409 resultados para Dunkl-Bessel Transform
Resumo:
The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of 10^5, 10^2 and 10^0 sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of 10^-2, 10^-1 and 10^0 Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.
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With the introduction of the Personally Controlled Health Record (PCEHR), the Australian public is being asked to accept greater responsibility for their healthcare. Although well designed, constructed and intentioned, policy and privacy concerns have resulted in an eHealth model that may impact future health information sharing requirements. Thus an opportunity to transform the beleaguered Australian PCEHR into a sustainable on-demand technology consumption model for patient safety must be explored further. Moreover, the current clerical focus of healthcare practitioners must be renegotiated to establish a shared knowledge creation landscape of action for safer patient interventions. To achieve this potential however requires a platform that will facilitate efficient and trusted unification of all health information available in real-time across the continuum of care. As a conceptual paper, the goal of the authors is to deliver insights into the antecedents of usage influencing superior patient outcomes within an eHealth-as-a-Service framework. To achieve this, the paper attempts to distil key concepts and identify common themes drawn from a preliminary literature review of eHealth and cloud computing concepts, specifically cloud service orchestration to establish a conceptual framework and a research agenda. Initial findings support the authors’ view that an eHealth-as-a-Service (eHaaS) construct will serve as a disruptive paradigm shift in the aggregation and transformation of health information for use as real-world knowledge in patient care scenarios. Moreover, the strategic value of extending the community Health Record Bank (HRB) model lies in the ability to automatically draw on a multitude of relevant data repositories and sources to create a single source of practice based evidence and to engage market forces to create financial sustainability.
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This guide is to support institutions in developing and teaching tertiary level programmes for sustainable energy professionals. Ongoing curriculum renewal is more difficult but vital for multidisciplinary courses preparing graduates to work in a specialised rapidly changing field. After more than 15 years of offering tertiary level “sustainable energy” qualifications in Australian Universities there was a clear need to assess how these courses are taught and develop curriculum frameworks to guide Universities designing/redesigning programs and courses to provide graduates with the relevant skills, knowledge and attributes (capabilities) seen by graduates and employers as required to work in this rapidly changing field. This guide presents the sustainable energy curriculum frameworks developed by the “Renewing the sustainable energy curriculum – providing internationally relevant skills for a carbon constrained economy” project, which was conducted over a two-and-a-quarter year period.
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This paper evaluates the performance of different text recognition techniques for a mobile robot in an indoor (university campus) environment. We compared four different methods: our own approach using existing text detection methods (Minimally Stable Extremal Regions detector and Stroke Width Transform) combined with a convolutional neural network, two modes of the open source program Tesseract, and the experimental mobile app Google Goggles. The results show that a convolutional neural network combined with the Stroke Width Transform gives the best performance in correctly matched text on images with single characters whereas Google Goggles gives the best performance on images with multiple words. The dataset used for this work is released as well.
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In this paper we propose the hybrid use of illuminant invariant and RGB images to perform image classification of urban scenes despite challenging variation in lighting conditions. Coping with lighting change (and the shadows thereby invoked) is a non-negotiable requirement for long term autonomy using vision. One aspect of this is the ability to reliably classify scene components in the presence of marked and often sudden changes in lighting. This is the focus of this paper. Posed with the task of classifying all parts in a scene from a full colour image, we propose that lighting invariant transforms can reduce the variability of the scene, resulting in a more reliable classification. We leverage the ideas of “data transfer” for classification, beginning with full colour images for obtaining candidate scene-level matches using global image descriptors. This is commonly followed by superpixellevel matching with local features. However, we show that if the RGB images are subjected to an illuminant invariant transform before computing the superpixel-level features, classification is significantly more robust to scene illumination effects. The approach is evaluated using three datasets. The first being our own dataset and the second being the KITTI dataset using manually generated ground truth for quantitative analysis. We qualitatively evaluate the method on a third custom dataset over a 750m trajectory.
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During the 18th and 19th centuries, prostitution came to be understood as a potentially disruptive element in the management of society. New forms of social control developed that sought to transform the souls of prostitutes to better control their bodies. Institutions for managing prostitutes, such as Magdalen Homes and lock hospitals, were introduced or increased in number throughout the British Empire, North America, and Western Europe. Often these institutions had as their stated objective the physical purification and moral reform of prostitutes, appearing to make a dramatic break with earlier methods of social control that had relied on practices of physical punishment and spatial segregation. Emergent institutions for the social control of prostitutes used a regimen of religious training, hard labor, and medical expertise. The objective of the Magdalen Home was not to punish sin but to absolve it, while the function of the lock hospital was not simply to confine the ill, but to confine the ill to "cure" them. The role of these institutions was not only symbolic, mirroring in some way the operation of earlier forms of social control, but was also practical and transformative. The mass institutionalization of prostitutes that occurred during the 18th and 19th centuries produced and emphasized sexual, class, and gender boundaries, grounded in the broad distinction between "pure" and "impure" women. Because of its association with sin, prostitution before the 18th century had been constructed as a religious problem relating to salvation and penitence. Throughout Western Europe during the Middle Ages, prostitutes, like the medieval leper and the Jew, were subject to restrictions designed to distinguish and isolate them from other members of their communities. The repression of prostitution during the Middle Ages was neither systematic nor highly organized, although it reinforced the image of the prostitute as sinful "other".
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Digital innovation is transforming the media and entertainment industries. The professionalization of YouTube’s platform is paradigmatic of that change. The 100 original channel initiative launched in late 2011 was designed to transform YouTube’s brand through production of a high volume of quality premium video content that would more deeply engage its audience base and in the process attract big advertisers. An unanticipated by-product has been the rapid growth of a wave of aspiring next-generation digital media companies from within the YouTube ecosystem. Fuelled by early venture capital some have ambitious goals to become global media corporations in the online video space. A number of larger MCNs (Multi-Channel Networks) - BigFrame, Machinima, Fullscreen, AwesomenessTV, Maker Studios , Revision3 and DanceOn - have attracted interest from media incumbents like Warner Brothers, DreamWorks, Discovery, Bertlesmann, Comcast and AMC, and two larger MCNs Alloy and Break Media have merged. This indicates that a shakeout is underway in these new online supply chains, after rapid initial growth. The higher profile MCNs seek to rapidly develop scale economies in online distribution and facilitate audience growth for their member channels, helping channels optimize monetization, develop sustainable business models and to facilitate producer-collaboration within a growing online community of like-minded content creators. Some MCNs already attract far larger online audiences than any national TV network. The speed with which these developments have occurred is reminiscent of the 1910s, when Hollywood studios first emerged and within only a few years replaced the incumbent film studios as the dominant force within the film industry.
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This research provides an assessment tool that assists the selection process of sustainability in detached suburban housing. It investigates the implications of using different design and construction methods including architecturally designed houses, developer housing and prefabricated houses. The study simulates one example of the three types of houses that have been chosen to fulfil a real client brief on a real site on the Sunshine Coast, Queensland Australia. Criteria for sustainability assessment are formulated based on literature reviews, exemplar designs and similar research projects for which the houses can be adequately evaluated. This criterion covers aspects including energy use, materials and thermal performance. The data is collected using computer models and sustainability assessment software to compare and draw conclusions on the success of each house. Our study indicates that architecturally designed housing with prefabricated building techniques are a better alternative to generic developer style housing. Our research provides an insight into the implications of three key elements of sustainability including energy use, materials and thermal performance. Designers, builders, developers and home-buyers are given an insight into some options currently available on the housing market and how the choices made during early design stages can provide a more positive environmental impact.
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In studies of germ cell transplantation, measureing tubule diameters and counting cells from different populations using antibodies as markers are very important. Manual measurement of tubule sizes and cell counts is a tedious and sanity grinding work. In this paper, we propose a new boundary weighting based tubule detection method. We first enhance the linear features of the input image and detect the approximate centers of tubules. Next, a boundary weighting transform is applied to the polar transformed image of each tubule region and a circular shortest path is used for the boundary detection. Then, ellipse fitting is carried out for tubule selection and measurement. The algorithm has been tested on a dataset consisting of 20 images, each having about 20 tubules. Experiments show that the detection results of our algorithm are very close to the results obtained manually. © 2013 IEEE.
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This book is about understanding the nature and application of reflection in higher education. It provides a theoretical model to guide the implementation of reflective learning and reflective practice across multiple disciplines and international contexts in higher education. The book presents research into the ways in which reflection is both considered and implemented in different ways across different professional disciplines, while maintaining a common purpose to transform and improve learning and/or practice. Readers will find this book innovative and new in three key ways. First, in its holistic theorisation of reflection within the pedagogic field of higher education; Secondly, in conceptualising reflection in different modes to achieve specific purposes in different disciplines; and finally, in providing conceptual guidance for embedding reflective learning and reflective practice in a systematic way across whole programmes, faculties or institutions in higher education. The book considers important contextual factors that influence the teaching of forms and methods of reflection. It provides a functional analysis of multiple modes of reflection, including written, oral, visual, auditory, and embodied forms. Empirical chapters analyse the application of these modes across disciplines and at different stages of a programme. The theoretical model accounts for students’ stage of development in the disciplinary field, along with progressive and cyclical levels of higher order thinking, and learning and professional practice that are expected within different disciplines and professional fields. The book provides: • A conceptual model for the application of reflection across disciplines in a variety of contexts. • Empirical examples of different modes and pedagogic patterns for reflection. • Guidance and support for embedding systemic pedagogical and curriculum change.
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Bat researchers currently use a variety of techniques that transform echolocation calls into audible frequencies and allow the spectral content of a signal to be viewed and analyzed. All techniques have limitations and an understanding of how each works and the effect on the signal being analyzed are vital for correct interpretation. The 3 most commonly used techniques for transforming frequencies of a call are heterodyne, frequency division, and time expansion. Three techniques for viewing spectral content of a signal are zero-crossing, Fourier analysis, and instantaneous frequency analysis. It is important for bat researchers to be familiar with the advantages and disadvantages of each technique.