The conceptualisation, sensitivity and measurement of holding costs and other selected elements impacting housing affordability (Literature review and research methodology for confirmation of PhD candidature)

It is widely held that strong relationships exist between housing, economic status, and well being. This is exemplified by widespread housing stock surpluses in many countries which threaten to destabilise numerous aspects related to individuals and community. However, the position of housing demand and supply is not consistent. The Australian position provides a distinct contrast whereby seemingly inexorable housing demand generally remains a critical issue affecting the socio-economic landscape. Underpinned by high levels of immigration, and further buoyed by sustained historically low interest rates, increasing income levels, and increased government assistance for first home buyers, this strong housing demand ensures elements related to housing affordability continue to gain prominence. A significant, but less visible factor impacting housing affordability – particularly new housing development – relates to holding costs. These costs are in many ways “hidden” and cannot always be easily identified. Although it is only one contributor, the nature and extent of its impact requires elucidation. In its simplest form, it commences with a calculation of the interest or opportunity cost of land holding. However, there is significantly more complexity for major new developments - particularly greenfield property development. Preliminary analysis conducted by the author suggests that even small shifts in primary factors impacting holding costs can appreciably affect housing affordability – and notably, to a greater extent than commonly held. Even so, their importance and perceived high level impact can be gauged from the unprecedented level of attention policy makers have given them over recent years. This may be evidenced by the embedding of specific strategies to address burgeoning holding costs (and particularly those cost savings associated with streamlining regulatory assessment) within statutory instruments such as the Queensland Housing Affordability Strategy, and the South East Queensland Regional Plan. However, several key issues require investigation. Firstly, the computation and methodology behind the calculation of holding costs varies widely. In fact, it is not only variable, but in some instances completely ignored. Secondly, some ambiguity exists in terms of the inclusion of various elements of holding costs, thereby affecting the assessment of their relative contribution. Perhaps this may in part be explained by their nature: such costs are not always immediately apparent. Some forms of holding costs are not as visible as the more tangible cost items associated with greenfield development such as regulatory fees, government taxes, acquisition costs, selling fees, commissions and others. Holding costs are also more difficult to evaluate since for the most part they must be ultimately assessed over time in an ever-changing environment, based on their strong relationship with opportunity cost which is in turn dependant, inter alia, upon prevailing inflation and / or interest rates. By extending research in the general area of housing affordability, this thesis seeks to provide a more detailed investigation of those elements related to holding costs, and in so doing determine the size of their impact specifically on the end user. This will involve the development of soundly based economic and econometric models which seek to clarify the componentry impacts of holding costs. Ultimately, there are significant policy implications in relation to the framework used in Australian jurisdictions that promote, retain, or otherwise maximise, the opportunities for affordable housing.

Violence, Spatiality and other Rurals

Occidentalism, which treats the other as the same, can be detected in both the criminological and rural sociological treatment of violence in the sociospatial sites of rural countrysides. Criminology tends to mistakenly assume that violence in the modern world is primarily an urban phenomenon (Baldwin & Bottoms, 1976, p. 1; Braithwaite, 1989, p. 47). If violence in rural settings is encountered it tends to be treated as a smaller scale version of the urban problem, or the importation of an otherwise urban problem - as the corrupting influence of the gesellschaft within the gemeinschaft. Within much rural sociology violence is rendered invisible by the assumption that rural communities conform to the idealised conception of the typical gemeinschaft society, small-scale traditional societies based on strong cohesiveness, intimacy and organic forms of solidarity. What these bonds conceal, rather than reveal - violence within the family - remains invisible to the public gaze. The visibility of violence within Aboriginal families and communities presents a major exception to the spatially ordered social relations which render so much white family violence hidden. The need to take into account the complexity and diversity of these sociospatial relations is concretely highlighted in our research which has taken us out of the urban context and confronted us not only with the phenomenon of the violence of other rurals, but also with fundamentally competing claims on, and conceptions of, space and place in the context of a racially divided Australian interior. This article represents the second installment of conceptual reflections on this research, with the first having been published in this journal in 1998.

Vision-based detection and tracking of aerial targets for UAV collision avoidance

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved (as opposed to radar). This paper describes the development and evaluation of a vision-based collision detection algorithm suitable for fixed-wing aerial robotics. The system was evaluated using highly realistic vision data of the moments leading up to a collision. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We make use of the enormous potential of graphic processing units to achieve processing rates of 30Hz (for images of size 1024-by- 768). Currently, integration in the final platform is under way.

Managing the winds of change

Environmental impacts caused during Australia's comparatively recent settlement by Europeans are evident. Governments (both Commonwealth and States) have been largely responsible for requiring landholders – through leasehold development conditions and taxation concessions – to conduct clearing that is now perceived as damage. Most governments are now demanding resource protection. There is a measure of bewilderment (if not resentment) among landholders because of this change. The more populous States, where most overall damage has been done (i.e. Victoria and New South Wales), provide most support for attempts to stop development in other regions where there has been less damage. Queensland, i.e. the north-eastern quarter of the continent, has been relatively slow to develop. It also holds the largest and most diverse natural environments. Tree clearing is an unavoidable element of land development, whether to access and enhance native grasses for livestock or to allow for urban developments (with exotic tree plantings). The consequences in terms of regulations are particularly complex because of the dynamic nature of vegetation. The regulatory terms used in current legislation – such as 'Endangered' and 'Of concern' – depend on legally-defined, static baselines. Regrowth and fire damage are two obvious causes of change. A less obvious aspect is succession, where ecosystems change naturally over long timeframes. In the recent past, the Queensland Government encouraged extensive tree-clearing e.g. through the State Brigalow Development Scheme (mostly 1962 to 1975) which resulted in the removal of some 97% of the wide-ranging mature forests of Acacia harpophylla. At the same time, this government controls National Parks and other reservations (occupying some 4% of the State's 1.7 million km2 area) and also holds major World Heritage Areas (such as the Great Barrier Reef and the Wet Tropics Rainforest) promulgated under Commonwealth legislation. This is a highly prescriptive approach, where the community is directed on the one hand to develop (largely through lease conditions) and on the other to avoid development (largely by unusable reserves). Another approach to development and conservation is still possible in Queensland. For this to occur, however, a more workable and equitable solution than has been employed to date is needed, especially for the remote lands of this State. This must involve resident landholders, who have the capacity (through local knowledge, infrastructure and daily presence) to undertake most costeffectively sustainable land-use management (with suitable attention to ecosystems requiring special conservation effort), that is, provided they have the necessary direction, encouragement and incentive to do so.

Incorporating uncertainty in environmental models informed by imagery

In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.

Life in the 'real world': a profile of Queensland University of Technology Library and Information Science graduates.

A graduate destination survey can provide a snap shot in time of a graduate’s career progression and outcome. This paper will present the results of a Queensland University of Technology study exploring the employment outcomes of students who had completed a library and information science course from the Faculty of Information Technology between 2000 and 2008. Seventy-four graduates completed an online questionnaire administered in July 2009. The study found that 90% of the graduates surveyed were working and living in Queensland, with over three quarters living and working in Brisbane. Nearly 70% were working full-time, while only 1.4% indicating that they were unemployed and looking for work. Over 80% of the graduates identified themselves as working in “librarianship”. This study is the first step in understanding the progression and destination of QUT’s library and information science graduates. It is recommended that this survey becomes an ongoing initiative so that the results can be analysed and compared over time.

Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal species.

Robot building for preschoolers

This paper describes Electronic Blocks, a new robot construction element designed to allow children as young as age three to build and program robotic structures. The Electronic Blocks encapsulate input, output and logic concepts in tangible elements that young children can use to create a wide variety of physical agents. The children are able to determine the behavior of these agents by the choice of blocks and the manner in which they are connected. The Electronic Blocks allow children without any knowledge of mechanical design or computer programming to create and control physically embodied robots. They facilitate the development of technological capability by enabling children to design, construct, explore and evaluate dynamic robotics systems. A study of four and five year-old children using the Electronic Blocks has demonstrated that the interface is well suited to young children. The complexity of the implementation is hidden from the children, leaving the children free to autonomously explore the functionality of the blocks. As a consequence, children are free to move their focus beyond the technology. Instead they are free to focus on the construction process, and to work on goals related to the creation of robotic behaviors and interactions. As a resource for robot building, the blocks have proved to be effective in encouraging children to create robot structures, allowing children to design and program robot behaviors.

Towards the implementation of vision-based UAS sense-and-avoid

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved. This paper describes the development of detection algorithms and the evaluation of a real-time flight ready hardware implementation of a vision-based collision detection system suitable for fixed-wing small/medium size UAS. In particular, this paper demonstrates the use of Hidden Markov filter to track and estimate the elevation (β) and bearing (α) of the target, compares several candidate graphic processing hardware choices, and proposes an image based visual servoing approach to achieve collision avoidance

Dynamic visual features for audio-visual speaker verification

The cascading appearance-based (CAB) feature extraction technique has established itself as the state-of-the-art in extracting dynamic visual speech features for speech recognition. In this paper, we will focus on investigating the effectiveness of this technique for the related speaker verification application. By investigating the speaker verification ability of each stage of the cascade we will demonstrate that the same steps taken to reduce static speaker and environmental information for the visual speech recognition application also provide similar improvements for visual speaker recognition. A further study is conducted comparing synchronous HMM (SHMM) based fusion of CAB visual features and traditional perceptual linear predictive (PLP) acoustic features to show that higher complexity inherit in the SHMM approach does not appear to provide any improvement in the final audio-visual speaker verification system over simpler utterance level score fusion.

Forecasting negative effects of monotony and sensation seeking on performance during a vigilance task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create hypovigilance and impair performance towards critical events. Identifying such impairment in monotonous conditions has been a major subject of research, but no research to date has attempted to predict it in real-time. This pilot study aims to show that performance decrements due to monotonous tasks can be predicted through mathematical modelling taking into account sensation seeking levels. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants‟ performance. The framework for prediction developed on this task could be extended to a monotonous driving task. A Hidden Markov Model (HMM) is proposed to predict participants‟ lapses in alertness. Driver‟s vigilance evolution is modelled as a hidden state and is correlated to a surrogate measure: the participant‟s reactions time. This experiment shows that the monotony of the task can lead to an important decline in performance in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

Anthony Browne and the cultural capital of classic fairy tales

Prolific British author/illustrator Anthony Browne both participates in the classic fairy-tale tradition and appropriates its cultural capital, ultimately undertaking a process of self-canonisation alongside the dissemination of fairy tales. In reading Browne’s Hansel and Gretel (1981), The Tunnel (1989) and Into the Forest (2004), a trajectory emerges that moves from broadly intertextual to more exclusively self-referential modes of representation which reward readers of “Anthony Browne”, rather than readers of “fairy tales”. All three books depict ‘babes in the woods’ stories wherein child characters must negotiate some form of threat outside the home in order to return home safely. Thus, they represent childhood agency. However, these visions of agency are ultimately subordinated to logics of capital, which means that child readers of Browne’s fairy-tale books are overtly invited to identify with children who act, but are interpellated as privileged if they ‘know’. Bourdieu’s model of ‘cultural capital’ offers a lens for considering Browne’s production of ‘value’ for his own works within a broader cultural landscape which privileges literary fairy tales as a register of juvenile cultural competency. If cultural capital can be formulated most simply as the symbolic exchange value of approved modes of knowing and being, it is clearly helpful when trying to unpack logics of meaning within heavily intertextual or citational texts. It is also helpful thinking about what kinds of stories we as a culture choose to disseminate, choose to privilege, or choose to suppress. Zipes notes of fairy tales that, “the genre itself becomes a kind of institute that is involved in the socialization and acculturation of readers” (22). He elaborates that, “We initiate readers and expect them to learn the fairy-tale code as part of our responsibility in the civilizing process” (Zipes 29), so it is little wonder that Tatar describes fairy tales as “a vital part of our cultural capital” (xix). Although Browne is clearly interested in literary fairy tales, the most obvious strategies of self-canonisation take place in Browne’s work not in words but in pictures: hidden in plain sight, as illustration becomes self-reflexive citation.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Talking the talk : oracy demands in first year university assessment tasks

With more constructivist approaches to learning in higher education and more value on teamwork skills, students’ oracy (speaking and listening) features more prominently in curriculum, pedagogy and assessment. The paper reports on a study of two first-year Australian university courses in disciplines with explicit industry orientations and high proportions of international students. Drawing on classroom observations and interviews with the lecturers, this paper investigates their pedagogical designs on oracy and the oracy demands of their assessment tasks. The study found that talk-based assessment tasks (a group project and a group oral presentation) featured in both courses but the two courses treated students’ oracy differently: as product or process. The contrast between the two assessment designs explicates issues around EAL student needs, authentic links to industry, the provenance of criteria used to assess performance, perceptions about the relevance of talk and the ‘hidden assessment’ of oracy.