sample geometry on the melting rates of burning iron rods was assessed. Promoted-ignition tests were conducted with rods having cylindrical, rectangular, and triangular cross-sectional shapes over a range of cross-sectional areas. The regression rate of the melting interface (RRMI) was assessed using a statistical approach which enabled the quantification of confidence levels for the observed differences in RRMI. Statistically significant differences in RRMI were observed for rods with the same cross-sectional area but different cross-sectional shape. The magnitude of the proportional difference in RRMI increased with the cross-sectional area. Triangular rods had the highest RRMI, followed by rectangular rods, and then cylindrical rods. The dependence of RRMI on rod shape is shown to relate to the action of molten metal at corners. The corners of the rectangular and triangular rods melted faster than the faces due to their locally higher surface area to volume ratios. This phenomenon altered the attachment geometry between liquid and solid phases, increasing the surface area available for heat transfer, causing faster melting. Findings relating to the application of standard flammability test results in industrial situations are also presented.
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This paper present an efficient method using system state sampling technique in Monte Carlo simulation for reliability evaluation of multi-area power systems, at Hierarchical Level One (HLI). System state sampling is one of the common methods used in Monte Carlo simulation. The cpu time and memory requirement can be a problem, using this method. Combination of analytical and Monte Carlo method known as Hybrid method, as presented in this paper, can enhance the efficiency of the solution. Incorporation of load model in this study can be utilised either by sampling or enumeration. Both cases are examined in this paper, by application of the methods on Roy Billinton Test System(RBTS).
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This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.
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A major priority for cancer control agencies is to reduce geographical inequalities in cancer outcomes. While the poorer breast cancer survival among socioeconomically disadvantaged women is well established, few studies have looked at the independent contribution that area- and individual-level factors make to breast cancer survival. Here we examine relationships between geographic remoteness, area-level socioeconomic disadvantage and breast cancer survival after adjustment for patients’ socio- demographic characteristics and stage at diagnosis. Multilevel logistic regression and Markov chain Monte Carlo simulation were used to analyze 18 568 breast cancer cases extracted from the Queensland Cancer Registry for women aged 30 to 70 years diagnosed between 1997 and 2006 from 478 Statistical Local Areas in Queensland, Australia. Independent of individual-level factors, area-level disadvantage was associated with breast-cancer survival (p=0.032). Compared to women in the least disadvantaged quintile (Quintile 5), women diagnosed while resident in one of the remaining four quintiles had significantly worse survival (OR 1.23, 1.27, 1.30, 1.37 for Quintiles 4, 3, 2 and 1 respectively).) Geographic remoteness was not related to lower survival after multivariable adjustment. There was no evidence that the impact of area-level disadvantage varied by geographic remoteness. At the individual level, Indigenous status, blue collar occupations and advanced disease were important predictors of poorer survival. A woman’s survival after a diagnosis of breast cancer depends on the socio-economic characteristics of the area where she lives, independently of her individual-level characteristics. It is crucial that the underlying reasons for these inequalities be identified to appropriately target policies, resources and effective intervention strategies.
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The impact of acid rock drainage (ARD) and eutrophication on microbial communities in stream sediments above and below an abandoned mine site in the Adelaide Hills, South Australia, was quantified by PLFA analysis. Multivariate analysis of water quality parameters, including anions, soluble heavy metals, pH, and conductivity, as well as total extractable metal concentrations in sediments, produced clustering of sample sites into three distinct groups. These groups corresponded with levels of nutrient enrichment and/or concentration of pollutants associated with ARD. Total PLFA concentration, which is indicative of microbial biomass, was reduced by >70% at sites along the stream between the mine site and as far as 18 km downstream. Further downstream, however, recovery of the microbial abundance was apparent, possibly reflecting dilution effect by downstream tributaries. Total PLFA was >40% higher at, and immediately below, the mine site (0-0.1 km), compared with sites further downstream (2.5-18 km), even after accounting for differences in specific surface area of different sediment samples. The increased microbial population in the proximity of the mine source may be associated with the presence of a thriving iron-oxidizing bacteria community as a consequence of optimal conditions for these organisms while the lower microbial population further downstream corresponded with greater sediments' metal concentrations. PCA of relative abundance revealed a number of PLFAs which were most influential in discriminating between ARD-polluted sites and the rest of the sites. These PLFA included the hydroxy fatty acids: 2OH12:0, 3OH12:0, 2OH16:0; the fungal marker: 18:2ω6; the sulfate-reducing bacteria marker 10Me16:1ω7; and the saturated fatty acids 12:0, 16:0, 18:0. Partial constrained ordination revealed that the environmental parameters with the greatest bearing on the PLFA profiles included pH, soluble aluminum, total extractable iron, and zinc. The study demonstrated the successful application of PLFA analysis to rapidly assess the toxicity of ARD-affected waters and sediments and to differentiate this response from the effects of other pollutants, such as increased nutrients and salinity.