921 resultados para Conditional moments


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Ecological studies are based on characteristics of groups of individuals, which are common in various disciplines including epidemiology. It is of great interest for epidemiologists to study the geographical variation of a disease by accounting for the positive spatial dependence between neighbouring areas. However, the choice of scale of the spatial correlation requires much attention. In view of a lack of studies in this area, this study aims to investigate the impact of differing definitions of geographical scales using a multilevel model. We propose a new approach -- the grid-based partitions and compare it with the popular census region approach. Unexplained geographical variation is accounted for via area-specific unstructured random effects and spatially structured random effects specified as an intrinsic conditional autoregressive process. Using grid-based modelling of random effects in contrast to the census region approach, we illustrate conditions where improvements are observed in the estimation of the linear predictor, random effects, parameters, and the identification of the distribution of residual risk and the aggregate risk in a study region. The study has found that grid-based modelling is a valuable approach for spatially sparse data while the SLA-based and grid-based approaches perform equally well for spatially dense data.

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We propose a topological localization method based on optical flow information. We analyse the statistical characteristics of the optical flow signal and demonstrate that the flow vectors can be used to identify and describe key locations in the environment. The key locations (nodes) correspond to significant scene changes and depth discontinuities. Since optical flow vectors contain position, magnitude and angle information, for each node, we extract low and high order statistical moments of the vectors and use them as descriptors for that node. Once a database of nodes and their corresponding optical flow features is created, the robot can perform topological localization by using the Mahalanobis distance between the current frame and the database. This is supported by field trials, which illustrate the repeatability of the proposed method for detecting and describing key locations in indoor and outdoor environments in challenging and diverse lighting conditions.

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The Children’s Book Council of Australia (CBCA) administers the oldest national prize for children’s literature in Australia. Each year, the CBCA confers “Book of the Year” awards to literature for young people in five categories. In 2001, the establishment of an “Early Childhood” category opened up the venerable “Picture Book” category (first awarded in 1955) to books with an implied readership up to 18 years of age. As a result, this category has emerged in recent years as a highly visible space within which the CBCA can contest discourses of cultural marginalisation insofar as Australian (“colonial”) literature is constructed as inferior or adjunct to the major Anglophone literary traditions, and the consistent identification of children’s literature (and, indeed, of children) as lesser than its ‘adult’ counterparts. The CBCA is engaged in defining, evaluating, and legitimising a tradition of Australian children’s literature which is underpinned by a canonical impulse, and is a reflexive practice of self-definition, self-evaluation and self-legitimisation for the CBCA itself. While it is obviously problematic to identify award winners as a canon, it is equally obvious that literary prizing is a cultural practice derived from the logic of canonicity. In his discussion of the United States’s Newbery Medal, Kenneth Kidd notes that “Medal books are instant classics, the selection process an ostensible simulation of the test of time” (169) and that “the Medal is part of the canonical architecture of children's literature” (169). Thus, it is instructive to consider the visions and values of the national, of the social, and of the literary-aesthetic, in the picture books chosen by the Children’s Book Council of Australia (CBCA) as the “best” of the early twenty-first century. These books not only constitute a kind of canon for contemporary Australian children’s literature, but may well come to define what contemporary Australian children’s literature means in the wider literary field. The Book of the Year: Picture Book awards given by the CBCA since 2001 demonstrate that it is not only true of the Booker Prize that, “The choices of winning books reflect not only on the books themselves, then, but also back on the Prize, affecting its reputation and creating journalistic capital which is vital for the Prize to achieve its prominence and impact.” (81). Many of the twenty-first century CBCA award-winning picture books complicate traditional or comfortable understanding of Australianness, children’s literature, or “appropriate” modes of form and content, reminding us that “moments when texts resist or complicate recuperation into national discourses offer fruitful points for exploring the relationships between text and celebratory context” (Roberts 6). The CBCA has taken the opportunities offered by the liberation of the Picture Book category from an implied readership to challenge dominant constructions of children’s literature in Australia, and in so doing, are engaged in overt practices of canonicity with potentially long-lasting effects. Works Cited: Kidd, Kenneth. “Prizing Children’s Literature: The Case of Newbery Gold.” Children's Literature 35 (2007): 166-190. Roberts, Gillian. Prizing Literature: The Celebration and Circulation of National Culture. Toronto: U Toronto P, 2011. Squires, Claire. “Book Marketing and the Booker Prize.” Judging a Book by Its Cover: Fans, Publishers, Designers, and the Marketing of Fiction. Eds. Nicole Matthews and Nickianne Moody. Aldershot: Ashgate, 2007. 71-82.

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A collaborative video with Avril Huddy where two viewpoints, performer and documenter, were presented simultaneously to investigate Arakawa and Gin’s notion of “boundary-swaying”. In this performance-work, the performer influences what the camera is able to capture by engaging the documenter in a form of improvised dance. The performer’s movements appear impulsive and unpredictable, testing ways for the documenter to frame the performer’s movement. The images revealed by the documenter’s camera reflect a complexity of moments and co-incidences, evoking a sense of the performer’s embodied thinking within improvised movement. While a second camera uses a conventional wide angle shot to document the unfolding of the performance-work and track the connection between the documenter and the performer. While the performance-work itself is still highly-experimental, the ideas underpinning this exploration suggest how future investigations integrating more sensitive technology such as motion capture and tracking devises may be investigated. This performance-work formed part of the Creative Response Exhibition curated by Alan Prohm, Bill Lavender and Jason Nelson and a peer-review committee as part of the proceedings of the AG3 Online: Third International Arakawa and Gins Architecture and Philosophy Conference, hosted by the Centre for Public Culture and Ideas at Griffith University.

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An experiment in narrative play. Ten Threaders explored an urban physical space and creatively related what they encountered via mobile to their Weavers. Weavers creatively shaped this material to fashion a collaborative story on the fly, framed by a theme of loss and connection. The Weavers On Threader’s Day, during the hours of the lost, Threaders and Weavers collaborate to recover moments of connection and loss, of missed (or not) meetings and inevitable (or not) parting. Threaders: Your path begins near Brick Lane. Use your gift to discover threads. The threads may be thin at start, as fine as an inkling or as fleet as a passing memory. Yet they pull forth deep personal moments which in turn lead to the most powerful stories in human experience, ones that partake of the mythic inevitable. On a street in London, as the sun declines, Gilgamesh pursues, Orpheus sings, Perdita boards a ship, Eurydice walks forever toward the light… as the Lady of Shalott works her loom. Weavers: The fabric a Threader stitches through is the ancient story rediscovered every time one person follows or leads another. As your Threader describes the moments and aspects of this journey to you, in spoken words and written words and in images sent from their phone, you weave these impressions into a multithreaded story, in concert with the other Weavers. And you help guide your Threader across the storyscape, with your narrative intuition and by pulling the threads that connect to times in your own life.

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Section 95AT of the Competition and Consumer Act 2010 (Cth) (CCA) provides that the Tribunal may grant an authorisation to acquire shares or assets that would otherwise contravene s 50. Section 95AT was inserted by the Trade Practices Legislation Amendment Act 2006 (Cth) and commenced on 1 January 2007. In Application for Authorisation of Macquarie Generation by AGL Energy Limited, (AGL Energy) the Tribunal has for the first time granted AGL Energy Limited (AGL) a conditional authorisation to acquire the assets of Macquarie Generation from the NSW Government.

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The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10(-14)). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility.

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The adhesion molecule L1, which is extensively characterized in the nervous system, is also expressed in dendritic cells (DCs), but its function there has remained elusive. To address this issue, we ablated L1 expression in DCs of conditional knockout mice. L1-deficient DCs were impaired in adhesion to and transmigration through monolayers of either lymphatic or blood vessel endothelial cells, implicating L1 in transendothelial migration of DCs. In agreement with these findings, L1 was expressed in cutaneous DCs that migrated to draining lymph nodes, and its ablation reduced DC trafficking in vivo. Within the skin, L1 was found in Langerhans cells but not in dermal DCs, and L1 deficiency impaired Langerhans cell migration. Under inflammatory conditions, L1 also became expressed in vascular endothelium and enhanced transmigration of DCs, likely through L1 homophilic interactions. Our results implicate L1 in the regulation of DC trafficking and shed light on novel mechanisms underlying transendothelial migration of DCs. These observations might offer novel therapeutic perspectives for the treatment of certain immunological disorders.

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In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

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This article outlines the knowledge and skills students develop when they engage in digital media production and analysis in school settings. The metaphor of ‘digital building blocks’ is used to describe the material practices, conceptual understandings and production of knowledge that lead to the development of digital media literacy. The article argues that the two established approaches to media literacy education, critical reading and media production, do not adequately explain how students develop media knowledge. It suggests there has been too little focus on material practices and how these relate to the development of conceptual understanding in media learning. The article explores empirical evidence from a four-year investigation in a primary school in Queensland, Australia using actor–network theory to explore ‘moments of translation’ as students deploy technologies and concepts to materially participate in digital culture. A generative model of media learning is presented with four categories of building blocks that isolate the specific skills and knowledge that can be taught and learnt to promote participation in digital media contexts: digital materials, conceptual understandings, media production and media analysis. The final section of the article makes initial comments on how the model might become the basis for curriculum development in schools and argues that further empirical research needs to occur to confirm the model’s utility.

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Rapid development of plug-in hybrid electric vehicles (PHEVs) brings new challenges and opportunities to the power industry. A large number of idle PHEVs can potentially be employed to form a distributed energy storage system for supporting renewable generation. To reduce the negative effects of unsteady renewable generation outputs, a stochastic optimization-based dispatch model capable of handling uncertain outputs of PHEVs and renewable generation is formulated in this paper. The mathematical expectations, second-order original moments, and variances of wind and photovoltaic (PV) generation outputs are derived analytically. Incorporated all the derived uncertainties, a novel generation shifting objective is proposed. The cross-entropy (CE) method is employed to solve this optimal dispatch model. Multiple patterns of renewable generation depending on seasons and renewable market shares are investigated. The feasibility and efficiency of the developed optimal dispatch model, as well as the CE method, are demonstrated with a 33-node distribution system.

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Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

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This paper discusses Compulsory Income Management (CIM) in Australia and the implications of technology backed forms of surveillance and increasingly conditional benefit payments. The CIM project raises important questions about requiring people to take greater responsibility for their personal behaviour when they no longer have control over key financial aspects of their lives. Some Indigenous communities have resisted the BasicsCard, because CIM was imposed with little prior consultation or subsequent independent evaluation. The compulsory income management of individuals by a paternalist welfare state contradicts and undermines the purported policy aims that they become less welfare dependent and more positively engaged with the world of paid employment and does little to address the growing condition of poverty in Australia.

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Bayesian networks (BNs) are graphical probabilistic models used for reasoning under uncertainty. These models are becoming increasing popular in a range of fields including ecology, computational biology, medical diagnosis, and forensics. In most of these cases, the BNs are quantified using information from experts, or from user opinions. An interest therefore lies in the way in which multiple opinions can be represented and used in a BN. This paper proposes the use of a measurement error model to combine opinions for use in the quantification of a BN. The multiple opinions are treated as a realisation of measurement error and the model uses the posterior probabilities ascribed to each node in the BN which are computed from the prior information given by each expert. The proposed model addresses the issues associated with current methods of combining opinions such as the absence of a coherent probability model, the lack of the conditional independence structure of the BN being maintained, and the provision of only a point estimate for the consensus. The proposed model is applied an existing Bayesian Network and performed well when compared to existing methods of combining opinions.