Sustainable suburbs : the developer’s challenge

As our cities expand, developers are transforming more and more land to create our suburbs of the future. Developers and government bodies have a golden opportunity to design suburbs that are not only great places to live, but also are environmentally sensitive and sustainable. This is a unique opportunity, as significant changes after development are constrained by the configuration of the subdivision, and then by the construction of the dwellings. This paper explores some of these issues by presenting initial findings from the CRCCI, Sustainable Subdivisions Project. The Project examines the drivers and barriers that land developers face when trying to achieve sustainable subdivisions. This paper will review the results from a series of industry interviews and workshops and explore possible ways forward. In addition, the possible effect on the way future land subdivision is managed and planned as a result of recent changes in the energy efficiency provisions of the Building Code of Australia will be explored. This paper highlights problems that both builders and land developers may face through poor subdivision design. Finally an innovative program being driven by a major land developer will be introduced. The program aims to deliver over 400 energy and water efficient homes through a series of compulsory and voluntary schemes that the developer is designing, funding and implementing. This program is the first large-scale development in Australia that demonstrates how developers can help achieve environmentally sensitive and sustainable suburbs of the future.

The PG500 series : novel heparan sulfate mimetics as potent angiogenesis and heparanase inhibitors for cancer therapy

Heparan sulfate mimetics, which we have called the PG500 series, have been developed to target the inhibition of both angiogenesis and heparanase activity. This series extends the technology underpinning PI-88, a mixture of highly sulfated oligosaccharides which reached Phase III clinical development for hepatocellular carcinoma. Advances in the chemistry of the PG500 series provide numerous advantages over PI-88. These new compounds are fully sulfated, single entity oligosaccharides attached to a lipophilic moiety, which have been optimized for drug development. The rational design of these compounds has led to vast improvements in potency compared to PI-88, based on in vitro angiogenesis assays and in vivo tumor models. Based on these and other data, PG545 has been selected as the lead clinical candidate for oncology and is currently undergoing formal preclinical development as a novel treatment for advanced cancer.

A comparative study : regulatory requirements on subdivisions for increasing passive cooling

A major project in the Sustainable Built Assets core area is the Sustainable Sub-divisions – Ventilation Project that is the second stage of a planned series of research projects focusing on sustainable sub-divisions. The initial project, Sustainable Sub-divisions: Energy focused on energy efficiency and examined the link between dwelling energy efficiency and sub-divisional layout. In addition, the potential for on site electricity generation, especially in medium and high-density developments, was also examined. That project recommended that an existing lot-rating methodology be adapted for use in SEQ through the inclusion of sub divisional appropriate ventilation data. Acquiring that data is the object of this project. The Sustainable Sub-divisions; Ventilation Project will produce a series of reports. The first report (Report 2002-077-B-01) summarised the results from an industry workshop and interviews that were conducted to ascertain the current attitudes and methodologies used in contemporary sub-division design in South East Queensland. The second report (Report 2002-077-B-02) described how the project is being delivered as outlined in the Project Agreement. It included the selection of the case study dwellings and monitoring equipment and data management process. This third report (Report 2002-077-B-03) provides an analysis and review of the approaches recommended by leading experts, government bodies and professional organizations throughout Australia that aim to increase the potential for passive cooling and heating at the subdivision stage. This data will inform issues discussed on the development of the enhanced lot-rating methodology in other reports of this series. The final report, due in June 2007, will detail the analysis of data for winter 2006 and summer 2007, leading to the development and delivery of the enhanced lot-rating methodology.

A robust reactive scheduling model for intensive care units

The ICU is an integral part of any hospital and is under great load from patient arrivals as well as resource limitations. Scheduling of patients in the ICU is complicated by the two general types; elective surgery and emergency arrivals. This complicated situation is handled by creating a tentative initial schedule and then reacting to uncertain arrivals as they occur. For most hospitals there is little or no flexibility in the number of beds that are available for use now or in the future. We propose an integer programming model to handle a parallel machine reacting system for scheduled and unscheduled arrivals.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

An historical analysis of the development of thinking in the principal writings of Malcolm Knowles

Malcolm Shepherd Knowles was a key writer and theorist in the field of adult education in the United States. He died in 1997 and left a large legacy of books and journal articles. This thesis traced the development of his thinking over the 46-year period from 1950 to 1995. It examined the 25 works authored, co-authored, edited, reissued and revised by him during that period. The writings were scrutinised using a literature research methodology to expose the theoretical content, and a history of thought lens to identify and account for the development of major ideas. The methodology enabled a gradual unfolding of the history. A broadly-consistent and sequential pattern of thought focusing on the notion of andragogy emerged. The study revealed that after the initial phases of exploratory thinking, Knowles developed a practical-theoretical framework he believed could function as a comprehensive theory of adult learning. As his thinking progressed, his theory developed into a unified framework for human resource development and, later, into a model for the development of self-directed lifelong learners. The study traced the development of Knowles’ thinking through the phases of thought, identified the writings that belonged within each phase and produced a series of diagrammatic representations showing the evolution of his conceptual framework. The production of a history of the development of Knowles’ thought is the major outcome of the study. In addition to plotting the narrative sequence of thought-events, the history helps to explicate the factors and conditions that influenced Knowles’ thinking and to show the interrelationships between ideas. The study should help practitioners in their use and appreciation of Knowles’ works.

An experimental and finite element investigation of the biomechanics of vertebral compression fractures

Osteoporosis is a disease characterized by low bone mass and micro-architectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fracture. Osteoporosis affects over 200 million people worldwide, with an estimated 1.5 million fractures annually in the United States alone, and with attendant costs exceeding $10 billion dollars per annum. Osteoporosis reduces bone density through a series of structural changes to the honeycomb-like trabecular bone structure (micro-structure). The reduced bone density, coupled with the microstructural changes, results in significant loss of bone strength and increased fracture risk. Vertebral compression fractures are the most common type of osteoporotic fracture and are associated with pain, increased thoracic curvature, reduced mobility, and difficulty with self care. Surgical interventions, such as kyphoplasty or vertebroplasty, are used to treat osteoporotic vertebral fractures by restoring vertebral stability and alleviating pain. These minimally invasive procedures involve injecting bone cement into the fractured vertebrae. The techniques are still relatively new and while initial results are promising, with the procedures relieving pain in 70-95% of cases, medium-term investigations are now indicating an increased risk of adjacent level fracture following the procedure. With the aging population, understanding and treatment of osteoporosis is an increasingly important public health issue in developed Western countries. The aim of this study was to investigate the biomechanics of spinal osteoporosis and osteoporotic vertebral compression fractures by developing multi-scale computational, Finite Element (FE) models of both healthy and osteoporotic vertebral bodies. The multi-scale approach included the overall vertebral body anatomy, as well as a detailed representation of the internal trabecular microstructure. This novel, multi-scale approach overcame limitations of previous investigations by allowing simultaneous investigation of the mechanics of the trabecular micro-structure as well as overall vertebral body mechanics. The models were used to simulate the progression of osteoporosis, the effect of different loading conditions on vertebral strength and stiffness, and the effects of vertebroplasty on vertebral and trabecular mechanics. The model development process began with the development of an individual trabecular strut model using 3D beam elements, which was used as the building block for lattice-type, structural trabecular bone models, which were in turn incorporated into the vertebral body models. At each stage of model development, model predictions were compared to analytical solutions and in-vitro data from existing literature. The incremental process provided confidence in the predictions of each model before incorporation into the overall vertebral body model. The trabecular bone model, vertebral body model and vertebroplasty models were validated against in-vitro data from a series of compression tests performed using human cadaveric vertebral bodies. Firstly, trabecular bone samples were acquired and morphological parameters for each sample were measured using high resolution micro-computed tomography (CT). Apparent mechanical properties for each sample were then determined using uni-axial compression tests. Bone tissue properties were inversely determined using voxel-based FE models based on the micro-CT data. Specimen specific trabecular bone models were developed and the predicted apparent stiffness and strength were compared to the experimentally measured apparent stiffness and strength of the corresponding specimen. Following the trabecular specimen tests, a series of 12 whole cadaveric vertebrae were then divided into treated and non-treated groups and vertebroplasty performed on the specimens of the treated group. The vertebrae in both groups underwent clinical-CT scanning and destructive uniaxial compression testing. Specimen specific FE vertebral body models were developed and the predicted mechanical response compared to the experimentally measured responses. The validation process demonstrated that the multi-scale FE models comprising a lattice network of beam elements were able to accurately capture the failure mechanics of trabecular bone; and a trabecular core represented with beam elements enclosed in a layer of shell elements to represent the cortical shell was able to adequately represent the failure mechanics of intact vertebral bodies with varying degrees of osteoporosis. Following model development and validation, the models were used to investigate the effects of progressive osteoporosis on vertebral body mechanics and trabecular bone mechanics. These simulations showed that overall failure of the osteoporotic vertebral body is initiated by failure of the trabecular core, and the failure mechanism of the trabeculae varies with the progression of osteoporosis; from tissue yield in healthy trabecular bone, to failure due to instability (buckling) in osteoporotic bone with its thinner trabecular struts. The mechanical response of the vertebral body under load is highly dependent on the ability of the endplates to deform to transmit the load to the underlying trabecular bone. The ability of the endplate to evenly transfer the load through the core diminishes with osteoporosis. Investigation into the effect of different loading conditions on the vertebral body found that, because the trabecular bone structural changes which occur in osteoporosis result in a structure that is highly aligned with the loading direction, the vertebral body is consequently less able to withstand non-uniform loading states such as occurs in forward flexion. Changes in vertebral body loading due to disc degeneration were simulated, but proved to have little effect on osteoporotic vertebra mechanics. Conversely, differences in vertebral body loading between simulated invivo (uniform endplate pressure) and in-vitro conditions (where the vertebral endplates are rigidly cemented) had a dramatic effect on the predicted vertebral mechanics. This investigation suggested that in-vitro loading using bone cement potting of both endplates has major limitations in its ability to represent vertebral body mechanics in-vivo. And lastly, FE investigation into the biomechanical effect of vertebroplasty was performed. The results of this investigation demonstrated that the effect of vertebroplasty on overall vertebra mechanics is strongly governed by the cement distribution achieved within the trabecular core. In agreement with a recent study, the models predicted that vertebroplasty cement distributions which do not form one continuous mass which contacts both endplates have little effect on vertebral body stiffness or strength. In summary, this work presents the development of a novel, multi-scale Finite Element model of the osteoporotic vertebral body, which provides a powerful new tool for investigating the mechanics of osteoporotic vertebral compression fractures at the trabecular bone micro-structural level, and at the vertebral body level.

Characterisation of soils with the use of instrumental techniques : a multivariate forensic study

The value of soil evidence in the forensic discipline is well known. However, it would be advantageous if an in-situ method was available that could record responses from tyre or shoe impressions in ground soil at the crime scene. The development of optical fibres and emerging portable NIR instruments has unveiled a potential methodology which could permit such a proposal. The NIR spectral region contains rich chemical information in the form of overtone and combination bands of the fundamental infrared absorptions and low-energy electronic transitions. This region has in the past, been perceived as being too complex for interpretation and consequently was scarcely utilized. The application of NIR in the forensic discipline is virtually non-existent creating a vacancy for research in this area. NIR spectroscopy has great potential in the forensic discipline as it is simple, nondestructive and capable of rapidly providing information relating to chemical composition. The objective of this study is to investigate the ability of NIR spectroscopy combined with Chemometrics to discriminate between individual soils. A further objective is to apply the NIR process to a simulated forensic scenario where soil transfer occurs. NIR spectra were recorded from twenty-seven soils sampled from the Logan region in South-East Queensland, Australia. A series of three high quartz soils were mixed with three different kaolinites in varying ratios and NIR spectra collected. Spectra were also collected from six soils as the temperature of the soils was ramped from room temperature up to 6000C. Finally, a forensic scenario was simulated where the transferral of ground soil to shoe soles was investigated. Chemometrics methods such as the commonly known Principal Component Analysis (PCA), the less well known fuzzy clustering (FC) and ranking by means of multicriteria decision making (MCDM) methodology were employed to interpret the spectral results. All soils were characterised using Inductively Coupled Plasma Optical Emission Spectroscopy and X-Ray Diffractometry. Results were promising revealing NIR combined with Chemometrics is capable of discriminating between the various soils. Peak assignments were established by comparing the spectra of known minerals with the spectra collected from the soil samples. The temperature dependent NIR analysis confirmed the assignments of the absorptions due to adsorbed and molecular bound water. The relative intensities of the identified NIR absorptions reflected the quantitative XRD and ICP characterisation results. PCA and FC analysis of the raw soils in the initial NIR investigation revealed that the soils were primarily distinguished on the basis of their relative quartz and kaolinte contents, and to a lesser extent on the horizon from which they originated. Furthermore, PCA could distinguish between the three kaolinites used in the study, suggesting that the NIR spectral region was sensitive enough to contain information describing variation within kaolinite itself. The forensic scenario simulation PCA successfully discriminated between the ‘Backyard Soil’ and ‘Melcann® Sand’, as well as the two sampling methods employed. Further PCA exploration revealed that it was possible to distinguish between the various shoes used in the simulation. In addition, it was possible to establish association between specific sampling sites on the shoe with the corresponding site remaining in the impression. The forensic application revealed some limitations of the process relating to moisture content and homogeneity of the soil. These limitations can both be overcome by simple sampling practices and maintaining the original integrity of the soil. The results from the forensic scenario simulation proved that the concept shows great promise in the forensic discipline.

Evaluating Specification Tests for Markov-Switching Time-Series Models

We evaluate the performance of several specification tests for Markov regime-switching time-series models. We consider the Lagrange multiplier (LM) and dynamic specification tests of Hamilton (1996) and Ljung–Box tests based on both the generalized residual and a standard-normal residual constructed using the Rosenblatt transformation. The size and power of the tests are studied using Monte Carlo experiments. We find that the LM tests have the best size and power properties. The Ljung–Box tests exhibit slight size distortions, though tests based on the Rosenblatt transformation perform better than the generalized residual-based tests. The tests exhibit impressive power to detect both autocorrelation and autoregressive conditional heteroscedasticity (ARCH). The tests are illustrated with a Markov-switching generalized ARCH (GARCH) model fitted to the US dollar–British pound exchange rate, with the finding that both autocorrelation and GARCH effects are needed to adequately fit the data.

Nutrients build-up and wash-off processes in urban land uses

This thesis describes outcomes of a research study conducted to investigate the nutrient build-up and wash-off processes on urban impervious surfaces. The data needed for the study was generated through a series of field investigations and laboratory test procedures. The study sites were selected in urbanised catchments to represent typical characteristics of residential, industrial and commercial land uses. The build-up and wash-off samples were collected from road surfaces in the selected study sites. A specially designed vacuum collection system and a rainfall simulator were used for sample collection. According to the data analysis, the solids build-up on road surfaces was significantly finer with more than 80% of the particles below 150 ìm for all the land uses. Nutrients were mostly associated with the particle size range below 150 ìm in both build-up and wash-off samples irrespective of type of land use. Therefore, the finer fraction of solids was the most important for the nutrient build-up and particulate nutrient wash-off processes. Consequently, the design of stormwater quality mitigation measures should target particles less than 150 ìm for the removal of nutrients irrespective of type of land use. Total kjeldahl nitrogen (TKN) was the most dominant form of nitrogen species in build-up on road surfaces. Phosphorus build-up on road surfaces was mainly in inorganic form and phosphate (PO4 3-) was the most dominant form. The nutrient wash-off process was found to be dependent on rainfall intensity and duration. Concentration of both total nitrogen and phosphorus was higher at the beginning of the rain event and decreased with the increase in rainfall duration. Consequently, in the design of stormwater quality mitigation strategies for nutrients removal, it is important to target the initial period of rain events. The variability of wash-off of nitrogen with rainfall intensity was significantly different to phosphorus wash-off. The concentration of nitrogen was higher in the wash-off for low intensity rain events compared to the wash-off for high intensity rain events. On the other hand, the concentration of phosphorus in the wash-off was high for high intensity rain events compared to low intensity rain events. Consequently, the nitrogen washoff can be defined as a source limiting process and phosphorus wash-off as a transport limiting process. This highlights the importance of taking into consideration the wash-off of low intensity rain events in the design of stormwater quality mitigation strategies targeting the nitrogen removal. All the nitrogen species in wash-off are primarily in dissolved form whereas phosphorus is in particulate form. The differences in the nitrogen and phosphorus wash-off processes is principally due to the degree of solubility, attachment to particulates, composition of total nitrogen and total phosphorus and the degree of adherence of the solids particles to the surface to which nutrients are attached. The particulate nitrogen available for wash-off is removed readily as these are mobilised as free solids particles on the surface. Phosphorus is washed-off mostly with the solids particles which are strongly adhered to the surface or as the fixed solids load. Investigation of the nitrogen wash-off process using bulk wash-off samples was in close agreement with the investigation of dissolved fraction of wash-off solids. This was primarily due to the predominant nature of dissolved nitrogen. However, the investigation of the processes which underpin phosphorus wash-off using bulk washoff samples could lead to loss of information. This is due to the composition of total phosphorus in wash-off solids and the inherent variability of the wash-off process for the different particle size ranges. This variability should preferably be taken into consideration as phosphorus wash-off is predominantly in particulate form. Therefore, care needs to be taken in the investigation of the phosphorus wash-off process using bulk wash-off samples to ensure that there is no loss of information and hence result in misleading outcomes. The investigation of different particle size ranges of wash-off solids is preferable in the interest of designing effective stormwater quality management strategies targeting phosphorus removal.

Hybrid cascade converter topology with series connected symmetrical and asymmetrical diode-clamped H-Bridge cells

A novel H-bridge multilevel PWM converter topology based on a series connection of a high voltage (HV) diode-clamped inverter and a low voltage (LV) conventional inverter is proposed. A DC link voltage arrangement for the new hybrid and asymmetric solution is presented to have a maximum number of output voltage levels by preserving the adjacent switching vectors between voltage levels. Hence, a fifteen-level hybrid converter can be attained with a minimum number of power components. A comparative study has been carried out to present high performance of the proposed configuration to approach a very low THD of voltage and current, which leads to the possible elimination of output filter. Regarding the proposed configuration, a new cascade inverter is verified by cascading an asymmetrical diode-clamped inverter, in which nineteen levels can be synthesized in output voltage with the same number of components. To balance the DC link capacitor voltages for the maximum output voltage resolution as well as synthesise asymmetrical DC link combination, a new Multi-output Boost (MOB) converter is utilised at the DC link voltage of a seven-level H-bridge diode-clamped inverter. Simulation and hardware results based on different modulations are presented to confirm the validity of the proposed approach to achieve a high quality output voltage.

Towards an intelligent learning system for the natural born cyborg

We propose to design a Custom Learning System that responds to the unique needs and potentials of individual students, regardless of their location, abilities, attitudes, and circumstances. This project is intentionally provocative and future-looking but it is not unrealistic or unfeasible. We propose that by combining complex learning databases with a learner’s personal data, we could provide all students with a personal, customizable, and flexible education. This paper presents the initial research undertaken for this project of which the main challenges were to broadly map the complex web of data available, to identify what logic models are required to make the data meaningful for learning, and to translate this knowledge into simple and easy-to-use interfaces. The ultimate outcome of this research will be a series of candidate user interfaces and a broad system logic model for a new smart system for personalized learning. This project is student-centered, not techno-centric, aiming to deliver innovative solutions for learners and schools. It is deliberately future-looking, allowing us to ask questions that take us beyond the limitations of today to motivate new demands on technology.

The relationship between deformity correction and clinical outcomes after thoracoscopic scoliosis surgery : a prospective series of 100 patients

The relationship between deformity correction and self-reported patient satisfaction after thoracoscopic anterior scoliosis surgery is unknown. Scoliosis Research Society questionnaire scores, radiographic outcomes, and rib hump correction were prospectively assessed for a group of 100 patients pre-operatively and at two years after surgery. Patients with lower post-op major Cobb angles report significantly higher SRS scores than patients with higher post-op Cobb angles.

Control issues for velocity sourced Series Elastic Actuators

The Series Elasic Actuator has been proposed as a method for providing safe force or torque based acutation for robots that interact with humans. In this paper we look at some outstanding issues in the implementation and control of Series Elastic Actuators. The study addresses issues in making the Series Elastic Actuator respond effectively in the presence of physical difficulties such as restriction, using a computation efficient controller. The improvement over previous implementations is achieved by treating the motor as a velocity source to the elastic element, rather than as a torque source.