Quantifying the state of populations and effects of disturbances at large spatio-temporal scales: The case of coral populations in the great barrier reef

This project was a step forward in applying statistical methods and models to provide new insights for more informed decision-making at large spatial scales. The model has been designed to address complicated effects of ecological processes that govern the state of populations and uncertainties inherent in large spatio-temporal datasets. Specifically, the thesis contributes to better understanding and management of the Great Barrier Reef.

Online hidden Markov model parameter estimation and minimax robust quickest change detection in uncertain stochastic processes

Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Time, place and space – student group collaboration using Google Drive

Virtual working environments are intrinsic to the contemporary workplace and collaborative skills are a vital graduate capability. To develop students’ collaborative skills, first year medical laboratory science students undertake a group poster project, based on a blended learning model. Learning is scaffolded in lectures, workshops in collaborative learning spaces, practitioner mentoring sessions, and online resources. Google Drive provides an online collaborative space for students to realise tangible outcomes from this learning. A Google Drive document is created for each group and shared with members. In this space, students assign tasks and plan workflow, share research, progressively develop poster content, reflect and comment on peer contributions and use the messaging functions to ‘talk’ to group members. This provides a readily accessible, transparent record of group work, crucial in peer assessment, and a communication channel for group members and the lecturer, who can support groups if required. This knowledge creation space also augments productivity and effectiveness of face-to-face collaboration. As members are randomly allocated to groups and are often of diverse backgrounds and unknown to each other, resilience is built as students navigate the uncertainties and complexities of group dynamics, learning to focus on the goal of the team task as they constructively and professionally engage in team dialogue. Students are responsible and accountable for individual and group work. The use of Google Drive was evaluated in a survey including Likert scale and open ended qualitative questions. Statistical analysis was carried out. Results show students (79%) valued the inclusion of online space in collaborative work and highly appreciated (78%) the flexibility provided by Google Drive, while recognising the need for improved notification functionality. Teaching staff recognised the advantages in monitoring and moderating collaborative group work, and the transformational progression in student collaborative as well as technological skill acquisition, including professional dialogue.

A Model to Estimate the Population Contributing to the Wastewater Using Samples Collected on Census Day

An important uncertainty when estimating per capita consumption of, for example, illicit drugs by means of wastewater analysis (sometimes referred to as “sewage epidemiology”) relates to the size and variability of the de facto population in the catchment of interest. In the absence of a day-specific direct population count any indirect surrogate model to estimate population size lacks a standard to assess associated uncertainties. Therefore, the objective of this study was to collect wastewater samples at a unique opportunity, that is, on a census day, as a basis for a model to estimate the number of people contributing to a given wastewater sample. Mass loads for a wide range of pharmaceuticals and personal care products were quantified in influents of ten sewage treatment plants (STP) serving populations ranging from approximately 3500 to 500 000 people. Separate linear models for population size were estimated with the mass loads of the different chemical as the explanatory variable: 14 chemicals showed good, linear relationships, with highest correlations for acesulfame and gabapentin. De facto population was then estimated through Bayesian inference, by updating the population size provided by STP staff (prior knowledge) with measured chemical mass loads. Cross validation showed that large populations can be estimated fairly accurately with a few chemical mass loads quantified from 24-h composite samples. In contrast, the prior knowledge for small population sizes cannot be improved substantially despite the information of multiple chemical mass loads. In the future, observations other than chemical mass loads may improve this deficit, since Bayesian inference allows including any kind of information relating to population size.

Could wastewater analysis be a useful tool for China? — A review

Analysing wastewater samples is an innovative approach that overcomes many limitations of traditional surveys to identify and measure a range of chemicals that were consumed by or exposed to people living in a sewer catchment area. First conceptualised in 2001, much progress has been made to make wastewater analysis (WWA) a reliable and robust tool for measuring chemical consumption and/or exposure. At the moment, the most popular application of WWA, sometimes referred as sewage epidemiology, is to monitor the consumption of illicit drugs in communities around the globe, including China. The approach has been largely adopted by law enforcement agencies as a device to monitor the temporal and geographical patterns of drug consumption. In the future, the methodology can be extended to other chemicals including biomarkers of population health (e.g. environmental or oxidative stress biomarkers, lifestyle indicators or medications that are taken by different demographic groups) and pollutants that people are exposed to (e.g. polycyclic aromatic hydrocarbons, perfluorinated chemicals, and toxic pesticides). The extension of WWA to a huge range of chemicals may give rise to a field called sewage chemical-information mining (SCIM) with unexplored potentials. China has many densely populated cities with thousands of sewage treatment plants which are favourable for applying WWA/SCIM in order to help relevant authorities gather information about illicit drug consumption and population health status. However, there are some prerequisites and uncertainties of the methodology that should be addressed for SCIM to reach its full potential in China.

Collaborative learning from distributed places and spaces: Exploring the use of virtual collaborative tools for local and global student teamwork projects

Educating responsive graduates. Graduate competencies include reliability, communication skills and ability to work in teams. Students using Collaborative technologies adapt to a new working environment, working in teams and using collaborative technologies for learning. Collaborative Technologies were used not simply for delivery of learning but innovatively to supplement and enrich research-based learning, providing a space for active engagement and interaction with resources and team. This promotes the development of responsive ‘intellectual producers’, able to effectively communicate, collaborate and negotiate in complex work environments. Exploiting technologies. Students use ‘new’ technologies to work collaboratively, allowing them to experience the reality of distributed workplaces incorporating both flexibility and ‘real’ time responsiveness. Students are responsible and accountable for individual and group work contributions in a highly transparent and readily accessible workspace. This experience provides a model of an effective learning tool. Navigating uncertainty and complexity. Collaborative technologies allows students to develop critical thinking and reflective skills as they develop a group product. In this forum students build resilience by taking ownership and managing group work, and navigating the uncertainties and complexities of group dynamics as they constructively and professionally engage in team dialogue and learn to focus on the goal of the team task.

Governance and regional planning outcomes: Using governance indicators to support a policy implementation approach

Regional planning faces numerous decision making uncertainties related to the complex interdependencies between urban and regional centres. Questions about how to achieve sustainable planning solutions across regions are a key uncertainty and relate to a lack of information about the actual achievement of outcomes as proposed by the objectives of a plan. Regional plan implementation and its impact on environmental, social and economic outcomes have been little explored within Australian urban and regional planning research. Despite a desire to improve the conditions across Australian regions, ambiguity persists regarding the results of regional planning efforts. Of the variables affecting regional planning, scholars argue that governance has a significant impact on achieving outcomes (see Pahl-Wostl 2009). In order to better analyse the impact of governance, we propose a set of governance indicators to examine decisions across regional planning institutions and apply this to governance models across Queensland’s regions. We contend that these governance indicators can support a more rigorous assessment of the impacts of governance models on plan implementation and outcomes. We propose that this is a way to better understand the relationship between planning and outcomes across urban and regional areas.

Study of reproducibility of human arterial plaque reconstruction and its effects on stress analysis based on multispectral in vivo magnetic resonance imaging

Purpose: To quantify the uncertainties of carotid plaque morphology reconstruction based on patient-specific multispectral in vivo magnetic resonance imaging (MRI) and their impacts on the plaque stress analysis. Materials and Methods: In this study, three independent investigators were invited to reconstruct the carotid bifurcation with plaque based on MR images from two subjects to study the geometry reconstruction reproducibility. Finite element stress analyses were performed on the carotid bifurcations, as well as the models with artificially modified plaque geometries to mimic the image segmentation uncertainties, to study the impacts of the uncertainties to the stress prediction. Results: Plaque reconstruction reproducibility was generally high in the study. The uncertainties among interobservers are around one or the subpixel level. It also shows that the predicted stress is relatively less sensitive to the arterial wall segmentation uncertainties, and more affected by the accuracy of lipid region definition. For a model with lipid core region artificially increased by adding one pixel on the lipid region boundary, it will significantly increase the maximum Von Mises Stress in fibrous cap (>100%) compared with the baseline model for all subjects. Conclusion: The current in vivo MRI in the carotid plaque could provide useful and reliable information for plaque morphology. The accuracy of stress analysis based on plaque geometry is subject to MRI quality. The improved resolution/quality in plaque imaging with newly developed MRI protocols would generate more realistic stress predictions.

The Learning Component of Dynamic Allocation Indices

For a multiarmed bandit problem with exponential discounting the optimal allocation rule is defined by a dynamic allocation index defined for each arm on its space. The index for an arm is equal to the expected immediate reward from the arm, with an upward adjustment reflecting any uncertainty about the prospects of obtaining rewards from the arm, and the possibilities of resolving those uncertainties by selecting that arm. Thus the learning component of the index is defined to be the difference between the index and the expected immediate reward. For two arms with the same expected immediate reward the learning component should be larger for the arm for which the reward rate is more uncertain. This is shown to be true for arms based on independent samples from a fixed distribution with an unknown parameter in the cases of Bernoulli and normal distributions, and similar results are obtained in other cases.

Hybrid game strategies for MO problems in aerospace design

Game strategies have been developed in past decades and used in the field of economics, engineering, computer science and biology due to their efficiency in solving design optimisation problems. In addition, research on Multi-Objective (MO) and Multidisciplinary Design Optimisation (MDO) has focused on developing robust and efficient optimisation method to produce quality solutions with less computational time. In this paper, a new optimisation method Hybrid Game Strategy for MO problems is introduced and compared to CMA-ES based optimisation approach. Numerical results obtained from both optimisation methods are compared in terms of computational expense and model quality. The benefits of using Game-strategies are demonstrated.

Country of Origin and Internet Publication: Applying the Berne Convention in the Digital Age

Historically, determining the country of origin of a published work presented few challenges, because works were generally published physically – whether in print or otherwise – in a distinct location or few locations. However, publishing opportunities presented by new technologies mean that we now live in a world of simultaneous publication – works that are first published online are published simultaneously to every country in world in which there is Internet connectivity. While this is certainly advantageous for the dissemination and impact of information and creative works, it creates potential complications under the Berne Convention for the Protection of Literary and Artistic Works (“Berne Convention”), an international intellectual property agreement to which most countries in the world now subscribe. Under the Berne Convention’s national treatment provisions, rights accorded to foreign copyright works may not be subject to any formality, such as registration requirements (although member countries are free to impose formalities in relation to domestic copyright works). In Kernel Records Oy v. Timothy Mosley p/k/a Timbaland, et al. however, the Florida Southern District Court of the United States ruled that first publication of a work on the Internet via an Australian website constituted “simultaneous publication all over the world,” and therefore rendered the work a “United States work” under the definition in section 101 of the U.S. Copyright Act, subjecting the work to registration formality under section 411. This ruling is in sharp contrast with an earlier decision delivered by the Delaware District Court in Håkan Moberg v. 33T LLC, et al. which arrived at an opposite conclusion. The conflicting rulings of the U.S. courts reveal the problems posed by new forms of publishing online and demonstrate a compelling need for further harmonization between the Berne Convention, domestic laws and the practical realities of digital publishing. In this chapter, we argue that even if a work first published online can be considered to be simultaneously published all over the world it does not follow that any country can assert itself as the “country of origin” of the work for the purpose of imposing domestic copyright formalities. More specifically, we argue that the meaning of “United States work” under the U.S. Copyright Act should be interpreted in line with the presumption against extraterritorial application of domestic law to limit its application to only those works with a real and substantial connection to the United States. There are gaps in the Berne Convention’s articulation of “country of origin” which provide scope for judicial interpretation, at a national level, of the most pragmatic way forward in reconciling the goals of the Berne Convention with the practical requirements of domestic law. We believe that the uncertainties arising under the Berne Convention created by new forms of online publishing can be resolved at a national level by the sensible application of principles of statutory interpretation by the courts. While at the international level we may need a clearer consensus on what amounts to “simultaneous publication” in the digital age, state practice may mean that we do not yet need to explore textual changes to the Berne Convention.

Podcast: Community wide interventions for increasing physical activity

If the amount of physical activity in a society increased, it should improve public health; but uncertainties remain about how to achieve this. Professor Philip Baker from the Queensland University of Technology in Australia describes the findings from the January 2015 update of the Cochrane review of the evidence on community-wide interventions.

Drivers of the accuracy of developers' early stage cost estimates in residential construction

Purpose – Preliminary cost estimates for construction projects are often the basis of financial feasibility and budgeting decisions in the early stages of planning and for effective project control, monitoring and execution. The purpose of this paper is to identify and better understand the cost drivers and factors that contribute to the accuracy of estimates in residential construction projects from the developers’ perspective. Design/methodology/approach – The paper uses a literature review to determine the drivers that affect the accuracy of developers’ early stage cost estimates and the factors influencing the construction costs of residential construction projects. It used cost variance data and other supporting documentation collected from two case study projects in South East Queensland, Australia, along with semi-structured interviews conducted with the practitioners involved. Findings – It is found that many cost drivers or factors of cost uncertainty identified in the literature for large-scale projects are not as apparent and relevant for developers’ small-scale residential construction projects. Specifically, the certainty and completeness of project-specific information, suitability of historical cost data, contingency allowances, methods of estimating and the estimator’s level of experience significantly affect the accuracy of cost estimates. Developers of small-scale residential projects use pre-established and suitably priced bills of quantities as the prime estimating method, which is considered to be the most efficient and accurate method for standard house designs. However, this method needs to be backed with the expertise and experience of the estimator. Originality/value – There is a lack of research on the accuracy of developers’ early stage cost estimates and the relevance and applicability of cost drivers and factors in the residential construction projects. This research has practical significance for improving the accuracy of such preliminary cost estimates.

The Other Country: A Fathers Journey with Autism

Michael and Helen Whelan believed that life after the birth of their first child would be the most amazing adventure. But at 14 months of age, their precious son Charlie's development seemed to stall and Michael and Helen began to realise that something was wrong. Referred to a paediatrician by their GP, they were given the shattering news: Charlie was autistic. For Michael and Helen, this diagnosis was bewildering, frightening and heartbreaking; neither was really sure what autism was or what it meant to Charlie's, and their family's, future. The Other Country is Michael Whelan's account of what happened next - the obstacles they faced, the treatments they tried and the people they met. The Whelans story is one of triumphs and setbacks, of tests and uncertainties, and above all, of dedication and love.