149 resultados para Collective representations

em Queensland University of Technology - ePrints Archive


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The aim of this paper is to demonstrate the validity of using Gaussian mixture models (GMM) for representing probabilistic distributions in a decentralised data fusion (DDF) framework. GMMs are a powerful and compact stochastic representation allowing efficient communication of feature properties in large scale decentralised sensor networks. It will be shown that GMMs provide a basis for analytical solutions to the update and prediction operations for general Bayesian filtering. Furthermore, a variant on the Covariance Intersect algorithm for Gaussian mixtures will be presented ensuring a conservative update for the fusion of correlated information between two nodes in the network. In addition, purely visual sensory data will be used to show that decentralised data fusion and tracking of non-Gaussian states observed by multiple autonomous vehicles is feasible.

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Random walk models based on an exclusion process with contact effects are often used to represent collective migration where individual agents are affected by agent-to-agent adhesion. Traditional mean field representations of these processes take the form of a nonlinear diffusion equation which, for strong adhesion, does not predict the averaged discrete behavior. We propose an alternative suite of mean-field representations, showing that collective migration with strong adhesion can be accurately represented using a moment closure approach.

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This paper demonstrates that in order to understand and design for interactions in complex work environments, a variety of representational artefacts must be developed and employed. A study was undertaken to explore the design of better interaction technologies to support patient record keeping in a dental surgery. The domain chosen is a challenging real context that exhibits problems that could potentially be solved by ubiquitous computing and multi-modal interaction technologies. Both transient and durable representations were used to develop design understandings. We describe the representations, the kinds of insights developed from the representations and the way that the multiple representations interact and carry forward in the design process.

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We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

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The capacity to identify, interpret, and prioritise environmental issues is critical in the management of corporate reputation. In spite of the significance of these abilities for corporate reputation management, there has been little effort to document and describe internal organizational influences on these capacities. Contrary to this state of affairs in the discipline of public relations, a long history of ethnographic research in cultural anthropology documents how sets of shared environmental perceptions can influence and moderate environmental factors in cultural populations (see for example, Durham, 1991 ). This study explores how cultural “frames of reference” derived from shared values and assumptions among organizational members influence organizational perceptions, and consequently, organizational actions. Specifically, this study explores how a central attribute of organizational culture--the property of cultural selection-- influences perceptions of organizational reputation held by organizational members. Perceptions of reputation among organizational members are obvious drivers to both the nature of and rationale for organizational communication strategies and responses. These perceptions are the result of collective processes that synthesise (with varying degrees of consensus) member conceptualisations, interpretations, and representations of the environmental realities in which their organization operate. To explore how cultural selection influences member perceptions of organizational reputation, this study employs ethnographic research including 20 depth interviews and six months of organizational observation in the focal organization. We argue that while external indicators of organizational reputation are acknowledged by members as significant, the internal action of cultural selection is a far stronger influence on organizational action.

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This paper explores the way men are represented in present-day advertising. Most gender related studies have concentrated in studying women in advertising and claim that men are still represented as the dominant gender and in more active, independent and functional roles than women. This paper asks whether this still holds for advertising in the beginning of 21st century. Many cultural changes may have broken the earlier stereotypes, for example changes in the family life, attitudes toward various sexual identities, concepts of masculinity and femininity, and changes in cultural style.

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As an Aboriginal woman currently reviewing feminist literature in Australia, I have found that representations of Aboriginal women's gender have been generated predominantly by women anthropologists. Australian feminists utilise this literature in their writing and teaching and accept its truths without question; the most often quoted ethnographic text is Diane Bell's Daughters of the Dreaming (1983a).1 Feminists' lack of critical engagement with this literature implies that they are content to accept women anthropologists' representations because Aboriginal women are not central to their constructions of feminism.2 Instead the Aboriginal woman is positioned on the margins, a symbol of difference; a reminder that it is feminists who are the bearers of true womanhood.

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International and national representations of the beach perpetuate normative female concepts by maintaining dominant masculine myths, such as that of the heroic lifesaver and tanned sunbaker. Female experiences on the beach are traditionally associated with rhetorics of danger and peril, contrasted to the welcomed and protective gaze of the beach male. Conventional understandings of the gaze promote male surveillance of women, and although some resistance exists, the beach primarily remains a place to observe the female form. This article attempts to explore currents of resistance at the beach through a self-reflexive examination of Schoolies. Although the event is fixed within patriarchal codes and structures, small eddies of resistance exist amongst female participants in light of increasing awareness of masculine hegemony. The Australian beach remains a contested site of multiple constructs of gender and national identity. This article reveals the changing tides of resistance.

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Association rule mining has made many advances in the area of knowledge discovery. However, the quality of the discovered association rules is a big concern and has drawn more and more attention recently. One problem with the quality of the discovered association rules is the huge size of the extracted rule set. Often for a dataset, a huge number of rules can be extracted, but many of them can be redundant to other rules and thus useless in practice. Mining non-redundant rules is a promising approach to solve this problem. In this paper, we firstly propose a definition for redundancy; then we propose a concise representation called Reliable basis for representing non-redundant association rules for both exact rules and approximate rules. An important contribution of this paper is that we propose to use the certainty factor as the criteria to measure the strength of the discovered association rules. With the criteria, we can determine the boundary between redundancy and non-redundancy to ensure eliminating as many redundant rules as possible without reducing the inference capacity of and the belief to the remaining extracted non-redundant rules. We prove that the redundancy elimination based on the proposed Reliable basis does not reduce the belief to the extracted rules. We also prove that all association rules can be deduced from the Reliable basis. Therefore the Reliable basis is a lossless representation of association rules. Experimental results show that the proposed Reliable basis can significantly reduce the number of extracted rules.