938 resultados para Digital Mathematical Library


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Young children shift meanings across multiple modes long before they have mastered formal writing skills. In a digital age, children are socialised into a wide range of new digital media conventions in the home, at school, and in community-based settings. This article draws on longitudinal classroom research with a culturally diverse cohort of eight-year old children, to advance new understandings about children’s engagement in transmediation in the context of digital media creation. The author illuminates three key principles of transmediation using multimodal snapshots of storyboard images, digital movie frames, and online comics. Insights about transmediation are developed through dialogue with the children about their thought processes and intentions for their multimedia creations.

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Signal Processing (SP) is a subject of central importance in engineering and the applied sciences. Signals are information-bearing functions, and SP deals with the analysis and processing of signals (by dedicated systems) to extract or modify information. Signal processing is necessary because signals normally contain information that is not readily usable or understandable, or which might be disturbed by unwanted sources such as noise. Although many signals are non-electrical, it is common to convert them into electrical signals for processing. Most natural signals (such as acoustic and biomedical signals) are continuous functions of time, with these signals being referred to as analog signals. Prior to the onset of digital computers, Analog Signal Processing (ASP) and analog systems were the only tool to deal with analog signals. Although ASP and analog systems are still widely used, Digital Signal Processing (DSP) and digital systems are attracting more attention, due in large part to the significant advantages of digital systems over the analog counterparts. These advantages include superiority in performance,s peed, reliability, efficiency of storage, size and cost. In addition, DSP can solve problems that cannot be solved using ASP, like the spectral analysis of multicomonent signals, adaptive filtering, and operations at very low frequencies. Following the recent developments in engineering which occurred in the 1980's and 1990's, DSP became one of the world's fastest growing industries. Since that time DSP has not only impacted on traditional areas of electrical engineering, but has had far reaching effects on other domains that deal with information such as economics, meteorology, seismology, bioengineering, oceanology, communications, astronomy, radar engineering, control engineering and various other applications. This book is based on the Lecture Notes of Associate Professor Zahir M. Hussain at RMIT University (Melbourne, 2001-2009), the research of Dr. Amin Z. Sadik (at QUT & RMIT, 2005-2008), and the Note of Professor Peter O'Shea at Queensland University of Technology. Part I of the book addresses the representation of analog and digital signals and systems in the time domain and in the frequency domain. The core topics covered are convolution, transforms (Fourier, Laplace, Z. Discrete-time Fourier, and Discrete Fourier), filters, and random signal analysis. There is also a treatment of some important applications of DSP, including signal detection in noise, radar range estimation, banking and financial applications, and audio effects production. Design and implementation of digital systems (such as integrators, differentiators, resonators and oscillators are also considered, along with the design of conventional digital filters. Part I is suitable for an elementary course in DSP. Part II (which is suitable for an advanced signal processing course), considers selected signal processing systems and techniques. Core topics covered are the Hilbert transformer, binary signal transmission, phase-locked loops, sigma-delta modulation, noise shaping, quantization, adaptive filters, and non-stationary signal analysis. Part III presents some selected advanced DSP topics. We hope that this book will contribute to the advancement of engineering education and that it will serve as a general reference book on digital signal processing.

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The emergence of mobile and ubiquitous computing has created what is referred to as a hybrid space – a virtual layer of digital information and interaction opportunities that sits on top and augments the physical environment. The increasing connectedness through such media, from anywhere to anybody at anytime, makes us less dependent on being physically present somewhere in particular. But, what is the role of ubiquitous computing in making physical presence at a particular place more attractive? Acknowledging historic context and identity as important attributes of place, this work embarks on a ‘global sense of place’ in which the cultural diversity, multiple identities, backgrounds, skills and experiences of people traversing a place are regarded as social assets of that place. The aim is to explore ways how physical architecture and infrastructure of a place can be mediated towards making invisible social assets visible, thus augmenting people’s situated social experience. Thereby, the focus is on embodied media, i.e. media that materialise digital information as observable and sometimes interactive parts of the physical environment hence amplify people’s real world experience, rather than substituting or moving it to virtual spaces.

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The Dark Ages are generally held to be a time of technological and intellectual stagnation in western development. But that is not necessarily the case. Indeed, from a certain perspective, nothing could be further from the truth. In this paper we draw historical comparisons, focusing especially on the thirteenth and fourteenth centuries, between the technological and intellectual ruptures in Europe during the Dark Ages, and those of our current period. Our analysis is framed in part by Harold Innis’s2 notion of "knowledge monopolies". We give an overview of how these were affected by new media, new power struggles, and new intellectual debates that emerged in thirteenth and fourteenth century Europe. The historical salience of our focus may seem elusive. Our world has changed so much, and history seems to be an increasingly far-from-favoured method for understanding our own period and its future potentials. Yet our seemingly distant historical focus provides some surprising insights into the social dynamics that are at work today: the fracturing of established knowledge and power bases; the democratisation of certain "sacred" forms of communication and knowledge, and, conversely, the "sacrosanct" appropriation of certain vernacular forms; challenges and innovations in social and scientific method and thought; the emergence of social world-shattering media practices; struggles over control of vast networks of media and knowledge monopolies; and the enclosure of public discursive and social spaces for singular, manipulative purposes. The period between the eleventh and fourteenth centuries in Europe prefigured what we now call the Enlightenment, perhaps moreso than any other period before or after; it shaped what the Enlightenment was to become. We claim no knowledge of the future here. But in the "post-everything" society, where history is as much up for sale as it is for argument, we argue that our historical perspective provides a useful analogy for grasping the wider trends in the political economy of media, and for recognising clear and actual threats to the future of the public sphere in supposedly democratic societies.

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The Dark Ages are generally held to be a time of technological and intellectual stagnation in western development. But that is not necessarily the case. Indeed, from a certain perspective, nothing could be further from the truth. In this paper we draw historical comparisons, focusing especially on the thirteenth and fourteenth centuries, between the technological and intellectual ruptures in Europe during the Dark Ages, and those of our current period. Our analysis is framed in part by Harold Innis’s2 notion of "knowledge monopolies". We give an overview of how these were affected by new media, new power struggles, and new intellectual debates that emerged in thirteenth and fourteenth century Europe. The historical salience of our focus may seem elusive. Our world has changed so much, and history seems to be an increasingly far-from-favoured method for understanding our own period and its future potentials. Yet our seemingly distant historical focus provides some surprising insights into the social dynamics that are at work today: the fracturing of established knowledge and power bases; the democratisation of certain "sacred" forms of communication and knowledge, and, conversely, the "sacrosanct" appropriation of certain vernacular forms; challenges and innovations in social and scientific method and thought; the emergence of social world-shattering media practices; struggles over control of vast networks of media and knowledge monopolies; and the enclosure of public discursive and social spaces for singular, manipulative purposes. The period between the eleventh and fourteenth centuries in Europe prefigured what we now call the Enlightenment, perhaps moreso than any other period before or after; it shaped what the Enlightenment was to become. We claim no knowledge of the future here. But in the "post-everything" society, where history is as much up for sale as it is for argument, we argue that our historical perspective provides a useful analogy for grasping the wider trends in the political economy of media, and for recognising clear and actual threats to the future of the public sphere in supposedly democratic societies.

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Language is a unique aspect of human communication because it can be used to discuss itself in its own terms. For this reason, human societies potentially have superior capacities of co-ordination, reflexive self-correction, and innovation than other animal, physical or cybernetic systems. However, this analysis also reveals that language is interconnected with the economically and technologically mediated social sphere and hence is vulnerable to abstraction, objectification, reification, and therefore ideology – all of which are antithetical to its reflexive function, whilst paradoxically being a fundamental part of it. In particular, in capitalism, language is increasingly commodified within the social domains created and affected by ubiquitous communication technologies. The advent of the so-called ‘knowledge economy’ implicates exchangeable forms of thought (language) as the fundamental commodities of this emerging system. The historical point at which a ‘knowledge economy’ emerges, then, is the critical point at which thought itself becomes a commodified ‘thing’, and language becomes its “objective” means of exchange. However, the processes by which such commodification and objectification occurs obscures the unique social relations within which these language commodities are produced. The latest economic phase of capitalism – the knowledge economy – and the obfuscating trajectory which accompanies it, we argue, is destroying the reflexive capacity of language particularly through the process of commodification. This can be seen in that the language practices that have emerged in conjunction with digital technologies are increasingly non-reflexive and therefore less capable of self-critical, conscious change.

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Robust, affine covariant, feature extractors provide a means to extract correspondences between images captured by widely separated cameras. Advances in wide baseline correspondence extraction require looking beyond the robust feature extraction and matching approach. This study examines new techniques of extracting correspondences that take advantage of information contained in affine feature matches. Methods of improving the accuracy of a set of putative matches, eliminating incorrect matches and extracting large numbers of additional correspondences are explored. It is assumed that knowledge of the camera geometry is not available and not immediately recoverable. The new techniques are evaluated by means of an epipolar geometry estimation task. It is shown that these methods enable the computation of camera geometry in many cases where existing feature extractors cannot produce sufficient numbers of accurate correspondences.

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This chapter examines how a change in school leadership can successfully address competencies in complex situations and thus create a positive learning environment in which Indigenous students can excel in their learning rather than accept a culture that inhibits school improvement. Mathematics has long been an area that has failed to assist Indigenous students in improving their learning outcomes, as it is a Eurocentric subject (Rothbaum, Weisz, Pott, Miyake & Morelli, 2000, De Plevitz, 2007) and does not contextualize pedagogy with Indigenous culture and perspectives (Matthews, Cooper & Baturo, 2007). The chapter explores the work of a team of Indigenous and non-Indigenous academics from the YuMi Deadly Centre who are turning the tide on improving Indigenous mathematical outcomes in schools and in communities with high numbers of Aboriginal and Torres Strait Islander students.

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‘Everybody is science conscious these days’ – so started the inaugural week of Frontiers of Science, a self described ‘intelligently presented and attractively drawn’ science-based comic strip published in the Sydney Morning Herald from 1961 to 1982 and ultimately syndicated to daily newspapers around the world. An archive of the first 200 Frontiers of Science comic strips (1961−65) has been made freely available online through an initiative of the University of Sydney Library. While the 1960s public interest in evolution, space exploration, and the Cold War have given way to the twenty-first century concerns about global warming, genetic engineering, and alternative energy sources, it is fair to say that everybody is still science conscious. Frontiers of Science provides an interesting and nostalgic insight into 1960s popular science through an unusual mode of dissemination.

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One of the surprising recurring phenomena observed in experiments with boosting is that the test error of the generated classifier usually does not increase as its size becomes very large, and often is observed to decrease even after the training error reaches zero. In this paper, we show that this phenomenon is related to the distribution of margins of the training examples with respect to the generated voting classification rule, where the margin of an example is simply the difference between the number of correct votes and the maximum number of votes received by any incorrect label. We show that techniques used in the analysis of Vapnik's support vector classifiers and of neural networks with small weights can be applied to voting methods to relate the margin distribution to the test error. We also show theoretically and experimentally that boosting is especially effective at increasing the margins of the training examples. Finally, we compare our explanation to those based on the bias-variance decomposition.

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This chapter explores some of the practical and theoretical obstacles and opportunities for self-expression experienced by a group of Queer Dig- ital Storytellers who primarily make and distribute their stories online. “Queer” in this chapter encompasses a diverse range of gender and sexual identities and perspectives on same, including the heterosexual children of queer parents and heterosexual parents of queer children. As such it is also used as a unifying moniker by participants in the Rainbow Family Tree case study that is examined in this chapter. The Digital Storytellers in this case study are largely motivated by a desire to have an impact on social attitudes towards gender and sexuality, both in their personal province of friends and family, and in public domains constituted of unknown or invisible audiences. The privacy and publicity dilemmas that will be considered arise out of positioning personal stories in the public domain and the quandaries that emerge from an activist desire to speak truth to power that is located across a wide cross section of audiences.

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A number of learning problems can be cast as an Online Convex Game: on each round, a learner makes a prediction x from a convex set, the environment plays a loss function f, and the learner’s long-term goal is to minimize regret. Algorithms have been proposed by Zinkevich, when f is assumed to be convex, and Hazan et al., when f is assumed to be strongly convex, that have provably low regret. We consider these two settings and analyze such games from a minimax perspective, proving minimax strategies and lower bounds in each case. These results prove that the existing algorithms are essentially optimal.

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We present new expected risk bounds for binary and multiclass prediction, and resolve several recent conjectures on sample compressibility due to Kuzmin and Warmuth. By exploiting the combinatorial structure of concept class F, Haussler et al. achieved a VC(F)/n bound for the natural one-inclusion prediction strategy. The key step in their proof is a d=VC(F) bound on the graph density of a subgraph of the hypercube—one-inclusion graph. The first main result of this report is a density bound of n∙choose(n-1,≤d-1)/choose(n,≤d) < d, which positively resolves a conjecture of Kuzmin and Warmuth relating to their unlabeled Peeling compression scheme and also leads to an improved one-inclusion mistake bound. The proof uses a new form of VC-invariant shifting and a group-theoretic symmetrization. Our second main result is an algebraic topological property of maximum classes of VC-dimension d as being d-contractible simplicial complexes, extending the well-known characterization that d=1 maximum classes are trees. We negatively resolve a minimum degree conjecture of Kuzmin and Warmuth—the second part to a conjectured proof of correctness for Peeling—that every class has one-inclusion minimum degree at most its VC-dimension. Our final main result is a k-class analogue of the d/n mistake bound, replacing the VC-dimension by the Pollard pseudo-dimension and the one-inclusion strategy by its natural hypergraph generalization. This result improves on known PAC-based expected risk bounds by a factor of O(log n) and is shown to be optimal up to a O(log k) factor. The combinatorial technique of shifting takes a central role in understanding the one-inclusion (hyper)graph and is a running theme throughout