Safeguarding rural Australia : addressing masculinity and violence in rural settings : risky behaviour in a rural Australian context : analysis of secondary data analysis

This report is an update of an earlier one produced in January 2010 (see Carrington et al. 2010) which remains as an ePrint through the project’s home page. The report focus on our examination of extant data which have been sourced with respect to personally and socially risky behaviour associated with males living in regional and remote Australia and which were available in public data bases at production.

Safeguarding rural Australia : addressing masculinity and violence in rural settings : consequences of violent harm in a rural Australian context : analysis of secondary data analysis

This report is an update of an earlier one produced in January 2010 (see Carrington et al. 2010) which remains as an ePrint through the project’s home page. The report considers extant data which have been sourced with respect to some of the consequences of violent acts, incidents, harms and risky behaviour involving males living in regional and remote Australia and which were available in public data bases at production.

Social network analysis of an online dating network

Online social networks can be found everywhere from chatting websites like MSN, blogs such as MySpace to social media such as YouTube and second life. Among them, there is one interesting type of online social networks, online dating network that is growing fast. This paper analyzes an online dating network from social network analysis point of view. Observations are made and results are obtained in order to suggest a better recommendation system for people-to-people networks.

Cellulosic ethanol from sugarcane bagasse in Australia : exploring industry feasibility through systems analysis, techno-economic assessment and pilot plant development

Overcoming many of the constraints to early stage investment in biofuels production from sugarcane bagasse in Australia requires an understanding of the complex technical, economic and systemic challenges associated with the transition of established sugar industry structures from single product agri-businesses to new diversified multi-product biorefineries. While positive investment decisions in new infrastructure requires technically feasible solutions and the attainment of project economic investment thresholds, many other systemic factors will influence the investment decision. These factors include the interrelationships between feedstock availability and energy use, competing product alternatives, technology acceptance and perceptions of project uncertainty and risk. This thesis explores the feasibility of a new cellulosic ethanol industry in Australia based on the large sugarcane fibre (bagasse) resource available. The research explores industry feasibility from multiple angles including the challenges of integrating ethanol production into an established sugarcane processing system, scoping the economic drivers and key variables relating to bioethanol projects and considering the impact of emerging technologies in improving industry feasibility. The opportunities available from pilot scale technology demonstration are also addressed. Systems analysis techniques are used to explore the interrelationships between the existing sugarcane industry and the developing cellulosic biofuels industry. This analysis has resulted in the development of a conceptual framework for a bagassebased cellulosic ethanol industry in Australia and uses this framework to assess the uncertainty in key project factors and investment risk. The analysis showed that the fundamental issue affecting investment in a cellulosic ethanol industry from sugarcane in Australia is the uncertainty in the future price of ethanol and government support that reduces the risks associated with early stage investment is likely to be necessary to promote commercialisation of this novel technology. Comprehensive techno-economic models have been developed and used to assess the potential quantum of ethanol production from sugarcane in Australia, to assess the feasibility of a soda-based biorefinery at the Racecourse Sugar Mill in Mackay, Queensland and to assess the feasibility of reducing the cost of production of fermentable sugars from the in-planta expression of cellulases in sugarcane in Australia. These assessments show that ethanol from sugarcane in Australia has the potential to make a significant contribution to reducing Australia’s transportation fuel requirements from fossil fuels and that economically viable projects exist depending upon assumptions relating to product price, ethanol taxation arrangements and greenhouse gas emission reduction incentives. The conceptual design and development of a novel pilot scale cellulosic ethanol research and development facility is also reported in this thesis. The establishment of this facility enables the technical and economic feasibility of new technologies to be assessed in a multi-partner, collaborative environment. As a key outcome of this work, this study has delivered a facility that will enable novel cellulosic ethanol technologies to be assessed in a low investment risk environment, reducing the potential risks associated with early stage investment in commercial projects and hence promoting more rapid technology uptake. While the study has focussed on an exploration of the feasibility of a commercial cellulosic ethanol industry from sugarcane in Australia, many of the same key issues will be of relevance to other sugarcane industries throughout the world seeking diversification of revenue through the implementation of novel cellulosic ethanol technologies.

Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Relevance feature discovery for text analysis

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term- based ones in describing user preferences, but many experiments do not support this hypothesis. This research presents a promising method, Relevance Feature Discovery (RFD), for solving this challenging issue. It discovers both positive and negative patterns in text documents as high-level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the high-level features. The thesis also introduces an adaptive model (called ARFD) to enhance the exibility of using RFD in adaptive environment. ARFD automatically updates the system's knowledge based on a sliding window over new incoming feedback documents. It can efficiently decide which incoming documents can bring in new knowledge into the system. Substantial experiments using the proposed models on Reuters Corpus Volume 1 and TREC topics show that the proposed models significantly outperform both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and other pattern-based methods.

State of Origin : Queensland Crown Leasehold - lessons from New South Wales

Throughout Australia freehold land interests are protected by statutory schemes which grant indefeasibility of title to registered interests. Queensland freehold land interests are protected by Torrens system established by the Land Title Act 1994. However, no such protection exists for Crown land interests. The extent of Queensland occupied under some form of Crown tenure, in excess of 70%, means that Queensland Crown land users are disadvantaged when compared to freehold land users. This article examines the role indefeasibility of title has in protecting interests in Crown land. A comparative analysis is undertaken between Queensland and New South Wales land management frameworks to determine whether interests in crown land are adequately protected in Queensland.

Confirmatory factor analysis of the Behaviour of Young Novice Drivers Scale (BYNDS)

The greatly increased risk of being killed or injured in a car crash for the young novice driver has been recognised in the road safety and injury prevention literature for decades. Risky driving behaviour has consistently been found to contribute to traffic crashes. Researchers have devised a number of instruments to measure this risky driving behaviour. One tool developed specifically to measure the risky behaviour of young novice drivers is the Behaviour of Young Novice Drivers Scale (BYNDS) (Scott-Parker et al., 2010). The BYNDS consists of 44 items comprising five subscales for transient violations, fixed violations, misjudgement, risky driving exposure, and driving in response to their mood. The factor structure of the BYNDS has not been examined since its development in a matched sample of 476 novice drivers aged 17-25 years. Method: The current research attempted to refine the BYNDS and explore its relationship with the self-reported crash and offence involvement and driving intentions of 390 drivers aged 17-25 years (M = 18.23, SD = 1.58) in Queensland, Australia, during their first six months of independent driving with a Provisional (intermediate) driver’s licence. A confirmatory factor analysis was undertaken examining the fit of the originally proposed BYNDS measurement model. Results: The model was not a good fit to the data. A number of iterations removed items with low factor loadings, resulting in a 36-item revised BYNDS which was a good fit to the data. The revised BYNDS was highly internally consistent. Crashes were associated with fixed violations, risky driving exposure, and misjudgement; offences were moderately associated with risky driving exposure and transient violations; and road-rule compliance intentions were highly associated with transient violations. Conclusions: Applications of the BYNDS in other young novice driver populations will further explore the factor structure of both the original and revised BYNDS. The relationships between BYNDS subscales and self-reported risky behaviour and attitudes can also inform countermeasure development, such as targeting young novice driver non-compliance through enforcement and education initiatives.

The implementation of performance based planning in Queensland under the integrated planning act 1997 : an evaluation of perceptions and planning schemes

Performance based planning is a form of planning regulation that is not well understood and the theoretical advantages of this type of planning are rarely achieved in practice. Normatively, this type of regulation relies on performance standards that are quantifiable and technically based which are designed to manage the effects of development, where performance standards provide certainty in respect of the level of performance and the means of achievement is flexible. Few empirical studies have attempted to examine how performance based planning has been conceptualised and implemented in practice. Existing literature is predominately anecdotal and consultant based (Baker et al. 2006) and has not sought to quantitatively examine how land use has been managed or determine how context influences implementation. The Integrated Planning Act 1997 (IPA) operated as Queensland’s principal planning legislation between March 1998 and December 2009. The IPA prevented Local Governments from prohibiting development or use and the term zone was absent from the legislation. While the IPA did not use the term performance based planning, the system is widely considered to be performance based in practice (e.g. Baker et al. 2006; Steele 2009a, 2009b). However, the degree to which the IPA and the planning system in Queensland is performance based is debated (e.g. Yearbury 1998; England 2004). Four research questions guided the research framework using Queensland as the case study. The questions sought to: determine if there is a common understanding of performance based planning; identify how performance based planning was expressed under the IPA; understand how performance based planning was implemented in plans; and explore the experiences of participants in the planning system. The research developed a performance adoption spectrum. The spectrum describes how performance based planning is implemented, ranging between pure and hybrid interpretations. An ex-post evaluation of seventeen IPA plans sought to determine plan performativity within the conceptual spectrum. Land use was examined from the procedural dimension of performance (Assessment Tables) and the substantive dimension of performance (Codes). A documentary analysis and forty one interviews supplemented the research. The analytical framework considered how context influenced performance based planning, including whether: the location of the local government affected land use management techniques; temporal variation in implementation exists; plan-making guidelines affected implementation; different perceptions of the concept exist; this type of planning applies to a range of spatial scales. Outcomes were viewed as the medium for determining the acceptability of development in Queensland, a significant departure from pure approaches found in the United States. Interviews highlighted the absence of plan-making direction in the IPA, which contributed to the confusion about the intended direction of the planning system and the myth that the IPA would guarantee a performance based system. A hybridised form of performance based planning evolved in Queensland which was dependent on prescriptive land use zones and specification of land use type, with some local governments going to extreme lengths to discourage certain activities in a predetermined manner. Context had varying degrees of influence on plan-making methods. Decision-making was found to be inconsistent and the system created a range of unforeseen consequences including difficulties associated with land valuation, increased development speculation, and the role of planners in court was found to be less critical than in the previous planning system.

Charity law review and civil society : paving the way from alienation to social inclusion in Northern Ireland ; the resonance with experience in Australia

This paper considers the opportunity, presented by the forthcoming charity law review in Northern Ireland, for adjusting the charity law framework so as to focus charitable activity on the circumstances typical of societies in conflict or experiencing transition. This opportunity is one for broadening the definition of 'charitable purpose' to include activities directed towards forestalling alienation and facilitating social inclusion. It would include rehabilitating the victims of social confrontation and developing related services of advocacy, mediation and reconciliation. It argues that a creative response to this opportunity could address the current social inclusion agenda and thereby contribute to the consolidation of civil society in this jurisdiction. It suggests that the experience in Northern Ireland, as an exemplar of a society in transition, has a resonance with the experience in Australia. It further suggests that it could also have a relevance for approaching the management of tensions within or between nations where people may otherwise come to perceive themselves as alienated...

Exploring information experience using social media during the 2011 Queensland floods : a pilot study

Social media networks have emerged as a powerful tool in allowing collaboration and sharing of information during times of crisis (Bruns, The Centre for Creative Industries Blog, comment posted on January 19,2011). The 2011 Queensland floods provided a unique opportunity to explore social media use during an emergency. This paper presents the findings of a pilot study that explored the information experiences of people using social media during the flooding of the Brisbane River. Analysis of data from four interviews supported the emergence of four categories of information experience. Examination of the categories revealed variation between the way in which individuals experienced social media and the point of the flooding at which each category of experience occurred. Information regarding individual’s use of social media has the potential to inform the development of social media platforms that can provide relevant and accessible information for the general public in event of a natural disaster.

Integrating organisational design with IT design : the Queensland Health payroll case

Most existing requirements engineering approaches focus on the modelling and specification of the IT artefacts ignoring the environment where the application is deployed. Although some requirements engineering approaches consider the stakeholder’s goals, they still focus on the IT artefacts’ specification. However, IT artefacts are embedded in a dynamic organisational environment and their design and specification cannot be separated from the environment’s constant evolution. Therefore, during the initial stages of a requirements engineering process it is advantageous to consider the integration of IT design with organisational design. We proposed the ADMITO (Analysis, Design and Management of IT and Organisations) approach to represent the dynamic relations between social and material entities, where the latter are divided into technological and organisational entities. In this paper we show how by using ADMITO in a concrete case, the Queensland Health Payroll (QHP) case, it is possible to have an integrated representation of IT and organisational design supporting organisational change and IT requirements specification.

Global civil society and adult education for social change : a postcolonial perspective

Adult education plays an important role in global economic development and features prominently in debates about changing requirements of post-industrial knowledge societies. This dominant technical-instrumental understanding of adult education in public discourse masks the transformative function of certain types of adult education - that is, the possibilities of adult education to improve social justice issues such as workers’ rights, human rights, civic participation in governance and socially just development. Given the increasing social stratification between and within the North and South in the global era, the potential of adult education to effect social change has been rediscovered by organisations within global civil society, namely international non-governmental organisations (INGOs). The broad objective of this research was to carry out an in-depth qualitative case study of a human rights advocacy program provided by a Northern INGO predominantly operating within the global South. The study analyses how participants see this program in terms of its potential to contribute to progressive social change in their home communities across the Asia-Pacific region. The following questions guided the study: 1. To what extent does this adult education program challenge existing systems of domination and marginalisation? 2. How did completion of the program affect participants’ views of their abilities to facilitate social action within their communities? Data sources for this research were interviews with 19 participants and staff and questionnaires from 28 participants of the program from a variety of countries in the Asia-pacific region. The gap in the literature that this study addressed is that existing empirical research sidelines the analysis of the globalisation, adult education, and social change nexus from a perspective that takes the marginalised other seriously, tending instead to mirror the material subjugation of the South in discursive practices. Social change is highly context-specific and strategies to advance it depend on the way in which people understand their reality and are affected by adverse social conditions. The present study employed a postcolonial framework that provided a holistic approach to analysing adult education for social change inclusive of material, political, and social conditions and the interplay between these from the local to the global level. The program convincingly exemplified an example of adult education for counter-hegemonic resistance against the dominant neoliberal discourse. It achieved this by enabling participants, based on Freirian pedagogical principles, to locate the problem of social change and frame their strategies to address it within mutually constitutive local and global developments and the discourses that describe them. It provided the underpinning knowledge and skills for effective advocacy and created opportunities to build networks between various stakeholders. At minimum, most advocates accord their participation in the program a supporting role in enhancing their ability to examine causes for social injustices and ways to address these. Some advocates even regarded their program participation as fundamental in understanding these issues. Almost all participants reported an increased skill-set that enabled them to become more effective advocates.

Analysis and correction of voltage profile in low voltage distribution networks containing photovoltaic cells and electric vehicles

Voltage drop and rise at network peak and off–peak periods along with voltage unbalance are the major power quality problems in low voltage distribution networks. Usually, the utilities try to use adjusting the transformer tap changers as a solution for the voltage drop. They also try to distribute the loads equally as a solution for network voltage unbalance problem. On the other hand, the ever increasing energy demand, along with the necessity of cost reduction and higher reliability requirements, are driving the modern power systems towards Distributed Generation (DG) units. This can be in the form of small rooftop photovoltaic cells (PV), Plug–in Electric Vehicles (PEVs) or Micro Grids (MGs). Rooftop PVs, typically with power levels ranging from 1–5 kW installed by the householders are gaining popularity due to their financial benefits for the householders. Also PEVs will be soon emerged in residential distribution networks which behave as a huge residential load when they are being charged while in their later generation, they are also expected to support the network as small DG units which transfer the energy stored in their battery into grid. Furthermore, the MG which is a cluster of loads and several DG units such as diesel generators, PVs, fuel cells and batteries are recently introduced to distribution networks. The voltage unbalance in the network can be increased due to the uncertainties in the random connection point of the PVs and PEVs to the network, their nominal capacity and time of operation. Therefore, it is of high interest to investigate the voltage unbalance in these networks as the result of MGs, PVs and PEVs integration to low voltage networks. In addition, the network might experience non–standard voltage drop due to high penetration of PEVs, being charged at night periods, or non–standard voltage rise due to high penetration of PVs and PEVs generating electricity back into the grid in the network off–peak periods. In this thesis, a voltage unbalance sensitivity analysis and stochastic evaluation is carried out for PVs installed by the householders versus their installation point, their nominal capacity and penetration level as different uncertainties. A similar analysis is carried out for PEVs penetration in the network working in two different modes: Grid to vehicle and Vehicle to grid. Furthermore, the conventional methods are discussed for improving the voltage unbalance within these networks. This is later continued by proposing new and efficient improvement methods for voltage profile improvement at network peak and off–peak periods and voltage unbalance reduction. In addition, voltage unbalance reduction is investigated for MGs and new improvement methods are proposed and applied for the MG test bed, planned to be established at Queensland University of Technology (QUT). MATLAB and PSCAD/EMTDC simulation softwares are used for verification of the analyses and the proposals.