886 resultados para Projection


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As climate change will entail new conditions for the built environment, the thermal behaviour of air-conditioned office buildings may also change. Using building computer simulations, the impact of warmer weather is evaluated on the design and performance of air-conditioned office buildings in Australia, including the increased cooling loads and probable indoor temperature increases due to a possibly undersized air-conditioning system, as well as the possible change in energy use. It is found that existing office buildings would generally be able to adapt to the increasing warmth of year 2030 Low and High scenarios projections and the year 2070 Low scenario projection. However, for the 2070 High scenario, the study indicates that the existing office buildings in all capital cities of Australia would suffer from overheating problems. For existing buildings designed for current climate conditions, it is shown that there is a nearly linear correlation between the increase of average external air temperature and the increase of building cooling load. For the new buildings designed for warmer scenarios, a 28-59% increase of cooling capacity under the 2070 High scenario would be required.

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X-ray computed tomography (CT) is a medical imaging technique that produces images of trans-axial planes through the human body. When compared with a conventional radiograph, which is an image of many planes superimposed on each other, a CT image exhibits significantly improved contrast although this is at the expense of reduced spatial resolution.----- A CT image is reconstructed mathematically from a large number of one dimensional projections of the chosen plane. These projections are acquired electronically using a linear array of solid-state detectors and an x ray source that rotates around the patient.----- X-ray computed tomography is used routinely in radiological examinations. It has also be found to be useful in special applications such as radiotherapy treatment planning and three-dimensional imaging for surgical planning.

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The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

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Automatic Speech Recognition (ASR) has matured into a technology which is becoming more common in our everyday lives, and is emerging as a necessity to minimise driver distraction when operating in-car systems such as navigation and infotainment. In “noise-free” environments, word recognition performance of these systems has been shown to approach 100%, however this performance degrades rapidly as the level of background noise is increased. Speech enhancement is a popular method for making ASR systems more ro- bust. Single-channel spectral subtraction was originally designed to improve hu- man speech intelligibility and many attempts have been made to optimise this algorithm in terms of signal-based metrics such as maximised Signal-to-Noise Ratio (SNR) or minimised speech distortion. Such metrics are used to assess en- hancement performance for intelligibility not speech recognition, therefore mak- ing them sub-optimal ASR applications. This research investigates two methods for closely coupling subtractive-type enhancement algorithms with ASR: (a) a computationally-efficient Mel-filterbank noise subtraction technique based on likelihood-maximisation (LIMA), and (b) in- troducing phase spectrum information to enable spectral subtraction in the com- plex frequency domain. Likelihood-maximisation uses gradient-descent to optimise parameters of the enhancement algorithm to best fit the acoustic speech model given a word se- quence known a priori. Whilst this technique is shown to improve the ASR word accuracy performance, it is also identified to be particularly sensitive to non-noise mismatches between the training and testing data. Phase information has long been ignored in spectral subtraction as it is deemed to have little effect on human intelligibility. In this work it is shown that phase information is important in obtaining highly accurate estimates of clean speech magnitudes which are typically used in ASR feature extraction. Phase Estimation via Delay Projection is proposed based on the stationarity of sinusoidal signals, and demonstrates the potential to produce improvements in ASR word accuracy in a wide range of SNR. Throughout the dissertation, consideration is given to practical implemen- tation in vehicular environments which resulted in two novel contributions – a LIMA framework which takes advantage of the grounding procedure common to speech dialogue systems, and a resource-saving formulation of frequency-domain spectral subtraction for realisation in field-programmable gate array hardware. The techniques proposed in this dissertation were evaluated using the Aus- tralian English In-Car Speech Corpus which was collected as part of this work. This database is the first of its kind within Australia and captures real in-car speech of 50 native Australian speakers in seven driving conditions common to Australian environments.

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A promenade performance. This research produced a unique combination of performance using electronically augmented costuming, site-specific discrete electronic lighting and video projection and sustained mountainside/top choreography. The work was examined and expanded in two subsequent peer reviewed papers which scoped out the emerging field of ‘Grounded Media’. Curator and writer Kevin Murray further accorded and enhanced these ideas in subsequent critical writing and the work was also featured in a two page major profile in RealtimeThe work was commissioned by the long established Floating Land Festival and involved extensive on-site work as well as a residency, production and artist talk series at the Noosa Art Gallery. A documentary film of the work was subsequently presented in the three-month exhibition ‘Lines of Sight’ for the Nishi Ogi Machi Media Festival, Nishiogikubo Station Platform 1, Tokyo, Japan, curated by Youkobo Art Space.

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An Interactive Installation with holographic 3D projections, satellite imagery, surround sound and intuitive body driven interactivity. Remnant (v.1) was commissioned by the 2010 TreeLine ecoArt event - an initiative of the Sunshine Coast Council and presented at a remnant block of subtropical rainforest called ‘Mary Cairncross Scenic Reserve’ - located 100kms north of Brisbane near the township of Maleny. V2 was later commissioned for KickArts Gallery, Cairns, re-presenting the work in a new open format which allowed audiences to both experience the original power of the work and to also understand the construction of the work's powerful illusory, visual spaces. This art-science project focused upon the idea of remnant landscapes - isolated blocks of forest (or other vegetation types) typically set within a patchwork quilt of surrounding farmed land. Participants peer into a mysterious, long tunnel of imagery whilst navigating entirely through gentle head movements - allowing them to both 'steer' in three dimensions and also 'alight', as a butterfly might, upon a sector of landscape - which in turn reveals an underlying 'landscape of mind'. The work challenges audiences to re-imagine our conceptions of country in ways that will lead us to better reconnect and sustain today’s heavily divided landscapes. The research field involved developing new digital image projection methods, alternate embodied interaction and engagement strategies for eco-political media arts practice. The context was the creation of improved embodied and improvisational experiences for participants, further informed by ‘eco-philosophical’ and sustainment theories. By engaging with deep conceptions of connectivity between apparently disparate elements, the work considered novel strategies for fostering new desires, for understanding and re-thinking the requisite physical and ecological links between ‘things’ that have been historically shattered. The methodology was primarily practice-led and in concert with underlying theories. The work’s knowledge contribution was to question how new media interactive experience and embodied interaction might prompt participants to reflect upon appropriate resources and knowledges required to generate this substantive desire for new approaches to sustainment. This accentuated through the power of learning implied by the works' strongly visual and kinaesthetic interface (i.e. the tunnel of imagery and the head and torso operated navigation). The work was commissioned by the 2010 TreeLine ecoArt event - an initiative of the Sunshine Coast Council and the second version was commissioned by Kickarts Gallery, Cairns, specifically funded by a national optometrist chain. It was also funded in development by Arts Queensland and reviewed in Realtime.

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The Pedestrian Interaction Patch Project (PIPP) seeks to exert influence over and encourage abnormal pedestrian behavior. By placing an unadvertised (and non recording) interactive video manipulation system and projection source in a high traffic public area, the PIPP allows pedestrians to privately (and publically) re-engage with a previously inactive physical environment, like a commonly used walkway or corridor. This system, the results of which are projected in real time on the architectural surface, inadvertently provides pedestrians with questions around preconceived notions of self and space. In an attempt to re-activate our relationship with the physical surrounds we occupy each day the PIPP creates a new set of memories to be recalled as we re-enter known environments once PIPP has moved on and as such re-enlivens our relationship with the everyday architecture we stroll past everyday. The PIPP environment is controlled using the software program Isadora, devised by Mark Coniglio at Troika Ranch, and contains a series of video manipulation patches that are designed to not only grab the pedestrians attention but to also encourage a sense of play and interaction between the architecture, the digital environment, the initially unsuspecting participant(s) and the pedestrian audience. The PIPP was included as part of the planned walking tour for the “Playing in Urban Spaces” seminar day, and was an installation that ran for the length of the symposium in a reclaimed pedestrian space that was encountered by both the participants and general public during the course of the day long event. Ideally once discovered PIPP encouraged pedestrians to return through the course of the seminar day to see if the environmental patches had changed or altered, and changed their standard route to include the PIPP installation or to avoid it, either way, encouraging an active response to the pathways normally traveled or newly discovered each day.

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Robust image hashing seeks to transform a given input image into a shorter hashed version using a key-dependent non-invertible transform. These image hashes can be used for watermarking, image integrity authentication or image indexing for fast retrieval. This paper introduces a new method of generating image hashes based on extracting Higher Order Spectral features from the Radon projection of an input image. The feature extraction process is non-invertible, non-linear and different hashes can be produced from the same image through the use of random permutations of the input. We show that the transform is robust to typical image transformations such as JPEG compression, noise, scaling, rotation, smoothing and cropping. We evaluate our system using a verification-style framework based on calculating false match, false non-match likelihoods using the publicly available Uncompressed Colour Image database (UCID) of 1320 images. We also compare our results to Swaminathan’s Fourier-Mellin based hashing method with at least 1% EER improvement under noise, scaling and sharpening.

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This thesis addresses the problem of detecting and describing the same scene points in different wide-angle images taken by the same camera at different viewpoints. This is a core competency of many vision-based localisation tasks including visual odometry and visual place recognition. Wide-angle cameras have a large field of view that can exceed a full hemisphere, and the images they produce contain severe radial distortion. When compared to traditional narrow field of view perspective cameras, more accurate estimates of camera egomotion can be found using the images obtained with wide-angle cameras. The ability to accurately estimate camera egomotion is a fundamental primitive of visual odometry, and this is one of the reasons for the increased popularity in the use of wide-angle cameras for this task. Their large field of view also enables them to capture images of the same regions in a scene taken at very different viewpoints, and this makes them suited for visual place recognition. However, the ability to estimate the camera egomotion and recognise the same scene in two different images is dependent on the ability to reliably detect and describe the same scene points, or ‘keypoints’, in the images. Most algorithms used for this purpose are designed almost exclusively for perspective images. Applying algorithms designed for perspective images directly to wide-angle images is problematic as no account is made for the image distortion. The primary contribution of this thesis is the development of two novel keypoint detectors, and a method of keypoint description, designed for wide-angle images. Both reformulate the Scale- Invariant Feature Transform (SIFT) as an image processing operation on the sphere. As the image captured by any central projection wide-angle camera can be mapped to the sphere, applying these variants to an image on the sphere enables keypoints to be detected in a manner that is invariant to image distortion. Each of the variants is required to find the scale-space representation of an image on the sphere, and they differ in the approaches they used to do this. Extensive experiments using real and synthetically generated wide-angle images are used to validate the two new keypoint detectors and the method of keypoint description. The best of these two new keypoint detectors is applied to vision based localisation tasks including visual odometry and visual place recognition using outdoor wide-angle image sequences. As part of this work, the effect of keypoint coordinate selection on the accuracy of egomotion estimates using the Direct Linear Transform (DLT) is investigated, and a simple weighting scheme is proposed which attempts to account for the uncertainty of keypoint positions during detection. A word reliability metric is also developed for use within a visual ‘bag of words’ approach to place recognition.

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In this paper we propose a new method for utilising phase information by complementing it with traditional magnitude-only spectral subtraction speech enhancement through Complex Spectrum Subtraction (CSS). The proposed approach has the following advantages over traditional magnitude-only spectral subtraction: (a) it introduces complementary information to the enhancement algorithm; (b) it reduces the total number of algorithmic parameters, and; (c) is designed for improving clean speech magnitude spectra and is therefore suitable for both automatic speech recognition (ASR) and speech perception applications. Oracle-based ASR experiments verify this approach, showing an average of 20% relative word accuracy improvements when accurate estimates of the phase spectrum are available. Based on sinusoidal analysis and assuming stationarity between observations (which is shown to be better approximated as the frame rate is increased), this paper also proposes a novel method for acquiring the phase information called Phase Estimation via Delay Projection (PEDEP). Further oracle ASR experiments validate the potential for the proposed PEDEP technique in ideal conditions. Realistic implementation of CSS with PEDEP shows performance comparable to state of the art spectral subtraction techniques in a range of 15-20 dB signal-to-noise ratio environments. These results clearly demonstrate the potential for using phase spectra in spectral subtractive enhancement applications, and at the same time highlight the need for deriving more accurate phase estimates in a wider range of noise conditions.

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Script for non verbal performance work for young audiences. Three productions by the Queensland Theatre Company 2000-2002. (QTC/QPAC) Out of the Box Festival of Early Childhood 2000. Queensland Arts Council Tours 2000, 2001, 2002. Seoul Arts Centre 2000 Selected by ASSITEJ as a representative script for Australia Set entirely in the backseat of a car, with the road behind appearing on a rear-projection screen, Backseat Driver is the story of two very different children battling the fingerdrumming, motor-humming boredom of a long car trip. Using non-verbal performance, video projection and the music of Cliff Richard, Elvis Presley and the Shadows, Backseat Drivers is a comedy for anyone who has ever asked the question ”are we there yet?”. Exploring the power of creative play, Backseat Driver has enjoyed three productions, including a season for Korean audiences at the Seoul Arts Centre in 2001.

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Script and images from creative development of performance project conducted in February 2005. Supported with a grant from Arts Queensland, this non-verbal, music driven two-hander, designed for young audiences, utilised video projection and the music of Erik Satie and Bill Evans to explore issues around conflict and environment.

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Script for non verbal performance work for young audiences. Three productions by the Queensland Theatre Company 2000-2002. ----- ----- ----- (QTC/QPAC) Out of the Box Festival of Early Childhood 2000. Queensland Arts Council Tours 2000, 2001, 2002. Seoul Arts Centre 2000 ----- ----- ----- Selected by ASSITEJ as a representative script for Australia ----- ----- ----- Set entirely in the backseat of a car, with the road behind appearing on a rear-projection screen, Backseat Driver is the story of two very different children battling the fingerdrumming, motor-humming boredom of a long car trip. Using non-verbal performance, video projection and the music of Cliff Richard, Elvis Presley and the Shadows, Backseat Drivers is a comedy for anyone who has ever asked the question ”are we there yet?”. Exploring the power of creative play, Backseat Driver has enjoyed three productions, including a season for Korean audiences at the Seoul Arts Centre in 2001.