218 resultados para stratified random sampling


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In Thomas Mann’s tetralogy of the 1930s and 1940s, Joseph and His Brothers, the narrator declares history is not only “that which has happened and that which goes on happening in time,” but it is also “the stratified record upon which we set our feet, the ground beneath us.” By opening up history to its spatial, geographical, and geological dimensions Mann both predicts and encapsulates the twentieth-century’s “spatial turn,” a critical shift that divested geography of its largely passive role as history’s “stage” and brought to the fore intersections between the humanities and the earth sciences. In this paper, I draw out the relationships between history, narrative, geography, and geology revealed by this spatial turn and the questions these pose for thinking about the disciplinary relationship between geography and the humanities. As Mann’s statement exemplifies, the spatial turn itself has often been captured most strikingly in fiction, and I would argue nowhere more so than in Graham Swift’s Waterland (1983) and Anne Michaels’s Fugitive Pieces (1996), both of which present space, place, and landscape as having a palpable influence on history and memory. The geographical/geological line that runs through both Waterland and Fugitive Pieces continues through Tim Robinson’s non-fictional, two-volume “topographical” history Stones of Aran. Robinson’s Stones of Aran—which is not history, not geography, and not literature, and yet is all three—constructs an imaginative geography that renders inseparable geography, geology, history, memory, and the act of writing.

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We study the natural problem of secure n-party computation (in the computationally unbounded attack model) of circuits over an arbitrary finite non-Abelian group (G,⋅), which we call G-circuits. Besides its intrinsic interest, this problem is also motivating by a completeness result of Barrington, stating that such protocols can be applied for general secure computation of arbitrary functions. For flexibility, we are interested in protocols which only require black-box access to the group G (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). Our investigations focus on the passive adversarial model, where up to t of the n participating parties are corrupted.

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Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of local texture information and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. The results on the parameter sensitivity demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusions ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.

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This paper presents a method for the estimation of thrust model parameters of uninhabited airborne systems using specific flight tests. Particular tests are proposed to simplify the estimation. The proposed estimation method is based on three steps. The first step uses a regression model in which the thrust is assumed constant. This allows us to obtain biased initial estimates of the aerodynamic coeficients of the surge model. In the second step, a robust nonlinear state estimator is implemented using the initial parameter estimates, and the model is augmented by considering the thrust as random walk. In the third step, the estimate of the thrust obtained by the observer is used to fit a polynomial model in terms of the propeller advanced ratio. We consider a numerical example based on Monte-Carlo simulations to quantify the sampling properties of the proposed estimator given realistic flight conditions.

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Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

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Objective This study compared correlates of physical activity (PA) among African-American and white girls of different weight groups to guide future interventions. Research Methods and Procedures Participants were 1015 girls (mean age, 14.6 years; 45% African-American) from 12 high schools in South Carolina who served as control subjects for a school-based intervention. Post-intervention measures obtained at the end of ninth grade were used. PA was measured using the Three-Day PA Recall, and a questionnaire measured social-cognitive and environmental variables thought to mediate PA. Height and weight were measured, and BMI was calculated. Girls were stratified by race and categorized into three groups, based on BMI percentiles for girls from CDC growth charts: normal (BMI < 85th percentile), at risk (BMI, 85th to 94th percentile), and overweight (BMI ≥ 95th percentile). Girls were further divided into active and low-active groups, based on a vigorous PA standard (average of one or more 30-minute blocks per day per 3-day period). Mixed-model ANOVA was used to compare factors among groups, treating school as a random effect Results None of the social-cognitive or environmental variables differed by weight status for African-American or white girls. Perceived behavioral control and sports team participation were significantly higher in girls who were more active, regardless of weight or race group. In general, social-cognitive variables seem to be more related to activity in white girls, whereas environmental factors seem more related to activity in African-American girls. Discussion PA interventions should be tailored to the unique needs of girls based on PA levels and race, rather than on weight status alone.

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As part of a wider study to develop an ecosystem-health monitoring program for wadeable streams of south-eastern Queensland, Australia, comparisons were made regarding the accuracy, precision and relative efficiency of single-pass backpack electrofishing and multiple-pass electrofishing plus supplementary seine netting to quantify fish assemblage attributes at two spatial scales (within discrete mesohabitat units and within stream reaches consisting of multiple mesohabitat units). The results demonstrate that multiple-pass electrofishing plus seine netting provide more accurate and precise estimates of fish species richness, assemblage composition and species relative abundances in comparison to single-pass electrofishing alone, and that intensive sampling of three mesohabitat units (equivalent to a riffle-run-pool sequence) is a more efficient sampling strategy to estimate reach-scale assemblage attributes than less intensive sampling over larger spatial scales. This intensive sampling protocol was sufficiently sensitive that relatively small differences in assemblage attributes (<20%) could be detected with a high statistical power (1-β > 0.95) and that relatively few stream reaches (<4) need be sampled to accurately estimate assemblage attributes close to the true population means. The merits and potential drawbacks of the intensive sampling strategy are discussed, and it is deemed to be suitable for a range of monitoring and bioassessment objectives.

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We study the natural problem of secure n-party computation (in the passive, computationally unbounded attack model) of the n-product function f G (x 1,...,x n ) = x 1 ·x 2 ⋯ x n in an arbitrary finite group (G,·), where the input of party P i is x i  ∈ G for i = 1,...,n. For flexibility, we are interested in protocols for f G which require only black-box access to the group G (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). Our results are as follows. First, on the negative side, we show that if (G,·) is non-abelian and n ≥ 4, then no ⌈n/2⌉-private protocol for computing f G exists. Second, on the positive side, we initiate an approach for construction of black-box protocols for f G based on k-of-k threshold secret sharing schemes, which are efficiently implementable over any black-box group G. We reduce the problem of constructing such protocols to a combinatorial colouring problem in planar graphs. We then give two constructions for such graph colourings. Our first colouring construction gives a protocol with optimal collusion resistance t < n/2, but has exponential communication complexity O(n*2t+1^2/t) group elements (this construction easily extends to general adversary structures). Our second probabilistic colouring construction gives a protocol with (close to optimal) collusion resistance t < n/μ for a graph-related constant μ ≤ 2.948, and has efficient communication complexity O(n*t^2) group elements. Furthermore, we believe that our results can be improved by further study of the associated combinatorial problems.

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In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0⩽trandom collection of functions, among the n players, each player gets a subset of S, in such a way that any u players together hold all the secret seeds in S while any t or fewer players will lack at least one element from S. The pseudo-random function is then computed as where fsi(·)'s are poly-random functions. One question raised by Micali and Sidney is how to distribute the secret seeds satisfying the above condition such that the number of seeds, d, is as small as possible. In this paper, we continue the work of Micali and Sidney. We first provide a general framework for shared generation of pseudo-random function using cumulative maps. We demonstrate that the Micali–Sidney scheme is a special case of this general construction. We then derive an upper and a lower bound for d. Finally we give a simple, yet efficient, approximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.

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In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0 ≤ t < u ≤ n. The idea behind the Micali-Sidney scheme is to generate and distribute secret seeds S = s1, . . . , sd of a poly-random collection of functions, among the n players, each player gets a subset of S, in such a way that any u players together hold all the secret seeds in S while any t or fewer players will lack at least one element from S. The pseudo-random function is then computed as where f s i (·)’s are poly-random functions. One question raised by Micali and Sidney is how to distribute the secret seeds satisfying the above condition such that the number of seeds, d, is as small as possible. In this paper, we continue the work of Micali and Sidney. We first provide a general framework for shared generation of pseudo-random function using cumulative maps. We demonstrate that the Micali-Sidney scheme is a special case of this general construction.We then derive an upper and a lower bound for d. Finally we give a simple, yet efficient, approximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.

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A laboratory experiment was set up in small chambers for monitoring greenhouse gas emissions and determining the most suitable time for sampling. A six-treatment experiment was conducted, including a one week pre-incubation and a week for incubation. Timelines for sampling were 1, 2, 3, 6 and 24 hours after closing the lid of the incubation chambers. Variation in greenhouse gas fluxes was high due to the time of sampling. The rates of gas emissions increased in first three hours and decreased afterward. The rates of greenhouse gas emissions at 3 hours after closing lids was close to the mean for the 24-h period.

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This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.

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Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

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Background Advance care planning is regarded as integral to better patient outcomes yet little is known about the prevalence of advance directives in Australia. Aims To determine the prevalence of advance directives (ADs) in the Australian population. Methods A national telephone survey about estate and advance planning. Sample was stratified by age (18-45 and >45 years) and quota sampling occurred based on population size in each State and Territory. Results Fourteen percent of the Australian population has an AD. There is State variation with people from South Australia and Queensland more likely to have an AD than people from other states. Will making and particularly completion of a financial enduring power of attorney are associated with higher rates of AD completion. Standard demographic variables were of limited use in predicting whether a person would have an AD. Conclusions Despite efforts to improve uptake of advance care planning (including ADs), barriers remain. One likely trigger for completing an AD and advance care planning is undertaking a wider future planning process (e.g. making a will or financial enduring power of attorney). This presents opportunities to increase advance care planning but steps are needed to ensure that planning which occurs outside the health system is sufficiently informed and supported by health information so that it is useful in the clinical setting. Variations by State could also suggest that redesign of regulatory frameworks (such as a user-friendly and well publicised form backed by statute) may help improve uptake of ADs.