162 resultados para 200 series


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Dr Mills is also the invited author of the Deep End Series Teacher Guides by ERA publications. This 3-volume series for teachers is used in more than 200 schools in Australia, the USA, Canada, New Zealand, Sweden, Norway, and South America.

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Dr Mills is the invited author of the Deep End Series Teacher Guides by ERA publications. This 3-volume series for teachers is used in more than 200 schools in Australia, the USA, Canada, New Zealand, Sweden, Norway, and South America.

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Dr Mills is also the invited author of the Deep End Series Teacher Guides by ERA publications. This 3-volume series for teachers is used in more than 200 schools in Australia, the USA, Canada, New Zealand, Sweden, Norway, and South America.

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A forced landing is an unscheduled event in flight requiring an emergency landing, and is most commonly attributed to engine failure, failure of avionics or adverse weather. Since the ability to conduct a successful forced landing is the primary indicator for safety in the aviation industry, automating this capability for unmanned aerial vehicles (UAVs) will help facilitate their integration into, and subsequent routine operations over civilian airspace. Currently, there is no commercial system available to perform this task; however, a team at the Australian Research Centre for Aerospace Automation (ARCAA) is working towards developing such an automated forced landing system. This system, codenamed Flight Guardian, will operate onboard the aircraft and use machine vision for site identification, artificial intelligence for data assessment and evaluation, and path planning, guidance and control techniques to actualize the landing. This thesis focuses on research specific to the third category, and presents the design, testing and evaluation of a Trajectory Generation and Guidance System (TGGS) that navigates the aircraft to land at a chosen site, following an engine failure. Firstly, two algorithms are developed that adapts manned aircraft forced landing techniques to suit the UAV planning problem. Algorithm 1 allows the UAV to select a route (from a library) based on a fixed glide range and the ambient wind conditions, while Algorithm 2 uses a series of adjustable waypoints to cater for changing winds. A comparison of both algorithms in over 200 simulated forced landings found that using Algorithm 2, twice as many landings were within the designated area, with an average lateral miss distance of 200 m at the aimpoint. These results present a baseline for further refinements to the planning algorithms. A significant contribution is seen in the design of the 3-D Dubins Curves planning algorithm, which extends the elementary concepts underlying 2-D Dubins paths to account for powerless flight in three dimensions. This has also resulted in the development of new methods in testing for path traversability, in losing excess altitude, and in the actual path formation to ensure aircraft stability. Simulations using this algorithm have demonstrated lateral and vertical miss distances of under 20 m at the approach point, in wind speeds of up to 9 m/s. This is greater than a tenfold improvement on Algorithm 2 and emulates the performance of manned, powered aircraft. The lateral guidance algorithm originally developed by Park, Deyst, and How (2007) is enhanced to include wind information in the guidance logic. A simple assumption is also made that reduces the complexity of the algorithm in following a circular path, yet without sacrificing performance. Finally, a specific method of supplying the correct turning direction is also used. Simulations have shown that this new algorithm, named the Enhanced Nonlinear Guidance (ENG) algorithm, performs much better in changing winds, with cross-track errors at the approach point within 2 m, compared to over 10 m using Park's algorithm. A fourth contribution is made in designing the Flight Path Following Guidance (FPFG) algorithm, which uses path angle calculations and the MacCready theory to determine the optimal speed to fly in winds. This algorithm also uses proportional integral- derivative (PID) gain schedules to finely tune the tracking accuracies, and has demonstrated in simulation vertical miss distances of under 2 m in changing winds. A fifth contribution is made in designing the Modified Proportional Navigation (MPN) algorithm, which uses principles from proportional navigation and the ENG algorithm, as well as methods specifically its own, to calculate the required pitch to fly. This algorithm is robust to wind changes, and is easily adaptable to any aircraft type. Tracking accuracies obtained with this algorithm are also comparable to those obtained using the FPFG algorithm. For all three preceding guidance algorithms, a novel method utilising the geometric and time relationship between aircraft and path is also employed to ensure that the aircraft is still able to track the desired path to completion in strong winds, while remaining stabilised. Finally, a derived contribution is made in modifying the 3-D Dubins Curves algorithm to suit helicopter flight dynamics. This modification allows a helicopter to autonomously track both stationary and moving targets in flight, and is highly advantageous for applications such as traffic surveillance, police pursuit, security or payload delivery. Each of these achievements serves to enhance the on-board autonomy and safety of a UAV, which in turn will help facilitate the integration of UAVs into civilian airspace for a wider appreciation of the good that they can provide. The automated UAV forced landing planning and guidance strategies presented in this thesis will allow the progression of this technology from the design and developmental stages, through to a prototype system that can demonstrate its effectiveness to the UAV research and operations community.

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Background Birth weight and length have seasonal fluctuations. Previous analyses of birth weight by latitude effects identified seemingly contradictory results, showing both 6 and 12 monthly periodicities in weight. The aims of this paper are twofold: (a) to explore seasonal patterns in a large, Danish Medical Birth Register, and (b) to explore models based on seasonal exposures and a non-linear exposure-risk relationship. Methods Birth weight and birth lengths on over 1.5 million Danish singleton, live births were examined for seasonality. We modelled seasonal patterns based on linear, U- and J-shaped exposure-risk relationships. We then added an extra layer of complexity by modelling weighted population-based exposure patterns. Results The Danish data showed clear seasonal fluctuations for both birth weight and birth length. A bimodal model best fits the data, however the amplitude of the 6 and 12 month peaks changed over time. In the modelling exercises, U- and J-shaped exposure-risk relationships generate time series with both 6 and 12 month periodicities. Changing the weightings of the population exposure risks result in unexpected properties. A J-shaped exposure-risk relationship with a diminishing population exposure over time fitted the observed seasonal pattern in the Danish birth weight data. Conclusion In keeping with many other studies, Danish birth anthropometric data show complex and shifting seasonal patterns. We speculate that annual periodicities with non-linear exposure-risk models may underlie these findings. Understanding the nature of seasonal fluctuations can help generate candidate exposures.

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The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

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This paper proposes an innovative instance similarity based evaluation metric that reduces the search map for clustering to be performed. An aggregate global score is calculated for each instance using the novel idea of Fibonacci series. The use of Fibonacci numbers is able to separate the instances effectively and, in hence, the intra-cluster similarity is increased and the inter-cluster similarity is decreased during clustering. The proposed FIBCLUS algorithm is able to handle datasets with numerical, categorical and a mix of both types of attributes. Results obtained with FIBCLUS are compared with the results of existing algorithms such as k-means, x-means expected maximization and hierarchical algorithms that are widely used to cluster numeric, categorical and mix data types. Empirical analysis shows that FIBCLUS is able to produce better clustering solutions in terms of entropy, purity and F-score in comparison to the above described existing algorithms.

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The QUT Design Lecture Series 2010 was a partnered event between QUT School of Design and the State Library of Queensland. The series, spanning from July to September 2010, involved 10 lectures delivered by international, national and local academics, researchers and practitioners. The QUT Design Lecture series 2010 was a public event which examined the cross over between design, digital technologies and artistic practices focusing upon research themes of intangible media, experimental eco-technologies and artistic-design production. Gold Medal Australian Institute of Architects, Clare Design opened the series, whilst internationally awarded and recognised Spanish design group Cloud 9 concluded the series, both focusing on new eco-technologies in the development of contemporary architecture.

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This publication is the first in a series of scholarly reports on research-based practice related to the First Year Experience in Higher Education. This report synthesises evidence about practice-based initiatives and pragmatic approaches in Aotearoa (New Zealand) and Australia that aim to enhance the experience of commencing students in the higher education sector. Trends in policies, programs and practices ... examines the first year experience literature from 2000-2010. It acknowledges the uniqueness of the Australasian socio-political context and its influence on the interests and output of researchers. The review surveyed almost 400 empirical reports and conceptual discussions produced over the decade that dealt with the stakeholders, institutions and the higher education sector in Australasia. The literature is examined through two theoretical constructs or “lenses”: first, a set of first year curriculum design principles and second, the generational approach to describing the maturation of initiatives. These outcomes and suggested directions for further research provide the challenges and the opportunities for FYE adherents, both scholars and practitioners, to grapple with in the next decade.

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The exhibition consists of a series of 9 large-scale cotton rag prints, printed from digital files, and a sound and picture animation on DVD composed of drawings, sound, analogue and digital photographs, and Super 8 footage. The exhibition represents the artist’s experience of Singapore during her residency. Source imagery was gathered from photographs taken at the Bukit Brown abandoned Chinese Cemetery in Singapore, and Australian native gardens in Parkville Melbourne. Historical sources include re-photographed Singapore 19th and early 20th century postcard images. The works use analogue, hand-drawn and digital imaging, still and animated, to explore the digital interface’s ability to combine mixed media. This practice stems from the digital imaging practice of layering, using various media editing software. The work is innovative in that it stretches the idea of the layer composition in a single image by setting each layer into motion using animation techniques. This creates a multitude of permutations and combinations as the two layers move in different rhythmic patterns. The work also represents an innovative collaboration between the photographic practitioner and a sound composer, Duncan King-Smith, who designed sound for the animation based on concepts of trance, repetition and abstraction. As part of the Art ConneXions program, the work travelled to numerous international venues including: Space 217 Singapore, RMIT Gallery Melbourne, National Museum Jakarta, Vietnam Fine Arts Museum Hanoi, and ifa (Institut fur Auslandsbeziehungen) Gallery in both Stuttgart and Berlin.

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The researcher was invited to photograph athletes in the lead-up to the 2006 Commonwealth Games held in Melbourne. She photographed four indigenous athletes, to produce a series of four large-scale cotton rag prints, 1 meter x 1 meter, printed onto photorag paper from digital files. “My photographic practice can be described as both political and spiritual, in the sense that as an Aboriginal Indigenous artist I take stock of the rationalising effect of the technologies I use, and create work that evokes nature and spirit. My methods often involve re-photographing or digitally re-working landscape photographs and adding historical or cultural icons of significance. Working with Indigenous athletes has been an honour and a pleasure. I admire the athletes’ passion and dedication to their chosen sport, and above all their humility, which seems a trait somewhat in contrast to what it takes to attain the highest levels of achievement. Indigenous athletes are wonderful role models for all Australians, and in making creative work that places their luminary presence with the land, I am aligning sportspeople with a deep sense of nature and spirit.” – Leah King-Smith. These works were commissioned by the National Portrait Gallery for the exhibition FLASH: Australian Athletes in Focus. The exhibition was a significant element in Melbourne2006 Festival, the cultural festival of the Commonwealth Games. The exhibition was prominently reviewed in Portrait: Magazine of Australian and International Portraiture and was subsequently remounted at Old Parliament House, Canberra (15 July to 12 November, 2006). One image was used for the front cover of Art Monthly, (March 2006).

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Dancelines was a body of work commissioned by Bangarra Dance Company and The Arts Centre, Melbourne. The artist was invited to produce a body of work that responded to the dance company's production of 'Boomerang'. The result was a body of photographs that applied the artist's interest in layering as a photographic technique and her interest in indigenous subjectivity and sprituality. The works drew correspondences between Rheannan Port, the subject's, own biography and character and the artist's voluminous archive of iamges of the natural world. The result complemented and formalised the collaborative processes that the artist had previously only explored in the video medium. The work was shown at the George Adams Gallery of the Arts Centre as part of Melbourne 2006 Commonwealth Games Arts Festival. 'Rheannan Port, #1' was selected for the 2006 Archibald Photographic Portrait Prize, at the Art Gallery of New South Wales. The work was reviewed in The Age newspaper.