983 resultados para Online handwriting recognition


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In this article, we investigate eight and nine year old girls’ school and home use of the popular game Minecraft and the ways in which the girls ‘bring themselves into being’ through talk and digital production in the social spaces of the classroom and within the game’s multiplayer online world. This work was conducted as part of a broader digital games in education project involving primary and secondary school-aged students in Australia and focuses specifically on data collected from an all-girls primary school in Brisbane. We investigate the processes of identity construction that occur as the girls undertake practices of curatorship (Potter, 2012) to display their knowledge of Minecraft through discussion of the game, both ‘in world’ and in face-to-face interactions, and as they assemble resources within and around the game to design, build and display their creations and share stories about their game play. The article begins with a consideration of recent scholarship focussing on children, learning and digital culture and literacy practices before explaining how Minecraft is, in many ways, an exemplary instance of a digital game that promotes and enables complex practices of digital participation. We then introduce the concepts of performativity and recognition (Butler 1990, 2004, 2005) which, we argue, provide productive ways to theorise identity work within affinity groups. The article then outlines some background to the research project and our methodology before providing analysis of the data in the second half of the article. We conclude by outlining the implications of our investigation for the conceptualisation of learning spaces as affinity groups and for considering digital participation as curatorship.

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There is a growing recognition of the interests and rights of individuals conceived using donated gametes in assisted reproductive technology to information about their biological parentage. In Australia these rights vary between jurisdictions according to differing statutory provisions. In February 2011 the Senate's Legal and Constitutional Affairs References Committee published its report on Donor Conception Practices in Australia. The report recommended the development of a nationally consistent approach to donor conception and recommended the enactment of legislation in those Australian jurisdictions without legislation regulating donor conception. This editorial reviews the Senate Committee report and its recommendations and supports calls for a nationally harmonised approach to donor conception in Australia.

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Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of local texture information and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. The results on the parameter sensitivity demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusions ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.

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Searching for relevant peer-reviewed material is an integral part of corporate and academic researchers. Researchers collect huge amount of information over the years and sometimes struggle organizing it. Based on a study with 30 academic researchers, we explore, in combination, different searching and archiving activities of document-based information. Based on our results we provide several implications for design.

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Faunal vocalisations are vital indicators for environmental change and faunal vocalisation analysis can provide information for answering ecological questions. Therefore, automated species recognition in environmental recordings has become a critical research area. This thesis presents an automated species recognition approach named Timed and Probabilistic Automata. A small lexicon for describing animal calls is defined, six algorithms for acoustic component detection are developed, and a series of species recognisers are built and evaluated.The presented automated species recognition approach yields significant improvement on the analysis performance over a real world dataset, and may be transferred to commercial software in the future.

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Purpose This paper aims to identify, through a literature review, key issues regarding how online role plays can be designed and to apply them when designing a role play on conflict management. Design/methodology/approach By drawing on the key issues identified in the literature review, a role play on conflict management was designed and evaluated. Data were collected by developing a survey that focused on perceived learning, participation and satisfaction. Findings Overall, a majority of the students felt that they learned and participated in the role play. The most positive finding was that the students were satisfied with their role play experience. Research limitations/implications Researchers are urged to further develop the dimensions and measures of online role play success. The measures that were developed for evaluating perceived learning, participation and satisfaction with role plays can be further developed and tested. It is suggested that the effects on learning need to be further explored. Practical implications It is suggested that teachers take the identified key issues of online role play design into account. An important challenge seems to be to encourage students to reflect and do additional reading and research in relation with online role plays. Originality/value Online collaboration is commonly argued as beneficial from an e-learning perspective. However, a challenge for research and practice is to learn how collaborative e-learning activities may be developed. This paper contributes by focusing on how online role plays can be designed and evaluated.

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All the signs are there that Australian retailers are not investing enough in their online operations.

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Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.

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The ability to identify and assess user engagement with transmedia productions is vital to the success of individual projects and the sustainability of this mode of media production as a whole. It is essential that industry players have access to tools and methodologies that offer the most complete and accurate picture of how audiences/users engage with their productions and which assets generate the most valuable returns of investment. Drawing upon research conducted with Hoodlum Entertainment, a Brisbane-based transmedia producer, this chapter outlines an initial assessment of the way engagement tends to be understood, why standard web analytics tools are ill-suited to measuring it, how a customised tool could offer solutions, and why this question of measuring engagement is so vital to the future of transmedia as a sustainable industry.

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This paper examines the use of Twitter for long-term discussions around Australian politics, at national and state levels, tracking two hashtags during 2012: #auspol, denoting national political topics, and #wapol, which provides a case study of state politics (representing Western Australia). The long-term data collection provides the opportunity to analyse how the Twitter audience responds to Australian politics: which themes attract the most attention and which accounts act as focal points for these discussions. The paper highlights differences in the coverage of state and national politics. For #auspol, a small number of accounts are responsible for the majority of tweets, with politicians invoked but not directly contributing to the discussion. In contrast, #wapol stimulates a much lower level of tweeting. This example also demonstrates that, in addition to citizen accounts, traditional participants within political debate, such as politicians and journalists, are among the active contributors to state-oriented discussions on Twitter.

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Facial expression recognition (FER) has been dramatically developed in recent years, thanks to the advancements in related fields, especially machine learning, image processing and human recognition. Accordingly, the impact and potential usage of automatic FER have been growing in a wide range of applications, including human-computer interaction, robot control and driver state surveillance. However, to date, robust recognition of facial expressions from images and videos is still a challenging task due to the difficulty in accurately extracting the useful emotional features. These features are often represented in different forms, such as static, dynamic, point-based geometric or region-based appearance. Facial movement features, which include feature position and shape changes, are generally caused by the movements of facial elements and muscles during the course of emotional expression. The facial elements, especially key elements, will constantly change their positions when subjects are expressing emotions. As a consequence, the same feature in different images usually has different positions. In some cases, the shape of the feature may also be distorted due to the subtle facial muscle movements. Therefore, for any feature representing a certain emotion, the geometric-based position and appearance-based shape normally changes from one image to another image in image databases, as well as in videos. This kind of movement features represents a rich pool of both static and dynamic characteristics of expressions, which playa critical role for FER. The vast majority of the past work on FER does not take the dynamics of facial expressions into account. Some efforts have been made on capturing and utilizing facial movement features, and almost all of them are static based. These efforts try to adopt either geometric features of the tracked facial points, or appearance difference between holistic facial regions in consequent frames or texture and motion changes in loca- facial regions. Although achieved promising results, these approaches often require accurate location and tracking of facial points, which remains problematic.

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Online fraud occurs when an individual or a business responds in some manner to an unsolicited invitation received via the internet and suffers financial or other detrimental effects as a result. In 2010–11, the Australian Bureau of Statistics (2012) found that over 1.2 million Australians (6.7% of the population aged 15 years and over) had been a victim of personal fraud, losing approximately $1.4b in the preceding 12 months. More than half of these victims (55.7%) were contacted via the internet or email (online victimisation). In addition to monetary losses, victims of online fraud suffer serious psychological, emotional, social and even physical problems as a consequence of their victimisation. This paper explores the challenges of responding to online fraud victimisation in Australia and describes some of the specific support services that have recently emerged to support victims of this crime.

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This paper presents Sequence Matching Across Route Traversals (SMART); a generally applicable sequence-based place recognition algorithm. SMART provides invariance to changes in illumination and vehicle speed while also providing moderate pose invariance and robustness to environmental aliasing. We evaluate SMART on vehicles travelling at highly variable speeds in two challenging environments; firstly, on an all-terrain vehicle in an off-road, forest track and secondly, using a passenger car traversing an urban environment across day and night. We provide comparative results to the current state-of-the-art SeqSLAM algorithm and investigate the effects of altering SMART’s image matching parameters. Additionally, we conduct an extensive study of the relationship between image sequence length and SMART’s matching performance. Our results show viable place recognition performance in both environments with short 10-metre sequences, and up to 96% recall at 100% precision across extreme day-night cycles when longer image sequences are used.

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Researchers are increasingly grappling with ways of theorizing social media and its use. This review essay proposes that the theory of Information Grounds (IG) may provide a valuable lens for understanding how social media fosters collaboration and social engagement among information professionals. The paper presents literature that helps us understand how social media can be seen as IG, and maps the characteristics of social media to the seven propositions of IG theory. This work is part of a wider study investigating the ways in which Information Technology (IT) professionals experience social media.