869 resultados para Scenographic Representations


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Jonzi D, one of the leading Hip Hop voices in the UK, creates contemporary theatrical works that merge dance, street art, original scored music and contemporary rap poetry, to create theatrical events that expand a thriving sense of a Hip Hop nation with citizens in the UK, throughout southern Africa and the rest of the world. In recent years Hip Hop has evolved as a performance genre in and of itself that not only borrows from other forms but vitally now contributes back to the body of contemporary practice in the performing arts. As part of this work Jonzi’s company Jonzi D Productions is committed to creating and touring original Hip Hop theatre that promotes the continuing development and awareness of a nation with its own language, culture and currency that exists without borders. Through the deployment of a universal voice from the local streets of Johannesburg and the East End of London, Jonzi D creates a form of highly energized performance that elevates Hip Hop as great democratiser between the highly developed global and under resourced local in the world. It is the staging of this democratised and technologised future (and present), that poses the greatest challenge for the scenographer working with Jonzi and his company, and the associated deprogramming and translation of the artists particular filmic vision to the stage, that this discussion will explore. This paper interrogates not only how a scenographic strategy can support the existence of this work but also how the scenographer as outsider can enter and influence this nation.

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RatSLAM is a biologically-inspired visual SLAM and navigation system that has been shown to be effective indoors and outdoors on real robots. The spatial representation at the core of RatSLAM, the experience map, forms in a distributed fashion as the robot learns the environment. The activity in RatSLAM’s experience map possesses some geometric properties, but still does not represent the world in a human readable form. A new system, dubbed RatChat, has been introduced to enable meaningful communication with the robot. The intention is to use the “language games” paradigm to build spatial concepts that can be used as the basis for communication. This paper describes the first step in the language game experiments, showing the potential for meaningful categorization of the spatial representations in RatSLAM.

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RatSLAM is a system for vision-based Simultaneous Localisation and Mapping (SLAM) inspired by models of the rodent hippocampus. The system can produce stable representations of large complex environments during robot experiments in both indoor and outdoor environments. These representations are both topological and metric in nature, and can involve multiple representations of the same place as well as discontinuities. In this paper we describe a new technique known as experience mapping that can be used online with the RatSLAM system to produce world representations known as experience maps. These maps group together multiple place representations and are spatially continuous. A number of experiments have been conducted in simulation and a real world office environment. These experiments demonstrate the high degree to which experience maps are representative of the spatial arrangement of the environment.

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Gabor representations have been widely used in facial analysis (face recognition, face detection and facial expression detection) due to their biological relevance and computational properties. Two popular Gabor representations used in literature are: 1) Log-Gabor and 2) Gabor energy filters. Even though these representations are somewhat similar, they also have distinct differences as the Log-Gabor filters mimic the simple cells in the visual cortex while the Gabor energy filters emulate the complex cells, which causes subtle differences in the responses. In this paper, we analyze the difference between these two Gabor representations and quantify these differences on the task of facial action unit (AU) detection. In our experiments conducted on the Cohn-Kanade dataset, we report an average area underneath the ROC curve (A`) of 92.60% across 17 AUs for the Gabor energy filters, while the Log-Gabor representation achieved an average A` of 96.11%. This result suggests that small spatial differences that the Log-Gabor filters pick up on are more useful for AU detection than the differences in contours and edges that the Gabor energy filters extract.

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This paper introduces three approaches to unlocking the degrees of “truth” within photographs published in newspapers by exploring the genres of Press photography, Photojournalism and Documentary photography. This is brought into context through a study of photographs appearing in The Australian newspaper during 2001 when the Norwegian freighter, the MV Tampa, rescued boat people whose vessel had sunk off the West Australian coast in 2001, and two months later the Children Overboard incident occurred.

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This paper examines Australian media representations of the male managers of two global mining corporations, Rio Tinto and BHP Billiton. These organizations are transnational (or multinational) corporations with assets and/or operations across national boundaries (Dunning and Lundan, 2008), and indeed their respective Chief Executive Officers, Tom Albanese and Marius Kloppers are two of the most economically (and arguably politically) powerful in the world overseeing 37 000 and 39 000 employees internationally. With a 2008 profit of US$15.962 billion and assets of US$ 75.889 Billion BHP Billiton is the world's largest mining company. In terms of its profits and assets Rio Tinto ranks fourth in the world, but with operations in six countries (mainly Canada and Australia) and a 2008 profit of US$10.3 billion it is also emblematic of the transnational in that its ‘budget is larger than that of all but a few nations’ (Giddens, 2003, p. 62).

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Over the last three years, in our Early Algebra Thinking Project, we have been studying Years 3 to 5 students’ ability to generalise in a variety of situations, namely, compensation principles in computation, the balance principle in equivalence and equations, change and inverse change rules with function machines, and pattern rules with growing patterns. In these studies, we have attempted to involve a variety of models and representations and to build students’ abilities to switch between them (in line with the theories of Dreyfus, 1991, and Duval, 1999). The results have shown the negative effect of closure on generalisation in symbolic representations, the predominance of single variance generalisation over covariant generalisation in tabular representations, and the reduced ability to readily identify commonalities and relationships in enactive and iconic representations. This chapter uses the results to explore the interrelation between generalisation and verbal and visual comprehension of context. The studies evidence the importance of understanding and communicating aspects of representational forms which allowed commonalities to be seen across or between representations. Finally the chapter explores the implications of the studies for a theory that describes a growth in integration of models and representations that leads to generalisation.

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Children often have difficulties in learning spatial representations. This study investigated the effect of four different instructional formats on learning outcomes and strategies used when dealing with spatial tasks such as assembly procedures. It was hypothesised that instructional material that imposed least extraneous cognitive load would facilitate enhanced learning. Forty secondary students were presented with four types of instruction; orthographic drawing, isometric drawing, physical model and, isometric and physical model together. The findings provide evidence to suggest that working from physical models caused least extraneous cognitive load compared to the isometric and orthographic groups. The model group took less time, had more correctly completed models, required fewer extra looks, spent less time studying the instruction and made fewer errors. Problem decomposition, forward working and attending to information in the foreground of the graphical representation strategies were analysed.

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This paper is a report of students' responses to instruction which was based on the use of concrete representations to solve linear equations. The sample consisted of 21 Grade 8 students from a middle-class suburban state secondary school with a reputation for high academic standards and innovative mathematics teaching. The students were interviewed before and after instruction. Interviews and classroom interactions were observed and videotaped. A qualitative analysis of the responses revealed that students did not use the materials in solving problems. The increased processing load caused by concrete representations is hypothesised as a reason.

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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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Queer university student print media often represents capitalism in a framework which could be classified as Marxism. However, at the same time, queer student media extensively publishes ideas which could be classified as academic queer theory. This chapter features analysis of these representations from the 2003, 2004 and 2006 editions of national queer student publication, Querelle, and from a sample of queer student media from four Australian universities. The perspectives of Marxism and academic queer theory are often argued to be contradictory (See for example, Hennessy 1994; Morton 1996b; Kirsch 2007), and thus the students’ application of these theories in tandem could be considered problematic. McKee asks ‘Who gets to be an intellectual?’ (2004) and suggests that the intellectualising undertaken by mainstream and alternative cultural creators is just as valid as that undertaken by university academics. He also raises concerns that the concept of theory is seen to be kept separate from everyday culture (McKee 2002). This chapter argues that in the construction and representation of their politics in this manner the queer student activists are creating their own version of queer theory. This analysis of queer student media contributes to research on queer communities and queer theory, demonstrating how one specific cultural subset theorises queerness and queer politics, thereby contributing to the genealogy of queer.

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The business of helping children to grow up as ‘custodians’, or ‘future managers’ of the Murray-Darling Basin is not simple, and that single sources of information and ways of seeing the environment are not enough. Children (and adults) need to be able to relate individually, emotionally and aesthetically to their places if they are to learn to love them. However, they also need access to a variety of ways of thinking and seeing those same places if they are to be able to take action to sustain them – action that inevitably involves forms of communication with their fellow citizens. This chapter documents the writing and art program Special Forever, with its focus on communications, as an important intervention into promoting eco-social sustainability.

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Association rule mining has contributed to 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 first propose a definition for redundancy, then propose a concise representation, called a Reliable basis, for representing non-redundant association rules. The Reliable basis contains a set of non-redundant rules which are derived using frequent closed itemsets and their generators instead of using frequent itemsets that are usually used by traditional association rule mining approaches. An important contribution of this paper is that we propose to use the certainty factor as the criterion to measure the strength of the discovered association rules. Using this criterion, we can ensure the elimination of as many redundant rules as possible without reducing the inference capacity of the remaining extracted non-redundant rules. We prove that the redundancy elimination, based on the proposed Reliable basis, does not reduce the strength of belief in the extracted rules. We also prove that all association rules, their supports and confidences, can be retrieved from the Reliable basis without accessing the dataset. 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. We also conduct experiments on the application of association rules to the area of product recommendation. The experimental results show that the non-redundant association rules extracted using the proposed method retain the same inference capacity as the entire rule set. This result indicates that using non-redundant rules only is sufficient to solve real problems needless using the entire rule set.