908 resultados para Digital signal processor


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Our understanding of the mechanisms of action of GH and its receptor, the GHR, has advanced significantly in the last decade and has provided some important surprises. It is now clear that the GH-GHR axis activates a number of inter-related signalling pathways, not all of which are dependent on the intracellular tyrosine kinase, JAK2 as originally postulated. JAK2-independent pathways, mediated via the Src family kinases, together with a number of negative regulators of GH signalling and emerging cross-talk mechanisms with other growth factor receptors, provide a complex array of mechanisms that are capable of fine-tuning responses to GH in a cell context dependent manner. Additionally, it is also now clear that GH and the GHR can translocate to the nucleus of target cells and initiate, as yet not well defined, nuclear responses. Continued emphasis on elucidation of these complex mechanisms is critical to provide further insights into the diverse physiological and pathophysiological effects of GH.

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In this paper, we propose a novel direction for gait recognition research by proposing a new capture-modality independent, appearance-based feature which we call the Back-filled Gait Energy Image (BGEI). It can can be constructed from both frontal depth images, as well as the more commonly used side-view silhouettes, allowing the feature to be applied across these two differing capturing systems using the same enrolled database. To evaluate this new feature, a frontally captured depth-based gait dataset was created containing 37 unique subjects, a subset of which also contained sequences captured from the side. The results demonstrate that the BGEI can effectively be used to identify subjects through their gait across these two differing input devices, achieving rank-1 match rate of 100%, in our experiments. We also compare the BGEI against the GEI and GEV in their respective domains, using the CASIA dataset and our depth dataset, showing that it compares favourably against them. The experiments conducted were performed using a sparse representation based classifier with a locally discriminating input feature space, which show significant improvement in performance over other classifiers used in gait recognition literature, achieving state of the art results with the GEI on the CASIA dataset.

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A recent Australian literature digitisation project uncovered some surprising discoveries in the children’s books that it digitised. The Children’s Literature Digital Resources (CLDR) Project digitised children’s books that were first published between 1851 to 1945 and made them available online through AustLit: The Australian Literature Resource. The digitisation process also preserved, within the pages of those books, a range of bookplates, book labels, inscriptions, and loose ephemera. This material allows us to trace the provenance of some of the digitised works, some of which came from the personal libraries of now-famous authors, and others from less celebrated sources. These extra-textual traces can contribute to cultural memory of the past by providing evidence of how books were collected and exchanged, and what kinds of books were presented as prizes in schools and Sunday schools. They also provide insight into Australian literary and artistic networks, particularly of the first few decades of the 20th century. This article describes the kinds of material uncovered in the digitisation process and suggests that the material provides insights into literary and cultural histories that might otherwise be forgotten. It also argues that the indexing of this material is vital if it is not to be lost to future researchers.

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The process of researching children’s literature from the past is a growing challenge as resources age and are increasingly treated as rare items, stored away within libraries and other research centres. In Australia, researchers and librarians have collaborated with the bibliographic database AustLit: The Australian Literature Resource to produce the Australian Children’s Literature Digital Resources Project (CLDR). This Project aims to address the growing demand for online access to rare children’s literature resources, and demonstrates the research potential of early Australian children’s literature by supplementing the collection with relevant critical articles. The CLDR project is designed with a specific focus and provides access to full text Australian children’s literature from European settlement to 1945. The collection demonstrates a need and desire to preserve literature treasures to prevent losing such collections in a digital age. The collection covers many themes relevant to the conference including, trauma, survival, memory, survival, hauntings, and histories. The resource provides new and exciting ways with which to research children’s literature from the past and offers a fascinating repository to scholars and professionals of ranging disciplines who are in interested in Australian children’s literature.

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Recently claims have been made that all universities will in coming decades merge to become just a few mega-institutions offering online degrees to the world. This assumes a degree of literacy with ICT (information and communication technology) amongst potential students, who are often regarded as 'digital natives'. Far from being digital natives, many students have considerable trouble using ICT beyond the ubiquitous Facebook. While some students are computer literate, a substantial proportion lack the skills to prosper under their own devices in an online tertiary education environment. For these students a blended learning experience is needed to develop skills to effectively interact in the virtual environment. This paper presents a case study that specifically examined the ICT capabilities of first-year university students enrolled in the School of Civil Engineering and the Built Environment at Queensland University of Technology (QUT). Empirical data are presented and curriculum strategies articulated to develop ICT skills in university undergraduates.

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Flood related scientific and community-based data are rarely systematically collected and analysed in the Philippines. Over the last decades the Pagsangaan River Basin, Leyte, has experienced several flood events. However, documentation describing flood characteristics such as extent, duration or height of these floods are close to non-existing. To address this issue, computerized flood modelling was used to reproduce past events where there was data available for at least partial calibration and validation. The model was also used to provide scenario-based predictions based on A1B climate change assumptions for the area. The most important input for flood modelling is a Digital Elevation Model (DEM) of the river basin. No accurate topographic maps or Light Detection And Ranging (LIDAR)-generated data are available for the Pagsangaan River. Therefore, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM), Version 1, was chosen as the DEM. Although the horizontal spatial resolution of 30 m is rather desirable, it contains substantial vertical errors. These were identified, different correction methods were tested and the resulting DEM was used for flood modelling. The above mentioned data were combined with cross-sections at various strategic locations of the river network, meteorological records, river water level, and current velocity to develop the 1D-2D flood model. SOBEK was used as modelling software to create different rainfall scenarios, including historic flooding events. Due to the lack of scientific data for the verification of the model quality, interviews with local stakeholders served as the gauge to judge the quality of the generated flood maps. According to interviewees, the model reflects reality more accurately than previously available flood maps. The resulting flood maps are now used by the operations centre of a local flood early warning system for warnings and evacuation alerts. Furthermore these maps can serve as a basis to identify flood hazard areas for spatial land use planning purposes.

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‘Positive Stories’ is a digital storytelling initiative that took place in Adelaide in 2010–2011.1 This article describes participants’ experiences of creative self-representation and the thorny complications of mediating voice, particularly in situations where privacy and publicity are significant issues.

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Digital Stories are short autobiographical documentaries, often illustrated with personal photographs and narrated in the first person, and typically produced in group workshops. As a media form they offer ‘ordinary people’ the opportunity to represent themselves to audiences of their choosing; and this amplification of hitherto unheard voices has significant repercussions for their social participation. Many of the storytellers involved in the ‘Rainbow Family Tree’ case study that is the subject of this paper can be characterised as ‘everyday’ activists for their common desire to use their personal stories to increase social acceptance of marginalised identity categories. However, in conflict with their willingness to share their personal stories, many fear the risks and ramifications of distributing them in public spaces (especially online) to audiences both intimate and unknown. Additionally, while technologies for production and distribution of rich media products have become more accessible and user-friendly, many obstacles remain. For many people there are difficulties with technological access and aptitude, personal agency, cultural capital, and social isolation, not to mention availability of the time and energy requisite to Digital Storytelling. Additionally, workshop context, facilitation and distribution processes all influence the content of stories. This paper explores the many factors that make ‘authentic’ self-representation far from straight forward. I use qualitative data drawn from interviews, Digital Story texts and ethnographic observation of GLBTQIS participants in a Digital Storytelling initiative that combined face-to-face and online modes of participation. I consider mediating influences in practice and theory and draw on strategies put forth in cultural anthropology and narrative therapy to propose some practical tools for nuanced and sensitive facilitation of Digital Storytelling workshops and webspaces. Finally, I consider the implications of these facilitation strategies for voice, identity and social participation.

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Our contemporary public sphere has seen the 'emergence of new political rituals, which are concerned with the stains of the past, with self disclosure, and with ways of remembering once taboo and traumatic events' (Misztal, 2005). A recent case of this phenomenon occurred in Australia in 2009 with the apology to the 'Forgotten Australians': a group who suffered abuse and neglect after being removed from their parents – either in Australia or in the UK - and placed in Church and State run institutions in Australia between 1930 and 1970. This campaign for recognition by a profoundly marginalized group coincides with the decade in which the opportunities of Web 2.0 were seen to be diffusing throughout different social groups, and were considered a tool for social inclusion. This paper examines the case of the Forgotten Australians as an opportunity to investigate the role of the internet in cultural trauma and public apology. As such, it adds to recent scholarship on the role of digital web based technologies in commemoration and memorials (Arthur, 2009; Haskins, 2007; Cohen and Willis, 2004), and on digital storytelling in the context of trauma (Klaebe, 2011) by locating their role in a broader and emerging domain of social responsibility and political action (Alexander, 2004).

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An advanced rule-based Transit Signal Priority (TSP) control method is presented in this paper. An on-line transit travel time prediction model is the key component of the proposed method, which enables the selection of the most appropriate TSP plans for the prevailing traffic and transit condition. The new method also adopts a priority plan re-development feature that enables modifying or even switching the already implemented priority plan to accommodate changes in the traffic conditions. The proposed method utilizes conventional green extension and red truncation strategies and also two new strategies including green truncation and queue clearance. The new method is evaluated against a typical active TSP strategy and also the base case scenario assuming no TSP control in microsimulation. The evaluation results indicate that the proposed method can produce significant benefits in reducing the bus delay time and improving the service regularity with negligible adverse impacts on the non-transit street traffic.

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This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

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Flexible information exchange is critical to successful design-analysis integration, but current top-down, standards-based and model-oriented strategies impose restrictions that contradicts this flexibility. In this article we present a bottom-up, user-controlled and process-oriented approach to linking design and analysis applications that is more responsive to the varied needs of designers and design teams. Drawing on research into scientific workflows, we present a framework for integration that capitalises on advances in cloud computing to connect discrete tools via flexible and distributed process networks. We then discuss how a shared mapping process that is flexible and user friendly supports non-programmers in creating these custom connections. Adopting a services-oriented system architecture, we propose a web-based platform that enables data, semantics and models to be shared on the fly. We then discuss potential challenges and opportunities for its development as a flexible, visual, collaborative, scalable and open system.

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Flexible information exchange is critical to successful design integration, but current top-down, standards-based and model-oriented strategies impose restrictions that are contradictory to this flexibility. In this paper we present a bottom-up, user-controlled and process-oriented approach to linking design and analysis applications that is more responsive to the varied needs of designers and design teams. Drawing on research into scientific workflows, we present a framework for integration that capitalises on advances in cloud computing to connect discrete tools via flexible and distributed process networks. Adopting a services-oriented system architecture, we propose a web-based platform that enables data, semantics and models to be shared on the fly. We discuss potential challenges and opportunities for the development thereof as a flexible, visual, collaborative, scalable and open system.

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This paper describes the use of property graphs for mapping data between AEC software tools, which are not linked by common data formats and/or other interoperability measures. The intention of introducing this in practice, education and research is to facilitate the use of diverse, non-integrated design and analysis applications by a variety of users who need to create customised digital workflows, including those who are not expert programmers. Data model types are examined by way of supporting the choice of directed, attributed, multi-relational graphs for such data transformation tasks. A brief exemplar design scenario is also presented to illustrate the concepts and methods proposed, and conclusions are drawn regarding the feasibility of this approach and directions for further research.