899 resultados para DIGITAL ELEVATION MODELS
Resumo:
While over the past decade many Australian schools have come to understand the transformative potential of digitally-rich teaching and learning, traditional models of schooling continue to dominate. Even with significant investment in the area, both in terms of digital resourcing and teacher professional development, innovation has generally only occurred in individual classrooms or ‘pockets’ in schools. This article discusses three interdependent conditions which need to exist as a foundation in order to facilitate the opportunity for transformation from traditional to digitally-rich ways of working in primary, middle and secondary schools or colleges. Distributed and transformational leadership approaches are critiqued with core elements identified which facilitate change. The establishment of a vision is identified and discussed as a fundamental driver and rudder for school transformation. The importance of creating and maintaining urgency to compel a school community to adopt and embed change is unpacked. This report concludes with a synthesis of the three preconditions and recommendations for proponents of digital school transformation.
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The huge amount of CCTV footage available makes it very burdensome to process these videos manually through human operators. This has made automated processing of video footage through computer vision technologies necessary. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned ‘normal’ model. There is no precise and exact definition for an abnormal activity; it is dependent on the context of the scene. Hence there is a requirement for different feature sets to detect different kinds of abnormal activities. In this work we evaluate the performance of different state of the art features to detect the presence of the abnormal objects in the scene. These include optical flow vectors to detect motion related anomalies, textures of optical flow and image textures to detect the presence of abnormal objects. These extracted features in different combinations are modeled using different state of the art models such as Gaussian mixture model(GMM) and Semi- 2D Hidden Markov model(HMM) to analyse the performances. Further we apply perspective normalization to the extracted features to compensate for perspective distortion due to the distance between the camera and objects of consideration. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.
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Many newspapers and magazines have added “social media features” to their web-based information services in order to allow users to participate in the production of content. This study examines the specific impact of the firm’s investment in social media features on their online business models. We make a comparative case study of four Scandinavian print media firms that have added social media features to their online services. We show how social media features lead to online business model innovation, particularly linked to the firms’ value propositions. The paper discusses the repercussions of this transformation on firms’ relationship with consumers and with traditional content contributors. The modified value proposition also requires firms to acquire new competences in order to reap full benefit of their social media investments. We show that the firms have been unable to do so since they have not allowed the social media features to affect their online revenue models.
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A typology of music distribution models is proposed consisting of the ownership model, the access model, and the context model. These models are not substitutes for each other and may co‐exist serving different market niches. The paper argues that increasingly the economic value created from recorded music is based on con‐text rather than on ownership. During this process, access‐based services temporarily generate economic value, but such services are destined to eventually become commoditised.
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1974 was the year when the Swedish pop group ABBA won the Eurovision Song Contest in Brighton and when Blue Swede reached number one on the Billboard Hot 100 in the US. Although Swedish pop music gained some international success even prior to 1974, this year is often considered as the beginning of an era in which Swedish pop music had great success around the world. With brands such as ABBA, Europe, Roxette, The Cardigans, Ace of Base, In Flames, Robyn, Avicii, Swedish House Mafia and music producers Stig Andersson, Ola Håkansson, Dag Volle, Max Martin, Andreas Carlsson, Jorgen Elofsson and several others have the myth of the Swedish music miracle kept alive for nearly more than four decades. Swedish music looks to continue reap success around the world, but since the millennium, Sweden's relationship with music has been more focused on relatively controversial Internet-based services for music distribution developed by Swedish entrepreneurs and engineers rather than on successful musicians and composers. This chapter focusses on the music industry in Sweden. The chapter will discuss the development of the Internet services mentioned above and their impact on the production, distribution and consumption of recorded music. Ample space will be given in particular to Spotify, the music service that quickly has fundamentally changed the music industry in Sweden. The chapter will also present how the music industry's three sectors - recorded music, music licensing and live music - interact and evolve in Sweden.
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The acceptance of broadband ultrasound attenuation for the assessment of osteoporosis suffers from a limited understanding of ultrasound wave propagation through cancellous bone. It has recently been proposed that the ultrasound wave propagation can be described by a concept of parallel sonic rays. This concept approximates the detected transmission signal to be the superposition of all sonic rays that travel directly from transmitting to receiving transducer. The transit time of each ray is defined by the proportion of bone and marrow propagated. An ultrasound transit time spectrum describes the proportion of sonic rays having a particular transit time, effectively describing lateral inhomogeneity of transit times over the surface of the receiving ultrasound transducer. The aim of this study was to provide a proof of concept that a transit time spectrum may be derived from digital deconvolution of input and output ultrasound signals. We have applied the active-set method deconvolution algorithm to determine the ultrasound transit time spectra in the three orthogonal directions of four cancellous bone replica samples and have compared experimental data with the prediction from the computer simulation. The agreement between experimental and predicted ultrasound transit time spectrum analyses derived from Bland–Altman analysis ranged from 92% to 99%, thereby supporting the concept of parallel sonic rays for ultrasound propagation in cancellous bone. In addition to further validation of the parallel sonic ray concept, this technique offers the opportunity to consider quantitative characterisation of the material and structural properties of cancellous bone, not previously available utilising ultrasound.
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In 1999 the global recorded music industry had experienced a period of growth that had lasted for almost a quarter of a century. Approximately one billion records were sold worldwide in 1974, and by the end of the century, the number of records sold was more than three times as high. At the end of the nineties, spirits among record label executives were high and few music industry executives at this time expected that a team of teenage Internet hackers, led by Shawn Fanning (at the time a student at Northeastern University in Boston) would ignite the turbulent process that eventually would undermine the foundations of the industry.
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Dealing with digital medical images is raising many new security problems with legal and ethical complexities for local archiving and distant medical services. These include image retention and fraud, distrust and invasion of privacy. This project was a significant step forward in developing a complete framework for systematically designing, analyzing, and applying digital watermarking, with a particular focus on medical image security. A formal generic watermarking model, three new attack models, and an efficient watermarking technique for medical images were developed. These outcomes contribute to standardizing future research in formal modeling and complete security and computational analysis of watermarking schemes.
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The digital era is proving to be one of disruption, where new technologies matched with innovative business models can be harnessed to attack even the most established of companies. For businesses with the relative certainty of captive customer bases, such as airports, the ability to digitally diversify offers the opportunity to venture into new modes of operation. For an airport, this opportunity can also be leveraged to sustain superior customer support regardless of a customer’s location in the world. This research paper presents a case study of the development of an Australian Airport Corporation’s mobile application as part of a greater digital strategy initiative using a design-led approach to innovate. An action research method provides the platform for an intensive embedded practice and study of design-led innovation within the major Australian Airport Corporation. The findings reveal design-led innovation to be a crucial in-house idea generation and concept development capability enabling the bridging of distinct corporate domains associated with commercialisation, operations and customer experience. A Digital Innovation Checklist is presented as an output of this research which structures an organizational approach toward digital channel innovation. The practitioner’s checklist is designed to aid in the future development of digital channels within the broader spectrum of strategy by addressing business assumptions.
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It is often said that Australia is a world leader in rates of copyright infringement for entertainment goods. In 2012, the hit television show, Game of Thrones, was the most downloaded television show over bitorrent, and estimates suggest that Australians accounted for a plurality of nearly 10% of the 3-4 million downloads each week. The season finale of 2013 was downloaded over a million times within 24 hours of its release, and again Australians were the largest block of illicit downloaders over BitTorrent, despite our relatively small population. This trend has led the former US Ambassador to Australia to implore Australians to stop 'stealing' digital content, and rightsholders to push for increasing sanctions on copyright infringers. The Australian Government is looking to respond by requiring Internet Service Providers to issue warnings and potentially punish consumers who are alleged by industry groups to have infringed copyright. This is the logical next step in deterring infringement, given that the operators of infringing networks (like The Pirate Bay, for example) are out of regulatory reach. This steady ratcheting up of the strength of copyright, however, comes at a significant cost to user privacy and autonomy, and while the decentralisation of enforcement reduces costs, it also reduces the due process safeguards provided by the judicial process. This article presents qualitative evidence that substantiates a common intuition: one of the major reasons that Australians seek out illicit downloads of content like Game of Thrones in such numbers is that it is more difficult to access legitimately in Australia. The geographically segmented way in which copyright is exploited at an international level has given rise to a ‘tyranny of digital distance’, where Australians have less access to copyright goods than consumers in other countries. Compared to consumers in the US and the EU, Australians pay more for digital goods, have less choice in distribution channels, are exposed to substantial delays in access, and are sometimes denied access completely. In this article we focus our analysis on premium film and television offerings, like Game of Thrones, and through semi-structured interviews, explore how choices in distribution impact on the willingness of Australian consumers to seek out infringing copies of copyright material. Game of Thrones provides an excellent case study through which to frame this analysis: it is both one of the least legally accessible television offerings and one of the most downloaded through filesharing networks of recent times. Our analysis shows that at the same time as rightsholder groups, particularly in the film and television industries, are lobbying for stronger laws to counter illicit distribution, the business practices of their member organisations are counter-productively increasing incentives for consumers to infringe. The lack of accessibility and high prices of copyright goods in Australia leads to substantial economic waste. The unmet consumer demand means that Australian consumers are harmed by lower access to information and entertainment goods than consumers in other jurisdictions. The higher rates of infringement that fulfils some of this unmet demand increases enforcement costs for copyright owners and imposes burdens either on our judicial system or on private entities – like ISPs – who may be tasked with enforcing the rights of third parties. Most worryingly, the lack of convenient and cheap legitimate digital distribution channels risks undermining public support for copyright law. Our research shows that consumers blame rightsholders for failing to meet market demand, and this encourages a social norm that infringing copyright, while illegal, is not morally wrongful. The implications are as simple as they are profound: Australia should not take steps to increase the strength of copyright law at this time. The interests of the public and those of rightsholders align better when there is effective competition in distribution channels and consumers can legitimately get access to content. While foreign rightsholders are seeking enhanced protection for their interests, increasing enforcement is likely to increase their ability to engage in lucrative geographical price-discrimination, particularly for premium content. This is only likely to increase the degree to which Australian consumers feel that their interests are not being met and, consequently, to further undermine the legitimacy of copyright law. If consumers are to respect copyright law, increasing sanctions for infringement without enhancing access and competition in legitimate distribution channels could be dangerously counter-productive. We suggest that rightsholders’ best strategy for addressing infringement in Australia at this time is to ensure that Australians can access copyright goods in a timely, affordable, convenient, and fair lawful manner.
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This digital poster (which was on display at "The Cube", Queensland University of Technology) demonstrates how specification parameters can be extracted from a product library repository for use in augmenting the information contents of the objects in a local BIM tool (Revit in this instance).
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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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Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity - past, present and future. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3 mm to 30 mm in length. ("Natural-colour" is used to contrast with "false-colour", i.e., colour generated from, or applied to, gray-scale data post-acquisition.) Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR) camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes), afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect data for research, education, art, entertainment, biodiversity assessment and biosecurity control. © 2014 Nguyen et al.
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Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.