998 resultados para lymphatic space invasion


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While much narrative inquiry is concerned with issues of self and identity, doing study on the processes (the how) of self-making offers ongoing challenges to methodology. This article explores the creation of a dialogic space that assisted young adolescents to write about themselves and their daily lives using email journals as an alternative to face-to-face interviews. With the researcher acting as a listener-responder, and in the absence of researcher-designed questions, a dynamic field was opened up for participant-led self-making to emerge over a six month period of self-reflective written expression. The article describes a shared email relationship based on a dialogic pattern of thinking, writing, listening and response intended to foster participants’ voices as ontological narratives of self. Findings show the use of email journals created a synergy for self-disclosure and a safe space for self-expression where the willingness of participants to be themselves was encouraged. The self-representations of a specific group of gifted young adolescents thus emerged as written versions of “who” they are —offering data that differs from interview approaches and contributing to discussion of the value of ontology narratives.

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Video surveillance systems using Closed Circuit Television (CCTV) cameras, is one of the fastest growing areas in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. This work attempts to address these problems by proposing an automatic suspicious behaviour detection which utilises contextual information. The utilisation of contextual information is done via three main components: a context space model, a data stream clustering algorithm, and an inference algorithm. The utilisation of contextual information is still limited in the domain of suspicious behaviour detection. Furthermore, it is nearly impossible to correctly understand human behaviour without considering the context where it is observed. This work presents experiments using video feeds taken from CAVIAR dataset and a camera mounted on one of the buildings Z-Block) at the Queensland University of Technology, Australia. From these experiments, it is shown that by exploiting contextual information, the proposed system is able to make more accurate detections, especially of those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information gives critical feedback to the system designers to refine the system.

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Existing recommendation systems often recommend products to users by capturing the item-to-item and user-to-user similarity measures. These types of recommendation systems become inefficient in people-to-people networks for people to people recommendation that require two way relationship. Also, existing recommendation methods use traditional two dimensional models to find inter relationships between alike users and items. It is not efficient enough to model the people-to-people network with two-dimensional models as the latent correlations between the people and their attributes are not utilized. In this paper, we propose a novel tensor decomposition-based recommendation method for recommending people-to-people based on users profiles and their interactions. The people-to-people network data is multi-dimensional data which when modeled using vector based methods tend to result in information loss as they capture either the interactions or the attributes of the users but not both the information. This paper utilizes tensor models that have the ability to correlate and find latent relationships between similar users based on both information, user interactions and user attributes, in order to generate recommendations. Empirical analysis is conducted on a real-life online dating dataset. As demonstrated in results, the use of tensor modeling and decomposition has enabled the identification of latent correlations between people based on their attributes and interactions in the network and quality recommendations have been derived using the 'alike' users concept.

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This chapter examines the changing landscape of literacy in the early years and considers how the diverse spaces and places in which early literacy learning is promoted and takes place can be conceptualised and researched. We argue that early literacy research needs to extend beyond a language focus to become attentive to the embodied, material dimensions of learning environments. The discussion is organised in terms of three kinds of spaces within which children encounter opportunities to participate in communication and representational practices. These are domestic spaces, commercial spaces and spaces of formal education. Theories of spatiality and material semiotics provide the conceptual tools for interpreting research studies located in these spaces. Implications for educators are considered.

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The natural convection thermal boundary layer adjacent to an inclined flat plate and inclined walls of an attic space subject to instantaneous and ramp heating and cooling is investigated. A scaling analysis has been performed to describe the flow behaviour and heat transfer. Major scales quantifying the flow velocity, flow development time, heat transfer and the thermal and viscous boundary layer thicknesses at different stages of the flow development are established. Scaling relations of heating-up and cooling-down times and heat transfer rates have also been reported for the case of attic space. The scaling relations have been verified by numerical simulations over a wide range of parameters. Further, a periodic temperature boundary condition is also considered to show the flow features in the attic space over diurnal cycles.

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In an era of normative standardised literacy curriculum continuing to make space for culturally responsive literacy pedagogy is on ongoing challenge for early childhood educators. Collaborative participatory research and ethnographic studies of teachers who accomplish innovative and inclusive early childhood education in culturally diverse high poverty communities is urgent for the profession. Such pedagogies involve complex understandings of the cultural and political histories, and the dynamic potential, of the places in which school communities are located. By incorporating the study of local histories and biographies and researching neighbourhood changes teachers adapt mandated curriculum to maintain community knowledges and allow for positive identity work at the same time as they meet the authorised systems objectives. When teachers work with children as co-researchers through the study of people's lives in particular places and times, the community and its complex histories become a rich resource for young people's literacy repertoires.

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A time-resolved inverse spatially offset Raman spectrometer was constructed for depth profiling of Raman-active substances under both the lab and the field environments. The system operating principles and performance are discussed along with its advantages relative to traditional continuous wave spatially offset Raman spectrometer. The developed spectrometer uses a combination of space- and time-resolved detection in order to obtain high-quality Raman spectra from substances hidden behind coloured opaque surface layers, such as plastic and garments, with a single measurement. The time-gated spatially offset Raman spectrometer was successfully used to detect concealed explosives and drug precursors under incandescent and fluorescent background light as well as under daylight. The average screening time was 50 s per measurement. The excitation energy requirements were relatively low (20 mW) which makes the probe safe for screening hazardous substances. The unit has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than previous picosecond-based systems, to provide a functional platform for in-line or in-field sensing of chemical substances.

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PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models (SSM). PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries Numpy and Scipy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimised and parallelised Fortran routines. These Fortran routines heavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package (LAPACK) functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.

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By 2020 Australia‟s National Digital Economy Strategy aims to increase household online participation and engage 12 per cent of all employees in teleworking arrangements. Achieving these goals is generally perceived as positive due to the reduced impact on the natural environment from less use of transport. However, this also will enable greater flexibility as to where people live and thus will impact upon the maintenance and formation of communities and on property use. This paper commences by clarifying what is Australia‟s internet economy before highlighting the impact of the internet on community formation and maintenance. The paper concludes by identifying what the achievement of these goals will mean for property use in the future.

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Written for Redland City Council in collaboration with the Capalaba Stakeholders Group. The provisions detailed in this report constitute a protocol agreement developed through the Capalaba Stakeholders Group between 2009 and 2011 around young people and public spaces in Redland City, Queensland. These provisions include agreed principles, standards and responses to tensions or unacceptable behaviour, how various tensions and problems can be resolved in constructive ways and how people, including young people can work together to make a public or community accessed space safe and accessible. It is based on the recognition that young people are part of the community and that strategies to resolve tensions that arise should be inclusive and employ a mixed methods approach.

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Having a good automatic anomalous human behaviour detection is one of the goals of smart surveillance systems’ domain of research. The automatic detection addresses several human factor issues underlying the existing surveillance systems. To create such a detection system, contextual information needs to be considered. This is because context is required in order to correctly understand human behaviour. Unfortunately, the use of contextual information is still limited in the automatic anomalous human behaviour detection approaches. This paper proposes a context space model which has two benefits: (a) It provides guidelines for the system designers to select information which can be used to describe context; (b)It enables a system to distinguish between different contexts. A comparative analysis is conducted between a context-based system which employs the proposed context space model and a system which is implemented based on one of the existing approaches. The comparison is applied on a scenario constructed using video clips from CAVIAR dataset. The results show that the context-based system outperforms the other system. This is because the context space model allows the system to considering knowledge learned from the relevant context only.

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Urban regeneration is occuring in cities across the world, as cities increase in scale and complexity. This chapter argues that in planning public spaces, greater consideration should be paid to sociability through consideration of the affective dimension of urban life.

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It is a matter of public record that the former Prime Minister of Australia, the Honourable Paul Keating, upset certain Australian architects with his intervention into the redevelopment of the 22-hectare “Barangaroo” site on Sydney Harbour. While Keating’s intervention continues to provide engaging theatre for Sydney residents the debate is also an interesting expression of the narrative of contestation that has been played out historically about the waters of Sydney Harbour. From a cultural studies perspective, the Harbour, and the Sydney Harbour Bridge, has been for many years a political and imaginative space that captures a diversity of local and national preoccupations. Keating’s announcement that planners have a “once-in-200-year opportunity to call a halt to the kind of encroachments we have seen in the past” is in fact another moment in the long history of disputation over the impact of the man-made environment on the natural landform in this area. This paper addresses the spaces of Sydney Harbour as represented in recent debates and in writing and film from previous decades. The argument suggests that the Harbour is a complex site of public and private enactment that is played out in a diverse range of cultural representations. In particular, the paper notes the work of Michel de Certeau on the mythic qualities of certain spaces in relation to the space of the Harbour. ‘The Greatest Harbour in the World’ argues that the Harbour, and the Bridge, fulfils a particular historical and cultural function that gives this space a set of meanings that are well beyond the typical parameters of urban development.