Dissertations / Theses on the topic 'Prediction of Australia'
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1
Eadie, Edward Norman. "Small resource stock share price behaviour and prediction." Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09CM/09cme11.pdf.
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Prentice, Jennifer Lorna. "An evaluation of clinical practice guidelines for the prediction and prevention of pressure ulcers." University of Western Australia. School of Surgery and Pathology, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0170.
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[Truncated abstract] Pressure ulcers affect a substantial proportion of patients admitted to health care services worldwide imposing considerable physical, social and economic burdens on patients and communities. As largely preventable wounds their prevalence is likely to escalate as the life expectancy and incidence of people living longer with other chronic diseases increases. Clinical practice guidelines are promulgated as evidence-based tools to assist clinicians and patients to determine care strategies, reduce inequities in healthcare provision and lower the burden of illness through improved health outcomes. This prospective multi-centre study evaluated the effectiveness of the Australian Wound Management Association?s Clinical Practice Guidelines for the Prediction and Prevention of Pressure Ulcers within ten selected Australian tertiary hospitals. The data, collected in 2000, examined pressure ulcer prevalence in a subset of five of these hospitals and junior doctors’ and nurses’ knowledge of pressure ulcers in all ten hospitals at two time points, before and after guideline implementation. Pressure ulcer prevalence was ascertained by two surveyors who independently examined the skin of all consenting adult patients on a designated day. ... In addition, it is recommended that all Australian health care facilities providing in-patient, residential aged or domiciliary care services be required to demonstrate compliance with the Australian Council of Health Care Standards framework for pressure ulcers in order to be an accredited healthcare provider. The use, benefits and cost utility of pressure reducing / relieving devices in the prediction and prevention of pressure ulcers in Australian contexts of care, is required to substantiate current guideline recommendations and assist service providers and clinicians in choosing devices according to patient need. A recommendation will be forwarded to the Australian Wound Management Association suggesting the Association develop a toolkit to facilitate implementation and adoption of their guidelines. It is recommended that training of doctors, nurses and allied health personnel in the prediction, prevention and management of pressure ulcers should be of a higher priority within under-and-postgraduate education programs. From a community perspective and with a view to improving the health of the community, it is proposed that pressure ulcers be the subject of ongoing health promotion campaigns aimed at raising patients’, caregivers’ and community awareness of the potential for pressure ulcers due to the secondary effects of lifestyle related chronic diseases and ensuing reduced levels of immobility.
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Senanayake, Sameera Jayan. "Prediction of graft survival and cost effectiveness of kidney transplantation according to donor quality levels in Australia." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/211469/1/Sameera%20Jayan_Senanayake_Thesis.pdf.
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This thesis sought to better understand how quality of donor kidneys and allocating kidneys based on the presumed longevity can increase value for money in donor kidney use. It showed that remaining on dialysis in the hope of receiving a superior-quality kidney is not a cost-effective strategy for any age group. If the Australian kidney allocation system can enable low-quality kidneys for older recipients, this will reduce discard rates, and promote the best value for all donated kidneys. The new index developed to predict graft failure demonstrated adequate potential to make pre-transplantation predictions about the longevity of a donated kidney.
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Oliver, Clive P. "Some determinants of success and failure in first-year university business units at private colleges." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 1999. https://ro.ecu.edu.au/theses/1202.
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This study investigates some of the determinates of academic success and failure (and dropout) from first year university level Business units at two private business colleges in Perth, Western Australia. Private business colleges are convenient vehicles for international and Western Australian students who do not possess adequate academic assessments for direct entry into university, and for students who might benefit from an enhanced pastoral support system, in the transition from secondary education to tertiary education. The study is important to private providers and to universities who are trying to help students succeed at university. The study utilises a model of two dependent variables (achievement at first attempt and achievement at second attempt); five independent variables (motivation to achieve, outside work commitments, performance to expectations, family problems, and attendance); and three situation variables (age, gender and whether English is the first language of the student). The variables in the model were identified from various studies in the literature, as likely to be most strongly related to academic success or failure. The model suggests a number of bivariate relationships between the dependent variables andthe independent variables and between the dependent variables and the situation variables. The model also suggests a number of joint relationships between the dependent, independent and situation variables. The dependent variables were measured for eight first year units of study which are generic to Bachelor Degree programmes at most universities for Business or Commerce; Accounting, Economics, Finance, Information Systems, Legal Framework, Management, Marketing and Statistics. The sample consists of 195 students from private provider A and 92 students from private provider B in Perth, Western Australia (a total of 287 students). Data were collected by means of a questionnaire which was distributed to students in both private colleges in mid-semester 1996, and which students completed on a voluntary basis. Each of the independent variables were measured from student self-report data and the private colleges provided the individual student results in each of the eight Business subjects to use as measures of the dependent variables. Analysis took the form of cross-tabulations, zero-order correlations and multiple regression to test the relationships between the dependent and independent variables, as suggested by the model. The computer package SPSS (Statistical Package for the Social Sciences) was used for the analysis. The conclusions relating to the zero-order correlations are presented in two parts: those relating Achievement at the first attempt and Achievement at the second attempt (as dependent variables) with the five independent variables and those relating the dependent variables with the three situation variables. (i) The five independent variables have small or no correlations with the two dependent variables. (ii) The three situation variables have small or no correlations with the two dependent variables. In each case, the amount of explained variance in the dependent variable was 7% or less and hence the relationships are of no practical significance for any of the eight Business subjects, for students or private providers. The conclusions relating to the multiple regression analysis are presented in three parts: those relating the dependent variables with the independent variables, those relating the dependent variables with the situation variables, and those relating the dependent variables with the independent and situation variables together. (iii) The five independent variables together account for less than 9% variance in the dependent variables. (iv) The three situation variables together account for less than 10% of variance in the dependent variables. (v) The five independent variables and the three situation variables together account for less than 15% of variance in the dependent variables. These relationships are so small that they are of no practical significance for any of the eight Business subjects, for students or private providers. While there do not appear to be any direct implications for private providers or students, flowing from this study, there are direct implications for further research. In particular, a better model needs to be developed that uses variables that can explain more of the variance in achievement at the first and second attempts. This may mean that different and better measures of the independent variables need to be made and that new independent variables need to be uncovered, perhaps, by interviewing students at private providers.
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Misich, Ian J. "Subsidence prediction and mine design for underground coal mining in the Collie Basin." Thesis, Curtin University, 1997. http://hdl.handle.net/20.500.11937/88.
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The subsidence characteristics of the Collie Basin sediments have been investigated to provide site specific design criteria for the Wongawilli method of coal extraction. As historical coal extraction (bord and pillar) methods did not generally give rise to large scale subsidence, there were very few details on mining subsidence in the Collie Basin available to base any design methodology on. Consequently, the investigation was conducted on a Green fields basis. Firstly, the mechanisms involved in the development of mining subsidence needed to be investigated and identified. It was then necessary to determine the effects that mining subsidence would have on mine and ground mass (specifically aquitards) structures and surface features. Once these two areas of work were completed, design criteria were formulated to manage the effects of mining subsidence by controlling the critical mechanisms of subsidence development.The results from this study have greatly enhanced the level of understanding of the subsidence mechanisms involved, and allowed for the development of predictive models which can be used for the design of coal extraction by the panel/pillar mining method in the Collie Basin. Mine planning engineers can now use this design information to derive the most cost effective methods for the extraction of coal within the Collie Basin.
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Vagh, Yunous. "Mining climate data for shire level wheat yield predictions in Western Australia." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2013. https://ro.ecu.edu.au/theses/695.
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Climate change and the reduction of available agricultural land are two of the most important factors that affect global food production especially in terms of wheat stores. An ever increasing world population places a huge demand on these resources. Consequently, there is a dire need to optimise food production.
Estimations of crop yield for the South West agricultural region of Western Australia have usually been based on statistical analyses by the Department of Agriculture and Food in Western Australia. Their estimations involve a system of crop planting recommendations and yield prediction tools based on crop variety trials. However, many crop failures arise from adherence to these crop recommendations by farmers that were contrary to the reported estimations. Consequently, the Department has sought to investigate new avenues for analyses that improve their estimations and recommendations.
This thesis explores a new approach in the way analyses are carried out. This is done through the introduction of new methods of analyses such as data mining and online analytical processing in the strategy. Additionally, this research attempts to provide a better understanding of the effects of both gradual variation parameters such as soil type, and continuous variation parameters such as rainfall and temperature, on the wheat yields.
The ultimate aim of the research is to enhance the prediction efficiency of wheat yields. The task was formidable due to the complex and dichotomous mixture of gradual and continuous variability data that required successive information transformations. It necessitated the progressive moulding of the data into useful information, practical knowledge and effective industry practices. Ultimately, this new direction is to improve the crop predictions and to thereby reduce crop failures.
The research journey involved data exploration, grappling with the complexity of Geographic Information System (GIS), discovering and learning data compatible software tools, and forging an effective processing method through an iterative cycle of action research experimentation. A series of trials was conducted to determine the combined effects of rainfall and temperature variations on wheat crop yields. These experiments specifically related to the South Western Agricultural region of Western Australia. The study focused on wheat producing shires within the study area. The investigations involved a combination of macro and micro analyses techniques for visual data mining and data mining classification techniques, respectively.
The research activities revealed that wheat yield was most dependent upon rainfall and temperature. In addition, it showed that rainfall cyclically affected the temperature and soil type due to the moisture retention of crop growing locations. Results from the regression analyses, showed that the statistical prediction of wheat yields from historical data, may be enhanced by data mining techniques including classification.
The main contribution to knowledge as a consequence of this research was the provision of an alternate and supplementary method of wheat crop prediction within the study area. Another contribution was the division of the study area into a GIS surface grid of 100 hectare cells upon which the interpolated data was projected. Furthermore, the proposed framework within this thesis offers other researchers, with similarly structured complex data, the benefits of a general processing pathway to enable them to navigate their own investigations through variegated analytical exploration spaces. In addition, it offers insights and suggestions for future directions in other contextual research explorations.
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Ruiz, Jose Eric Civil & Environmental Engineering Faculty of Engineering UNSW. "Integrating subsurface ocean temperatures in the statistical prediction of ENSO and Australian rainfall & streamflow." Awarded by:University of New South Wales. School of Civil and Environmental Engineering, 2006. http://handle.unsw.edu.au/1959.4/23433.
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As a global climate phenomenon, the El Ni??o-Southern Oscillation (ENSO) involves the coupling of the ocean and the atmosphere. Most climate prediction studies have, by far, only investigated the teleconnections between global climatic anomalies and the ???surface??? predictors of ENSO. The prediction models resulting from these studies have generally suffered from inadequate, if not the lack of, skill across the so-called boreal ???spring barrier???. This is illustrated in the first part of this thesis where the applicability of the SOI phase for long-lead rainfall projections in Australia is discussed. With the increasing availability of subsurface ocean temperature data, the characteristics of the Pacific Ocean???s heat content and its role in ENSO are now better understood. The second part of this thesis investigated the predictability of ENSO using the thermocline as a predictor. While the persistence and SST-based ENSO hindcasts dropped in skill across the spring barrier, the thermocline-based hindcasts remained skillful even up to a lag of eighteen months. Continuing on the favorable results of ENSO prediction, the third part of this thesis extended the use of the thermocline in the prediction of Australia???s rainfall and streamflow. When compared to models that use ???surface??? predictors, the model that incorporated thermocline information resulted in more skillful projections of rainfall and streamflow especially at long lead-times. More importantly, significant increases in skill of autumn and winter projections demonstrate the ability of the subsurface ocean to retain some climatic memory across the predictability barrier. This resilience can be attributed to the high persistence of the ocean heat content during the first half of the year. Based on weighting, the model averaging exercise also affirmed the superiority of the ???subsurface??? model over the ???surface??? models in terms of streamflow projections. The encouraging findings of this study could have far-reaching implications not only to the science of ENSO prediction but also to the more pragmatic realm of hydrologic forecasting. What this study has demonstrated is an alternative predictor that is suitable for the long range forecasting of ENSO, rainfall and streamflow. With better hydrologic forecasting comes significant improvement in the management of reservoirs which eventually leads to an increase in the reliability and sufficiency of water supply provision.
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Lien, Debbie A. "The prediction of antenatal and postnatal depression in a sample of Western Australian women." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2007. https://ro.ecu.edu.au/theses/1558.
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In Australia, the Edinburgh Postnatal Depression Scale (EPDS; Cox, Holden & Sagovsky, 1987) has been increasingly used to screen for antenatal depression prior to its evaluation on a sample of Australian pregnant women. Also, the identification of predictors associated with antenatal depression has been neglected relative to the research focus on postpartum depression. An aim of the study was to evaluate the antenatal screening properties of the EPDS against diagnoses of major depression with the Mini International Neuropsychiatric Interview (MINI; Sheehan eta!., 1998). The aims were also to develop predictive models of risk factors associated with antenatal depression as measured by: (a) diagnosis of major depression (MINI); (b) depressive symptoms (EPDS 2: 9); (c) depression false positive results (EPDS 2:9, but no MINI diagnosis of major depression); and (d) depression level (EPDS total score) in the antenatal and early postnatal period. The study was prospective in design, with 200 women enrolled from Western Australia's largest public maternity hospital. An EPDS 2: 12 was identified to be optimum for the clinical screening of major depression at 32 weeks of pregnancy. The results from the different regression analyses showed that the strongest predictors of antenatal depression were: depression earlier in pregnancy, anxiety, stress, daily hassles, expectations of support, personality traits, and history variables. The findings were in support of routine screening for depression and anxiety during pregnancy, the effects of stress on mood, and the lesser importance of antenatal compared to postnatal variables in accounting for postpartum depression level.
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Misich, Ian J. "Subsidence prediction and mine design for underground coal mining in the Collie Basin." Curtin University of Technology, School of Civil Engineering, 1997. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=12359.
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The subsidence characteristics of the Collie Basin sediments have been investigated to provide site specific design criteria for the Wongawilli method of coal extraction. As historical coal extraction (bord and pillar) methods did not generally give rise to large scale subsidence, there were very few details on mining subsidence in the Collie Basin available to base any design methodology on. Consequently, the investigation was conducted on a Green fields basis. Firstly, the mechanisms involved in the development of mining subsidence needed to be investigated and identified. It was then necessary to determine the effects that mining subsidence would have on mine and ground mass (specifically aquitards) structures and surface features. Once these two areas of work were completed, design criteria were formulated to manage the effects of mining subsidence by controlling the critical mechanisms of subsidence development.The results from this study have greatly enhanced the level of understanding of the subsidence mechanisms involved, and allowed for the development of predictive models which can be used for the design of coal extraction by the panel/pillar mining method in the Collie Basin. Mine planning engineers can now use this design information to derive the most cost effective methods for the extraction of coal within the Collie Basin.
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Wan, Jing. "Prediction of the potential geographic distributions and risk assessment of four trade impacting invasive insect pests in Australia and China." Thesis, Wan, Jing (2020) Prediction of the potential geographic distributions and risk assessment of four trade impacting invasive insect pests in Australia and China. PhD thesis, Murdoch University, 2020. https://researchrepository.murdoch.edu.au/id/eprint/61455/.
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This thesis explores biological invasion through the potential pest distribution and risk analysis of tomato potato psyllid (TPP), Bactericera cockerelli; fall armyworm (FAW), Spodoptera frugiperda; Bactrocera bryoniae; and Bactrocera neohumeralis. Through better understanding of the pest distribution and risk analysis agricultural management policies can be implemented, and containment and eradication actions taken.
The TPP is a psyllid native to North America that has recently invaded Australia. The potential for economic losses accompanying invasions of TPP and its associated bacterial plant pathogen Candidatus Liberibacter solanacearum (CLso), has caused much concern. Here, we employed ecological niche models to predict environments suitable for TPP/CLso on a global scale and then evaluated the extent to which global potato cultivation is at risk. A total of 86 MaxEnt models were built using various combinations of settings and climatic predictors, and the best model based on model evaluation metrics was selected. Climatically suitable habitats were identified in Eurasia, Africa, South America, and Australasia. Intersecting the predicted suitability map with land use data showed that 79.06% of the global potato production, 96.14% of the potato production acreage in South America and Eurasia, and all the Australian potato production are at risk. The information generated in this study increases knowledge of the ecology of TPP/CLso and can be used by government agencies to make decisions about preventing the spread of TPP and CLso across the globe.
Fall armyworm (FAW), S. frugiperda is native to the Americas and it has rapidly invaded 47 African countries and 18 Asian countries since the first detection of invasion into Nigeria and Ghana in 2016. It is regarded as a ‘super pest’ based on its host range (at least 353 host plants), its inherent ability to survive in a wide range of habitats, its strong migration ability, high fecundity, rapid development of resistance to insecticides/viruses and its gluttonous characteristics. In order to better understand the seasonal geographic distributions of S. frugiperda, we employed ecological niche models of MaxEnt to predict potential year-round breeding and seasonal distribution for S. frugiperda on a global scale and in Australia. A total of 74 MaxEnt models were built using various combinations of regularization multiplier, feature class and climatic variables, and the best model based on model evaluation metrics was selected, with an evaluation of dominant climatic factors that control its distribution. The results suggest that the temperature factor was the most important variable affecting the seasonal distribution of S. frugiperda. No matter where in the world, the year-round breeding distribution model predicted smaller portions of fall armyworm's ranges than the seasonal model. S. frugiperda had a high remaining invasion potential in Australia, posing a significant threat to its biosecurity, food security and agricultural productivity.
Bactrocera bryoniae and Bactrocera neohumeralis are highly destructive fruit flies and considered major biosecurity/quarantine pests of fruit and vegetable in the tropical and subtropical regions in the South Pacific. Ecological niche modelling MaxEnt was employed to predict the potential geographic distribution of B. bryoniae and B. neohumeralis across the world and particularly in China with the occurrence data of these two species. B. bryoniae and B. neohumeralis exhibit similar potential geographic distribution ranges across the world and in China, and included southern Asia, the central and the southeast coast of Africa, southern North America, northern and central South America, and Australia. While within China, most of the southern Yangtze River area was found suitable for these two species. Notably, southern China was considered to have the highest risk of B. bryoniae and B. neohumeralis invasions. Our study identifies the regions at high risk for potential establishment of B. bryoniae and B. neohumeralis in the world and particularly in China and informs government officials to develop policies for inspection and biosecurity/quarantine measures to prevent and control their invasion.
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Garforth, Tayne. "Serial robbery: An investigation into the variations of offence behaviour and implications for inferring offender characteristics." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2007. https://ro.ecu.edu.au/theses/252.
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This research investigates whether and to what extent the thematic structure of robbery offence behaviours identified in L. Alison, W. Rockett, S. Deprez & S. Watts, 2000 is replicated for an Australian sample of serial robbers. Offence variables representing variations in the degree of planning (proactive-reactive) and self-control (rational-impulsive) were examined from a sample of offences obtained from 91 serial robbery offenders using data obtained from police Offence Reports in Western Australia. A Smallest Space Analysis (SSA) tended to support the relevance of these psychological processes to robbery behaviour and considered to offer a meaningful basis for distinguishing between robbery offences according to three narrative themes. However, the thematic structure of the "Amateur" robber (identified in previous research as "Bandits") differed in some respects from that proposed by Alison et al. (2000). This research further aimed to evaluate the hypothesis that proposes the consistency of these themes as a function of narrative roles. Overall, a total of 78 cases (85. 7%) were found to exhibit the same 'pure' or hybrid theme across at least two of the three offences committed in the series and considered to provide some support to the hypothesis that the SSA structure represents the dominant themes underlying robbery behaviour and the utility of narrative theory as a useful framework in explaining variations in offence behaviour. Whilst results indicated that offence behaviour of individual robbers were consistent with the themes underlying differences in robber styles, the examination of specific offence variables using Cochran' s Q tests and frequency analysis suggests that some caution must be incorporated into investigative strategies involving the use of single behavioural indicators in the identification of serial offenders and offence linking. Whilst these results have implications for research methods that focus on identifying clusters of behaviours that reflect meaningful aspects of "personality", the nature of behavioural consistency suggests that this robber typology may be improved with further investigation of situational factors influencing crime scene behaviour in order to achieve the development of a more productive model for contemporary offender profiling.
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Farrelly, Francis John. "A predictive model of sport sponsorship renewal in Australia." Title page, abstract and table of contents only, 2002. http://web4.library.adelaide.edu.au/theses/09PH/09phf245.pdf.
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Bibliography: leaves 231-291. This thesis investigates key drivers of sponsorship renewal. The market orientation of sponsors, and their perception of their sponsored entity's (property's) market orientation, are analysed as antecedents of the trust invested by sponsors in the relationship, the level of commitment they exhibit and both the economic and non-economic satisfaction they derive from it. Sponsor economic and non-economic satisfaction and their commitment to the relationship are considered to be the ultimate drivers of the decision to renew. The argument is presented that sponsorship is a form of strategic or co-marketing alliance. The Australian Football League, the leading sponsorship property in Australia, is investigated in the empirical part of the thesis.
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Mamouni, Limnios Elena Alexandra. "Incorporating complex systems dynamics in sustainability assessment frameworks : enhanced prediction and management of socio-ecological systems performance." University of Western Australia. Faculty of Business, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0012.
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[Truncated abstract] The application of reductionism, breaking down problems to simpler components that can be solved and then aggregating the results, is one of the bases of classical science. However, living organisms, ecosystems, social and economic structures are complex systems, characterised by non-linear interactions between their elements and exhibit emergent properties that are not directly traceable to their components. Sustainability assessment frameworks oversimplify system interactions, achieving limited predictive capacity and causing managerial behavior that may reduce system's ability to adapt to external disturbance. Intrigued by the importance of complexity, we explore the central theme of how complex thinking can influence the understanding and progress towards sustainability. The purpose is to conceptualize the relationship of key terms (such as sustainability, functionality and resilience), and consecutively develop new or adjust existing sustainability frameworks to take into account complex systems interactions. We aim at developing theory and frameworks that can be used to raise awareness of the pitfalls of the growth paradigm and direct towards modest positions when managing complex systems. We seek to define the structural elements that influence system adaptive capacity, allowing identification of early signs of system rigidity or vulnerability and the development of knowledge and techniques that can improve our predictive and managerial ability. The focus has been on a variety of system scales and dynamics. At the collective community level, a number of stakeholder engagement practices and frameworks are currently available. However, there is limited awareness of the complexity challenges among stakeholders, who are commonly directed to a triple bottom line analysis aiming at maximizing a combination of outputs. An attempt is conducted to measure the functionality of the processes underlying a standing stock, in contrast to sustainability measures that only assess the variations of the standing stock itself. We develop the Index of Sustainable Functionality (ISF), a framework for the assessment of complex systems interactions within a large-scale geographic domain and apply it to the State of Western Australia. '...' Finally, we focus on smaller systems scales and develop a methodology for the calculation of Product Ecological Footprint (PEF) including elements from the accounting method of activity based costing. We calculate PEF for three apple production systems and identify significant differences from first stage calculations within the same industry. Cross-industry application will provide a practical way to link individuals' consumption with their ecological impact, reduce misperceptions of products' ecological impacts and develop a market-driven approach to internalizing environmental externalities. At the firm level PEF can be compared with investment costs, resulting in the opportunity to optimize both functions of financial cost and ecological impact in decision making. We have developed methods for incorporating complexity in sustainability assessment frameworks. Further work is required in testing and validating these methodologies at multiple system scales and conditions. Integrating such tools in decision making mechanisms will enhance long-term management of socioecological systems performance.
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Tilakaratne, Chandima University of Ballarat. "Stock market predictions based on quantified intermarket influences." University of Ballarat, 2007. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12798.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Doctor of Philosophy
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Tilakaratne, Chandima. "Stock market predictions based on quantified intermarket influences." University of Ballarat, 2007. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15394.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Doctor of Philosophy
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Ziesch, Jennifer [Verfasser], Charlotte M. [Akademischer Betreuer] Krawczyk, David C. [Akademischer Betreuer] Tanner, Charlotte M. [Gutachter] Krawczyk, David C. [Gutachter] Tanner, and Andreas [Gutachter] Henk. "Prediction of seismic and sub-seismic deformation to ensure carbon traps in the Otway Basin, Australia / Jennifer Ziesch ; Gutachter: Charlotte M. Krawczyk, David C. Tanner, Andreas Henk ; Charlotte M. Krawczyk, David C. Tanner." Berlin : Technische Universität Berlin, 2016. http://d-nb.info/1156182018/34.
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Tilakaratne, Chandima University of Ballarat. "A neural network approach for predicting the direction of the Australian stock market index." University of Ballarat, 2004. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12804.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Master of Information Technology by Research
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Tilakaratne, Chandima. "A neural network approach for predicting the direction of the Australian stock market index." University of Ballarat, 2004. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15397.
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This research investigated the feasibility and capability of neural network-based approaches for predicting the direction of the Australian Stock market index (the target market). It includes several aspects: univariate feature selection from the historical time series of the target market, inter-market analysis for finding the most relevant influential markets, investigations of the effect of time cycles on the target market and the discovery of the optimal neural network architectures. Previous research on US stock markets and other international markets have shown that the neural network approach is one of most powerful techniques for predicting stock market behaviour. Neural networks are capable of capturing the non-linear stochastic and chaotic patterns in the stock market time series data. This study discovered that the relative return series of the Open, High, Low and Close prices of the target market, show 6-day cycles during the studied period of about 14 years. Multi-layer feedforward neural networks trained with a backpropagation algorithm were used for the experiments. Two major testing methods: testing with randomly selected test data and forward testing, were examined and compared. The best neural network developed in this study has achieved 87%, 81% 83% and 81% accuracy respectively in predicting the next-day direction of the relative return of the Open, High, Low and Close prices of the target market. The architecture of this network consists of 33 input features, one hidden layer with 3 neurons and 4 output neurons. The best input features set includes the relative returns from 1 to 6 days in the past of the Open, High, Low and Close prices of the target market, the day of the week, and the previous day’s relative return of the Close prices of the US S&P 500 Index, US Dow Jones Industrial Average Index, US Gold/Silver Index, and the US Oil Index.Master of Information Technology by Research
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Sykes, Deborah Ann. "Computerised growth prediction : an evaluation of Quick Ceph in Central Australian Aborigines /." Title page, abstract and contents only, 1995. http://web4.library.adelaide.edu.au/theses/09DM/09dms983.pdf.
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Davies, Malcolm Roy, and n/a. "Prediction of Transformational Leadership by Personality Constructs for Senior Australian Organisational Executive Leaders." Griffith University. School of Psychology, 2005. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20060220.142914.
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The purpose of this thesis was to investigate prediction of senior leader transformational leadership behaviour. Transformational leadership was identified as a major theory with substantial practical implications for economic prosperity. It was argued that a better understanding of what predicts transformational behaviour would assist in creating a lift in the effective application of the theory with attendant benefits for all organisational stakeholders. It was proposed that personality components would predict transformational behaviour. Personality was conceptualised in two ways: as components of the Five Factor Model of personality and as personality disorder components. Specifically, eight personality constructs were hypothesised as predictors. They were three Hogan Personality Inventory based Five Factor Model components and the five Hogan Development Survey personality disorder components. It was further proposed that self-subordinate rating agreement would moderate the prediction of transformational behaviour by the selected personality components. A survey research methodology was used to gather data from senior Australian organisational executive leaders. Two samples were accessed while subjects were attending training or strategy seminars. The samples incorporated a total of 462 individual senior leader subjects and 1,881 of their subordinates drawn from the top four levels of a range of large multi-level public and private Australian organisations. It was argued that the sample validly represent a senior executive cohort of organisational leaders. Subject leaders completed a brief demographic questionnaire, the leader version of the Multifactor Leadership Questionnaire, and either the Hogan Personality Inventory or the Hogan Development Survey. Subjects' subordinates completed the rater version of the Multifactor Leadership Questionnaire. Transformational behaviour was operationalised as charisma, which was calculated as the mean of two subordinate rated transformational components of the Multifactor Leadership Questionnaire, viz., idealised behaviour and inspirational motivation. This dependent variable was regressed on the various personality variables to assess predictive ability. Moderation of the prediction of transformational leadership behaviour by personality components was assessed by multiple regression of transformational leadership behaviour on the various personality components within self-subordinate rating agreement categories. There were eight specific original contributions from the findings of this thesis. The HPI component ambition was found to positively predict charisma. The HPI component prudence was found to negatively predict charisma. Self subordinate rating agreement operationalised as an absolute difference score was found to moderate the level of prediction by whole HPI regression model and some of the relationships and predictions of charisma by individual HPI components. It was found that prevalence of personality disorder components among senior executives varied from six percent to 34 percent of the sample cases. The HDS personality disorder components sceptical and cautious were found to negatively predict charisma; whereas the HDS component imaginative was found to positively predict charisma. Self subordinate rating agreement operationalised as a relative difference score was found to moderate the whole HDS regression model and some but not all of the relationships and predictions of charisma by individual HDS components. Theoretical and practical implications of the above findings, limitations of this research and recommendations for future research were discussed.
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Goh, Gek Huang Louise. "Risk score for predicting cardiovascular disease mortality in Australian women." Thesis, Curtin University, 2014. http://hdl.handle.net/20.500.11937/223.
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Louise evaluated the utility of risk score models for predicting cardiovascular mortality in Australian women. She found that most risk models do not diagnose “at risk” women well. Currently published predicted risk levels used for screening and recommending treatment are ineffective. Lower treatment thresholds are recommended. Central obesity and ethnicity have been identified for inclusion in future models. Her study has important implications for improving the accuracy of identifying “at risk” women for preventive treatment.
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James, Kyle. "DNA-MAP, a knowledge-based decision support system for Australian Defence Force forensic ancestry prediction." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/213211/1/Kyle_James_Thesis.pdf.
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Development of a Knowledge-Based Decision Support System to predict ancestry of the remains of missing World War Two soldiers in South-East Asia. By utilizing biological and historical information provided by the user, ancestry is assigned based on complex statistical analyses searching for distinctive patterns in the DNA that distinguish between the Australian and Japanese populations. Important features taken into consideration are the detection of a rare event, the effect of sample size and the impact of natural variation.
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Della, Torre Gail. "Variables predictive of assessment and treatment outcome in adult sex offenders in Western Australia." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2001. https://ro.ecu.edu.au/theses/1024.
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This exploratory study examines differences between a) sex offenders who entered treatment (N = 117) and those who did not enter treatment (N =51), and b) sex offenders who completed treatment successfully (N = 83) and those who did not complete successfully (N = 22), The two samples were derived from a total sample pool of 199 adult male sex offenders who were sentenced in Western Australia in 1995 and assessed for treatment suitability by the Sex Offender Treatment Unit (SOTU). Logistic regression was used to determine which variables would best predict a) entry into treatment, and b) treatment Success. Variables used in the study included demographic information, offender characteristics and offence details. The results indicated little differences between those offenders who entered treatment and those offenders who did not enter treatment. Only two variables, marital status and prior non-sex violent offences appear to discriminate between the two groups. Six variables appear to be associated with treatment success. They are age at first conviction, prior sex offence convictions, prior non-violent offence convictions, marital status, education and offender type. This study also reports on the proportion of sex offenders who were assessed for treatment suitability from the total number sentenced in 1995, the proportion of offenders who were considered suitable for treatment, of those considered suitable the proportion who actually entered treatment, and of those who entered treatment the proportion, who completed treatment successfully.
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Vanderklift, Mathew Arie. "Interactions between sea urchins and macroalgae in south-western Australia : testing general predictions in a local context." University of Western Australia. School of Plant Biology, 2002. http://theses.library.uwa.edu.au/adt-WU2004.0086.
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Generalist herbivores profoundly influence the biomass and species composition of macroalgae assemblages. In subtidal ecosystems of temperate latitudes, large invertebrates are usually the most influential herbivores. I tested the prediction that exclusion of invertebrate herbivores would lead to changes in the biomass and species composition of the macroalgae assemblages that are a prominent feature of the reefs in south-western Australia. The most abundant invertebrate herbivores were sea urchins (Heliocidaris erythrogramma, Phyllacanthus irregularis and Centrostephanus tenuispinus), and these occupied different trophic positions. Heliocidaris was present at virtually all reefs surveyed, and was particularly abundant in the Fremantle region. Analyses of stable isotopes and direct observations of gut contents revealed that it was almost exclusively herbivorous, and that it mainly ate foliose brown algae. In contrast, Phyllacanthus and Centrostephanus were omnivorous; while they consumed large proportions of algae, a substantial proportion of the diet of both species was animal tissue. Because Heliocidaris is a generalist herbivore that occurs at high densities, it could exert a large influence on the macroalgae assemblage. This prediction was tested by a series of press experiments. Contrary to the prediction, Heliocidaris exerted a very minor influence on the biomass, and no detectable influence on the species composition, of attached macroalgae. However, it exerted a major influence on the retention of drift macroalgae and seagrass by trapping and feeding on drift. It exerted a particularly strong influence on retention of the kelp Ecklonia radiata. This kelp was not abundant in the attached algae assemblage (when all plots were pooled it ranked 35th in biomass), but was abundant as drift (ranking 1st). Most of the drift Ecklonia was retained by sea urchins, rather than freely drifting.Herbivorous fish may also influence macroalgae assemblages. To compare the effects of sea urchins versus fish on recruiting and adult macroalgae a 13-month exclusion experiment was conducted. There were no detectable effects of sea urchins (mainly Heliocidaris) on either recruiting or adult macroalgae. There were some patterns in the biomass of recruiting algae consistent with an influence by herbivorous fish; however, these patterns were also consistent with the presence of artefacts (shading and reduced water flow) by fish exclusion devices. I began with the prediction that large invertebrate herbivores were a major influence on the macroalgae assemblages of subtidal reefs in south-western Australia. Overall, there was little evidence to support this prediction: within spatial extents of tens of square metres and over periods of 1-2 years, only minor effects were detected. However, it remains plausible that herbivores exert an influence over long time periods across large spatial extents in south-western Australia. I propose that trophic subsidies support the comparatively high densities of Heliocidaris that exist at some reefs. I further propose that these subsidies mediate the effects of sea urchins on the attached macroalgae assemblage, and that they might play an important role in energy and nutrient cycling in these nearshore ecosystems.
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Connor, Carmela F. "Psychological sequelae of predictive testing in Huntington's disease in Western Australia and New South Wales." Thesis, Connor, Carmela F. (1999) Psychological sequelae of predictive testing in Huntington's disease in Western Australia and New South Wales. Professional Doctorate thesis, Murdoch University, 1999. https://researchrepository.murdoch.edu.au/id/eprint/52306/.
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While there has been extensive investigation of the psychological consequences of Predictive Testing (PT) in Huntington’s Disease (HD) in overseas populations, there is a need to improve our understanding of how receiving a PT result affects the Australian client and their family. The current investigation comprised three studies.
Study 1 involved retrospectively following up all applicants, and their partners, enrolled in the West Australian (WA) and New South Wales (NSW) HD PT Programmes (n = 79). The long-term psychosocial sequelae of applicants were explored in an effort to determine whether there were any differences between carriers and non-carriers. Secondly, factors that were significantly associated with psychological distress following a PT result were identified. Support was found for the hypothesis that at least 10% of carriers and non-carriers would obtain clinically significant scores on measures of psychological distress (Spielberger Anxiety Scale [STAI], Impact of Event Scale [IES], & General Health Questionnaire [GHQ]). Carriers were more likely than non-carriers to experience clinically abnormal scores, especially with regard to STAI (State) and the dimensions of intrusion and avoidance on the IES.
Study 2 involved assessing the frequency and nature of adverse reactions that developed in applicants who had undergone PT in WA by analysing clinic case notes (n = 119). An Adverse Event (AE) was considered to have occurred if the applicant experienced any of the following: depression, anxiety, suicidal ideation or attempt, guilt, psychiatric hospitalisation, breakdown in relationships, and substance abuse. Support was found for the hypothesis that the rate of AE’s found in WA would be higher than 10% for both carriers and non-carriers, as approximately 21 % of the sample experienced an AE. In particular, it was found that carriers were significantly more likely than non-carriers to experience an increase in substance abuse, relationship breakdown, clinical depression, suicidal ideation, and anxiety. Conversely, noncarriers were more likely to report feelings of guilt at 'surviving' the HD gene.
Study 3 was an exploratory study, investigating the nature and pattern of psychosocial sequelae that developed in PT applicants in WA over a 12 to 18 month period, by administering measures of psychological distress at baseline and various intervals post-result. As a full data set was obtained for only 6 individuals it was not possible to address the initial hypotheses. Nevertheless, the case study approach did provide some insight into how PT applicants in WA adjusted to coping with their result status. Overall, the findings were consistent with the first two studies in that at least 10% of carriers and non-carriers obtained clinically significant scores on measures of psychological distress (Beck Depression Inventory [BDI], STAI, IBS, GHQ, Social Support Questionnaire), with carriers more likely than non-carriers to experience clinically abnormal scores.
In conclusion, the results of the three studies indicate that PT for HD in WA and NSW results in considerable psychosocial consequences for the participants. This contrasts with overseas research and the growing perception that PT in HD is a relatively harmless procedure with few adverse consequences (Bundey, 1997). The implications of these findings are presented, as well as an outline of the methodological limitations of this investigation and suggestions for future research.
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Chow, Chi Ngok. "Modelling the structure of Australian Wool Auction prices." Thesis, Curtin University, 2010. http://hdl.handle.net/20.500.11937/1225.
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The largest wool exporter in the world is Australia, where wool being a major export is worth over AUD $2 billion per year and constitutes about 17 per cent of all agricultural exports. Most Australian wool is sold by auctions in three regional centres. The prices paid in these auction markets are used by the Australian production and service sectors to identify the quality preferences of the international retail markets and the intermediate processors. One ongoing problem faced by wool growers has been the lack of clear market signals on the relative importance of wool attributes with respect to the price they receive at auction. The goal of our research is to model the structure of Australian wool auction prices. We aim to optimise the information that can be extracted and used by the production and service sectors in producing and distributing the raw wool clip.Most of the previous methods of modelling and predicting wool auction prices employed by the industry have involved multiple-linear regressions. These methods have proven to be inadequate because they have too many assumptions and deficiencies. This has prompted alternative approaches such as neural networks and tree-based regression methods. In this thesis we discuss these alternative approaches. We observe that neural network methods offer good prediction accuracy of price but give minimal understanding of the price driving variables. On the other hand, tree-based regression methods offer good interpretability of the price driving characteristics but do not give good prediction accuracy of price. This motivates a hybrid approach that combines the best of the tree-based methods and neural networks, offering both prediction accuracy and interpretability.Additionally, there also exists a wool specifications problem. Industrial sorting of wool during harvest, and at the start of processing, assembles wool in bins according to the required wool specifications. At present this assembly is done by constraining the range of all specifications in each bin, and having either a very large number of bins, or a large variance of characteristics within each bin. Multiple-linear regression on price does not provide additional useful information that would streamline this process, nor does it assist in delineating the specifications of individual bins.In this thesis we will present a hybrid modular approach combining the interpretability of a regression tree with the prediction accuracy of neural networks. Our procedure was inspired by Breiman and Shang’s idea of a “representer tree” (also known as a “born again tree”) but with two main modifications: 1) we use a much more accurate Neural Network in place of a multiple tree method, and 2) we use our own modified smearing method which involves adding Gaussian noise. Our methodology has not previously been used for wool auction data and the accompanying price prediction problem. The numeric predictions from our method are highly competitive with other methods. Our method also provides an unprecedented level of clarity and interpretability of the price driving variables in the form of tree diagrams, and the tabular form of these trees developed in our research. These are extremely useful for wool growers and other casual observers who may not have a higher level understanding of modelling and mathematics. This method is also highly modular and can be continually extended and improved. We will detail this approach and illustrate it with real data.The more accurate modelling and analysis helps wool growers to better understand the market behaviour. If the important factors are identified, then effective strategies can be developed to maximise return to the growers.In Chapter 1 of this thesis, we present a brief overview of the Australian wool auction market. We then discuss the problems faced by the wool growers and their significance, which motivate our research.In Chapter 2, we define the predictive aspect of the modelling problem and present the data that is available to us for our research. We introduce the assumptions that must be made in order to model the auction data and predict the wool prices.Chapter 3 discusses neural networks and their potential in our wool auction problem. Neural networks are known to give good results in many modern applications resolving industrial problems. As a result of the popularity of such methods and the ongoing development of them, our research partner, the Department of Agriculture and Food, Government of Western Australia, performed a preliminary investigation into neural networks and found them to give satisfactory predictions of wool auction prices. In our Chapter 3, we perform an analysis and assessment of neural networks, specifically, the generalised regression neural networks (GRNN). We look at the strengths and weaknesses of GRNN, and apply them to the wool auction problem and comment on their relevance and usability in our wool problem. We detail the problems we face, and why neural networks alone may not be the best approach for the wool auction problem, thus laying the foundation for the development of our hybrid modular approach in Chapter 5. We also use the numerical prediction results from GRNN as the benchmark in our comparisons of different modelling methods in the rest of this thesis.Chapter 4 details the tree-based regression methods, as an alternate approach to neural networks. In analysing the tree-based methods with our wool auction data, we illustrate the tree methods’ advantages over neural networks, as well as the trade-offs, with our auction data. We also demonstrate how powerful and useful a tree diagram can be to the wool auction problem. And in this Chapter, we improve a typical tree diagram further by introducing our own tabular form of the tree, which can be of immerse use to wool growers. In particular, we can use our tabular form to solve the wool specification problem mentioned earlier, and we incorporate this tabular form as part of a new hybrid methodology in Chapter 5. In Chapter 4 we also consider the ensemble methods such as bootstrap aggregating (bagging) and random forests, and discuss their results. We demonstrate that, the ensemble methods provide higher prediction accuracies than ordinary regression trees by introducing many trees into the model. But this is at the expense of losing the simplicity and clarity of having only a single tree. However, the study of assemble methods do end up providing an excellent idea for our hybrid approach in Chapter 5.Chapter 5 details the new hybrid approach we developed as a result of our work in Chapters 3 and 4 using neural networks and tree-based regression methods. Our hybrid approach combines the two methods with their respective strengths. We apply our new approach to the data, compare the results with our earlier work in neural networks and tree-based regression methods, then discuss the results.Finally, we conclude our thesis with Chapter 6, discussing the potential of our new hybrid approach and the directions of possible future works.
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Fawcett, Derek. "Measurement and prediction of speed of sound, with application to gas flow metering in Australian natural gases." Thesis, Fawcett, Derek (1995) Measurement and prediction of speed of sound, with application to gas flow metering in Australian natural gases. PhD thesis, Murdoch University, 1995. https://researchrepository.murdoch.edu.au/id/eprint/42395/.
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Natural gas custody transfer between buyer and seller is now commonly based upon energy content. Measurement of energy transferred requires simultaneous measurement of volume flow, density and composition of natural gas in high pressure pipelines. Densitometers are used to determine the density of the pipeline gas. Densitometers, however, are subject to systematic errors, and the minimisation of this error requires an accurate measurement of the speed of sound within the gas.
This research investigation has developed an apparatus which is believed to be W1ique. It consists of four interconnected spherical pressure vessels, forming a Differential Burnett apparatus. Sequential isothermal expansions of a gas sample between the vessels allows the accurate determination of a (P,Z) isotherm, either directly, or by comparison to a reference gas. Each of the spheres is equipped with an acoustical source and receiver, and can thus act as an independent spherical acoustic resonator allowing the precise measurement of the speed of sound in the gas. The ability to conduct the volumetric measurements simultaneously with the acoustic measurements is the unique feature of this apparatus.
Measurements have been conducted in this apparatus with the pure gases He, N2 and CH4, for which there is a wealth of high quality PVT and speed of sound data. These measurements were conducted in order to calibrate the apparatus volumes and to determine the magnitude of a number of small correction factors required in the modelling of the acoustic response of the spheres. Comparison between the literature data and our measurements on these pure gases also provided a stringent check on the performance of our apparatus and the measurement accuracies attainable.
Following this detailed characterisation of our apparatus, acoustic and volumetric measurements were made on natural gas samples on a number of isotherms over a wide pressure range. These measurements have provided extensive data on various natural gas thermophysical properties - speed of sound, compressibility factor, isentropic exponent and virial coefficients.
The resulting thermophysical property information has been used by the industry partner in this research {AlintaGas} to correctly calibrate pipeline densitometers and in other areas of high pressure gas flow metering.
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McEniery, Michelle. "Predicting early retirement from organisational variables : should I stay or should I go? /." [St. Lucia, Qld.], 2006. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe19338.pdf.
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Ruddy, Joshua D. "Predictive modelling of self-reported wellness and the risk of injury in elite Australian footballers." Phd thesis, Australian Catholic University, 2020. https://acuresearchbank.acu.edu.au/download/9fc2c9d8146dd478d146ed145468baa828d7ec88a9f41a7ff2222306d7768403/4540065/Ruddy_2020_Predictive_modelling_self-reportred_wellness_Australian.pdf.
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Injuries are a common occurrence in team sports and can have significant financial, physical and psychological consequences for athletes and their sporting organisations. As such, an abundance of research has attempted to identify factors associated with the risk of injury, which is important when developing injury prevention and risk mitigation strategies. Traditionally, research has implemented reductionist approaches to identify injury risk factors. These reductionist methodologies assume that all the parts of a system (in this case, injury aetiology) can be broken down and examined individually and then summed together to represent the system as a whole. Reductionist approaches are useful in establishing associations between specific factors and the risk of injury. However, in order to predict the occurrence of injuries at an individual level, complex approaches should be implemented. In light of this, machine learning has been suggested as an appropriate method of applying complex approaches to the prediction of injuries in sport. Machine learning is a field of computer science which involves building algorithms to learn from data and make predictions without being programmed what to look for or where to look for it. Whilst machine learning cannot be used to establish causal relationships between specific factors and the occurrence of injuries, it differs from reductionist methodologies in that it has the ability to identify the complex, non-linear interactions that occur amongst risk factors.
Study 1 (Chapter 4) aimed to utilise machine learning methods to predict the occurrence of hamstring strain injuries (HSIs) in elite Australian footballers. Hamstring strain injury is the most common injury in elite Australian football and three of the most consistently identified risk factors for HSI are increasing age, prior HSI and low levels of eccentric knee flexor strength. While some iterations of the predictive models achieved near perfect performance (maximum area under the curve [AUC] = 0.92), others performed worse than random chance (minimum AUC = 0.24). It was concluded that age, previous HSI and eccentric knee flexor strength data could not be used to identify Australian footballers at an increased risk of HSI with any consistency, despite these factors being highly associated with the risk of HSI.
It is suggested that more observed injuries, in addition to more frequent measures of the variables included in the models, may have improved the performance of the predictive models in Study 1. To overcome the limitations acknowledged in Study 1, Study 2 (Chapter 5) investigated whether more frequent measures of the impact of prior injury (in the form of session availability), in addition to a greater number of observed injuries (albeit non-specific pathologies), improved the ability to identify injury risk. It was observed that greater session availability in the previous 7 days increased injury probabilities by up to 4.4%. Additionally, lesser session availability in the previous 84 days increased injury probabilities by up to 14.1%, only when coupled with greater availability in the previous 7 days. It was concluded that session availability may provide an informative marker of the impact of prior injury on subsequent injury risk and can be used by practitioners to guide the progression of training, particularly for athletes that are returning from long periods of injury.
Study 1 and Study 2 implemented complex approaches in an attempt to improve injury risk identification at an individual level. Despite the findings of Study 1 and Study 2, quantifying injury risk on a daily basis remains a complex and challenging task for practitioners working in Australian football. Commonly implemented tools such as self-reported wellness questionnaires provide a much more accessible measure of athletes’ wellbeing and how they are responding to the demands of training/competition. Whilst improving the ability to estimate injury risk at an individual level is an important focus area, it may also be important to determine the level of information that more accessible and more frequently measured variables (such as self-reported wellness) provide regarding injury risk. To make this determination, however, it is also necessary to understand the factors that directly influence self-reported wellness. Accordingly, Study 3 (Chapter 6) aimed to investigate the factors that impact wellness in elite Australian footballers. Measures of external load examined on their own were able to explain changes in wellness to a large degree (root mean square error = 1.55, 95% confidence intervals = 1.52 to 1.57). However, there was a proportion of wellness that could not be explained by external loads.
It is suggested that examining the interaction between external training loads and self-reported wellness may assist practitioners in their load management strategies. However, there is limited research investigating the interaction between external loads and wellness and the impact this information may have on subsequent injury risk. Accordingly, Study 4 (Chapter 7) aimed to investigate the ability of external load data, session availability data and self-reported wellness data, as well as the interaction between the three, to identify the risk of lower limb non-contact injuries in elite Australian footballers. The model with the least input variables (athlete ID and session type) displayed the highest predictive ability (AUC = 0.76, Akaike information criterion [AIC] = 479, Brier score = 0.009). The models built using external load, session availability and wellness data all displayed similar predictive ability (AUCs = 0.72 to 0.75, AICs = 477 to 478, Brier scores = 0.009 to 0.009). Despite observing higher predictive performance compared to previous research, the addition of external load, session availability and wellness data, as well as demographic and pre-season external load data, did not improve the ability to predict lower limb non-contact injuries in Study 4.
Overall, this program of research displayed a limited ability to predict injuries in elite Australian football. The findings of this thesis highlight a need for a larger number of observed injuries when implementing predictive modelling strategies to identify injury risk at an individual level. Despite this, the predictive modelling strategies implemented in this thesis may assist researchers and practitioners in better understanding the relationships that exist between variables that are commonly collected, analysed and interpreted. Whilst the efficacy of complex approaches and their application in sports research may warrant further investigation, researchers and practitioners alike need to strongly consider the limitations of input data and the predictive modelling strategies used to analyse these data when conducting (as well as interpreting) future research.
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Samsonova, Maria. "Tropicalisation of temperate seagrass meadows in Western Australia: Predicting the impact of tropical herbivorous fishes on temperate seagrass meadows." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2020. https://ro.ecu.edu.au/theses/2294.
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Rising sea temperatures through climate change produce shifts in the distribution of tropical species to temperate regions, a process termed “tropicalisation”. The poleward expansion of tropical herbivores into temperate seagrass meadows is predicted to increase grazing pressure and alter ecosystem services and processes in these seagrass systems. This study attempted to examine the effects of tropicalisation on temperate seagrass meadows along the western coast of Australia, where the increasing abundance of tropical consumers such as the herbivorous Siganus fuscescens has already been documented. Through the assessment of fish assemblages in seagrass meadows and the grazing levels on seagrass in 2001 and 2016/17, as well as in situ and mesocosm feeding preference experiments, this study attempted to estimate the grazing rates and impact that the growing abundance of S. fuscescens may have in temperate seagrass meadows.
Shifts in the grazing rates on seagrass between 2001 and 2016/17 were inconsistent, varying between seagrass species and location. Based on observational data on the bites on seagrass leaves, rates of consumption increased for Posidonia sinuosa while no similar pattern was found for Posidonia australis. This was despite an apparent greater consumption on P. australis compared to P. sinuosa in 2001, and the minimal amount of grazing on tethered seagrass. The higher observed level of P. sinuosa consumption in 2016/17 is likely explained by the changed herbivorous fish species composition, even though no fish were clearly observed feeding on seagrass in the current study. The tropical herbivore S. fuscescens was more abundant in 2016/17 that 2001, although abundances were patchy and no fish was observed feeding on seagrass. The higher level of P. sinuosa consumption in 2016/17, compared to 2001, supports the prediction that with increasing abundances in temperate seagrass ecosystems, tropical herbivores will enhance the consumption of seagrass. However, seagrass consumption is likely to be strongly influenced by the availability of macroalgae which were shown as the preferred food sources.
Feeding trials in mesocosms were compromised by the large number of deaths and the limited grazing on natural food sources by S. fuscescens, suggesting that the population in the Perth region is susceptible to adverse handling and husbandry effects. To maximise the survival rate of captured fish, the fishing and handling procedures were altered to adapt to the ongoing observations in the response of fish to handling in the field or in the mesocosm facilities. Lesson learned from the capture, handling and husbandry of S. fuscescens in feeding trials in the current study will hopefully provide greater success for feeding preference experiments in the future. The sampling program initiated in 2001 and repeated in 2016/17 provides base-line data and the opportunity to monitor and track the shift in abundances of tropical herbivores and resultant increases in grazing rates to test the above predictions. The consequences of tropicalisation will depend on the variety of abiotic and biotic factors, including the fish assemblages in the area, the abundance of tropical species, the availability of food, and the feeding preferences that invading species will develop in response to the changed environmental conditions.
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Ghaiyed, Andrew Peter. "A genomic ancestry panel for Australian and Japanese WWII military remains recovered in the Asia-Pacific." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/211296/1/Andrew_Ghaiyed_Thesis.pdf.
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The Ghaiyed population-specific panel (GPSP) is an ancestry prediction strategy comprised of ancestry-informative DNA markers that was developed to assist Unrecovered War Casualties-Army (UWC-A) in the accounting of historical military remains. The GPSP was able to significantly increase the proportion of individuals that could be assigned ancestry compared to conventional methods used by the Forensic Science community and previous UWC-A methodology. The GPSP is supported by the novel application of admixture simulation tools and a modified Chi-square Automatic Interaction Detector/Probability Decision Tree (CHAID/PDT) method for ancestry classification, to more reliably account for the remains of those fallen in previous conflicts.
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Baxter, Katrina. "Linking seafloor mapping and ecological models to improve classification of marine habitats : opportunities and lessons learnt in the Recherche Archipelago, Western Australia." University of Western Australia. School of Plant Biology, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0181.
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[Truncated abstract] Spatially explicit marine habitat data is required for effective resource planning and management across large areas, although mapped boundaries typically lack rigour in explaining what factors influence habitat distributions. Accurate, quantitative methods are needed. In this thesis I aimed to assess the utility of ecological models to determine what factors limit the spatial extent of marine habitats. I assessed what types of modeling methods were able to produce the most accurate predictions and what influenced model results. To achieve this, initially a broad scale marine habitat survey was undertaken in the Recherche Archipelago, on the south coast of Western Australia using video and sidescan sonar. Broad and more detailed functional habitats types were mapped for 1054km2 of the Archipelago. Broad habitats included high and low profile reefs, sand, seagrass and extensive rhodolith beds, although considerable variation could be identified from video within these broad types. Different densities of seagrass were identified and reefs were dominated by macroalgae, filter feeder communities, or a combination of both. Geophysical characteristics (depth, substrate, relief) and dominant benthic biota were recorded and then modelled using decision trees and a combination of generalised additive models (GAMs) and generalised linear models (GLMs) to determine the factors influencing broad and functional habitat variation. Models were developed for the entire Archipelago (n=2769) and a subset of data in Esperance Bay (n=797), which included exposure to wave conditions (mean maximum wave height and mean maximum shear stress) calculated from oceanographic models. Additional distance variables from the mainland and islands were also derived and used as model inputs for both datasets. Model performance varied across habitats, with no one method better than the other in terms of overall model accuracy for each habitat type, although prevalent classes (>20%) such as high profile reefs with macroalgae and dense seagrass were the most reliable (Area Under the Curve >0.7). ... This highlighted not only issues of data prevalence, but also how ecological models can be used to test the reliability of classification schemes. Care should be taken when mapping predicted habitat occurrence with broad habitat models. It should not be assumed that all habitats within the type will be defined spatially, as this may result in the distribution of distinctive and unique habitats such as filterfeeders being underestimated or not identified at all. More data is needed to improve prediction of these habitats. Despite the limitations identified, the results provide direction for future field sampling to ensure appropriate variables are sampled and classification schemes are carefully designed to improve descriptions of habitat distributions. Reliable habitat models that make ecological sense will assist future assessments of biodiversity within habitats as well as provide improved data on the probability of habitat occurrence. This data and the methods developed will be a valuable resource for reserve selection models that prioritise sites for management and planning of marine protected areas.
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Ji, Inyeob Economics Australian School of Business UNSW. "Essays on testing some predictions of RBC models and the stationarity of real interest rates." Publisher:University of New South Wales. Economics, 2008. http://handle.unsw.edu.au/1959.4/41441.
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This dissertation contains a series of essays that provide empirical evidence for Australia on some fundamental predictions of real business cycle models and on the convergence and persistence of real interest rates. Chapter 1 provides a brief introduction to the issues examined in each chapter and provides an overview of the methodologies that are used. Tests of various basic predictions of standard real business cycle models for Australia are presented in Chapters 2, 3 and 4. Chapter 2 considers the question of great ratios for Australia. These are ratios of macroeconomic variables that are predicted by standard models to be stationary in the steady state. Using time series econometric techniques (unit root tests and cointegration tests) Australia great ratios are examined. In Chapter 3 a more restrictive implication of real business cycle models than the existence of great ratios is considered. Following the methodology proposed by Canova, Finn and Pagan (1994) the equilibrium decision rules for some standard real business cycle are tested on Australian data. The final essay on this topic is presented in Chapter 4. In this chapter a large-country, small-country is used to try and understand the reason for the sharp rise in Australia??s share of world output that began around 1990. Chapter 5 discusses real interest rate linkages in the Pacific Basin region. Vector autoregressive models and bootstrap methods are adopted to study financial linkages between East Asian markets, Japan and US. Given the apparent non-stationarity of real interest rates a related issue is examined in Chapter 6, viz. the persistence of international real interest rates and estimation of their half-life. Half-life is selected as a means of measuring persistence of real rates. Bootstrap methods are employed to overcome small sample issues in the estimation and a non-standard statistical inference methodology (Highest Density Regions) is adopted. Chapter 7 reapplies the High Density Regions methodology and bootstrap half-life estimation to the data used in Chapters 2 and 5. This provides a robustness check on the results of standard unit root tests that were applied to the data in those chapters. Main findings of the thesis are as follows. The long run implications of real business cycle models are largely rejected by the Australia data. This finding holds for both the existence of great ratios and when the explicit decision rules are employed. When the small open economy features of the Australian economy are incorporated in a two country RBC model, a country-specific productivity boom seems to provide a possible explanation for the rise in Australia??s share of world output. The essays that examine real interest rates suggest the following results. Following the East Asian financial crisis in 1997-98 there appears to have been a decline in the importance of Japan in influencing developments in the Pacific Basin region. In addition there is evidence that following the crisis Korea??s financial market became less insular and more integrated with the US. Finally results obtained from the half-life estimators suggest that despite the usual findings from unit root tests, real interest rates may in fact exhibit mean-reversion.
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Woods, Carl T. C. "The development of an objective multi-dimensional approach to talent identification in junior Australian football." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2015. https://ro.ecu.edu.au/theses/1672.
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Talent identification (TID) is a pertinent component of the sports science discipline given the considerable influence it may have within the pursuit of excellence. Thus, research has attempted to identify the determinants of a talented performance through the use of objective testing procedures. However, many of these ‘traditional’ approaches have been operationalised by mono-dimensional objective physical performance tests that do not inherently account for the multi-dimensional requisites of game-play, particularly within a team sporting context. This is problematic when attempting to identify talent, as a successful performance in team sports is often the combination of physical, technical and tactical elements. For example, a physically inferior junior may still succeed against their physically superior counterparts given additional technical and tactical skills; commonly referred to as a compensation phenomenon. Hence, forecasting longitudinal performance based upon one element of effective play (e.g. physical) will likely lead to an unsubstantiated and biased identification.
Despite the aforementioned, TID practices in junior Australian football (AF) are predominately facilitated by physically biased objective performance tests. Given the combative nature of game-play, physicality is an important attribute, but solely basing identification and selection on isolated physical attributes can be misleading given the previously mentioned compensation phenomenon. This mono-dimensionality is somewhat expected as to date there is a scarcity of objective tests measuring the multidimensional characteristics of AF game-play. Thus, through the consolidation of a number of theoretical concepts and recommendations proposed within the literature, this thesis aimed to develop a multi-dimensional objective approach to TID in junior AF, and in doing so, identify the determinants of a talented performance.
To address this aim, objective physical, technical and tactical measurements were taken on both talent identified and non-talent identified junior AF players through the use of representative performance tests. Indeed, this reflected the first stage of the Expert Performance Approach (Ericsson & Williams, 1991; Williams & Ericsson, 2005) and the Model of a Skilful Player (Launder, 2001). Throughout each research study, talent identified players were defined through participation within the West Australian Football League (WAFL) State Under 18 (U18) Academy (an elite talent development program), whilst non-talent identified players were randomly chosen from the remaining cohort of WAFL U18 players not participating in the State Academy program. Thus, a cross-sectional observational research design was employed for each experimental procedure used throughout this thesis. It is of note that the first three studies utilised players from the 2013 sample, whilst the fourth research study utilised players from the 2014 sample.
In the first of four research studies, a range of sport specific physical characteristics were found to differ between talent identified and non-talent identified junior AF players. However, a binary logistic regression model indicated that it was the measurements of standing height, lower body power and maximal aerobic capacity that provided the greatest prediction of talent, and thus important physical determinants of talent in AF at an U18 level.
The second study investigated if measurements of technical skill could be used to accurately identify talent in junior AF. Despite the range of technical skills required in AF, the two modes of ball disposal (kicking and handballing) have been deemed critical for success based upon recent research (Parrington, Ball, MacMahon, 2013; Sullivan et al., 2014). Consequently, two representative skill tests were described; the Australian Football Kicking (AFK) test and the Australian Football Handballing (AFHB) test. Results indicated that the majority of the talent identified players possessed superior ball disposal skills in comparison to their non-talent identified counterparts. Specifically, measures of accuracy and ball speed on both the dominant and non-dominant sides reflected the strongest prediction of talent for the AFK test, and measures of accuracy on both dominant and non-dominant sides reflected the strongest prediction of talent for the AFHB test. These results reinforced the construct of each test, and highlighted their effectiveness for use as an objective TID tool in AF.
Research had yet to investigate if decision-making skill was predictive of talent in junior AF despite its suggested importance for the exhibition of an expert performance in the game. The third study in this research series attempted to fill this remaining gap and objectively quantify decision-making skill through the use of a video-based decision-making task. In order to construct such a task, video footage was obtained from the Australian Football League (AFL) using an aerial behind-the-goal camera perspective. Through the use of an expert coaching panel, 26 clips out of an initial sample of 52 were deemed applicable, as each consisted of approximately three to five possible decision-making options. Results indicated that the talent identified players performed the task more accurately in comparison to their non-talent identified counterparts, and was thus a valuable objective tool for identifying talent at an U18
level.
The fourth and final study in this research series investigated if the application of a multi-dimensional battery of objective performance tests provided more accurate TID in AF when compared to isolated performance measures. The construction of this test battery was informed by the results of studies one, two and three, but to ensure the translation of this test battery, it was applied to the 2014 U18 cohort, not the 2013 cohort which was done in the previous studies. However, the definition of talent identified and non-talent identified remained consistent with the previous studies. Results indicated that the majority of the talent identified players possessed a superior combination of physical, technical and tactical characteristics in comparison to their non-talent identified counterparts. Specifically, a receiver operating curve indicated a classification accuracy of 95% when summating the total scores obtained for each physical, technical and tactical test. This classification accuracy supports the implementation of multi-dimensional objective designs over the traditional monodimensional designs when attempting to identify talent in team sporting contexts.
This thesis was motivated by the need to enhance the accuracy and reliability of current TID practices in AF by developing an objective multi-dimensional approach. In doing so, it contributes an important body of research to the study of TID by providing a conceptually translatable means in which the development of such an approach can be undertaken in other team sports.
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Amein, Hussein Aly Abbass. "Computational intelligence techniques for decision making : with applications to the dairy industry." Thesis, Queensland University of Technology, 2000. https://eprints.qut.edu.au/36867/1/36867_Digitised%20Thesis.pdf.
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Zhou, Huaqiong. "Development of predictive models for paediatric unplanned hospital readmissions: A mixed-methods sequential explanatory study at a tertiary children’s hospital in Western Australia." Thesis, Curtin University, 2021. http://hdl.handle.net/20.500.11937/85885.
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A mixed-methods sequential explanatory research design, collecting quantitative and qualitative data, examined paediatric unplanned hospital readmissions and nurse-caregiver communication of hospital-to-home transition information at a tertiary children’s hospital in Western Australia. The thesis is presented as seven peer-reviewed journal publications, including three comprehensive literature analyses and four primary studies. Research outcomes confirmed the complexities associated with developing predictive models, inconsistent content and delivery of transition information and the need to implement a comprehensive transition framework.
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Getley, Ian L. Department of Aviation Faculty of Science UNSW. "Cosmic and solar radiation monitoring of Australian commercial flight crew at high southern latitudes as measured and compared to predictive computer modelling." Awarded by:University of New South Wales, 2007. http://handle.unsw.edu.au/1959.4/40536.
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This study set out to examine the levels of galactic cosmic radiation exposure to Australian aircrew during routine flight operations, with particular attention to the high southern latitude flights between Australia and South Africa. Latitudes as high as 65?? South were flown to gain the data and are typical of the normal flight routes flown between Sydney and Johannesburg on a daily basis. In achieving this objective it became evident that suitable commercially available radiation monitoring equipment was not readily available and scientific radiation monitors were sourced from overseas research facilities to compliment my own FH4lB and Liulin monitors provided by UNSW. At the same time it became apparent that several predictive codes had been developed to attempt to model the radiation doses received by aircrew based on flight route, latitudes and altitudes. Further, it became apparent that these codes had not been subjected to verification at high southern latitudes and that they had not been validated for the effects of solar particle events. Initially measurements were required at the high latitudes followed by mid-latitude data to further balance the PCAIRE code to ensure reasonableness of results for both equatorial and high latitudes. Whilst undertaking this study new scientific monitors became available which provided an opportunity to observe comparative data and results. The Liulin, QDOS and a number of smaller personal dosimeters were subsequently obtained and evaluated. This appears to be the first time that such an extensive cross comparison of these monitors has been conducted over such a wide range of latitudes and altitudes. During the course of this study a fortuitous encounter with GLE 66 enabled several aspects of code validation to be examined, namely the inability of predictive codes to estimate the increased dose associated with a GLE or the effects of a Forbush decrease on the code results. Finally I review the known biological effects as discussed by numerous authors based on current epidemiological studies, with a view to high-lighting were the advent of future technology in aviation may project aircrew dose levels.
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Humphreys, Abbey. "Predicting the Impact of Sea Level Rise on the Distribution of Phragmites Australis and Spartina Alterniflora and Changes in Community Compositions in Tidal Freshwater Marshes of James City County, Va." W&M ScholarWorks, 2017. https://scholarworks.wm.edu/etd/1516639677.
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With ongoing sea level rise (SLR), tidal freshwater marshes (TFMs) eventually will be flooded with more brackish water. The impact of more water and salt on the plant community of TFMs, however, is unknown. With SLR, both the invasive reed Phragmites australis and the native salt marsh grass Spartina alterniflora could become dominant species in TFMs. I am looking at determining how increases in salinity and inundation caused by sea level rise will impact the relative distribution of Phragmites and Spartina in tidal freshwater marshes in Southeastern Virginia. Using GIS, I summarized past expansion patterns by mapping the current and historical distribution of Phragmites and Spartina. With soil samples collected from 6 TFMs in James City County with established Phragmites stand, I tested the effects of salinity and flooding on the germination of Phragmites and Spartina seeds and the subsequent effects of competition with these conditions. Inundation positively impacted the abundance of Phragmites and Spartina, while competition form Phragmites and Spartina decreased native species richness. Based on germination success and historical distributions, SLR-caused range shifts were predicted for Phragmites and Spartina and suggest Phragmites and Spartina will be more abundant in number within TFMs and in more TFMs in James City County. TFM area across James City County will diminish if accretion rates cannot keep pace with sea level rise and current TFMs will transition to oligohaline marshes, causing significant community changes.
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Son, Kyongho. "Improving model structure and reducing parameter uncertainty in conceptual water balance models with the use of auxiliary data." University of Western Australia. School of Environmental Systems Engineering, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0094.
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[Truncated abstract] The use of uncertainty analysis is gaining considerable attention in catchment hydrological modeling. In particular, the choice of an appropriate model structure, the identifiability of parameter values, and the reduction of model predictive uncertainty are deemed as essential elements of hydrological modelling. The chosen model structure must be parsimonious, and the parameters used must either be derivable from field measured data or inferred unambiguously from analysis of catchment response data. In this thesis, a long-term water balance model for the Susannah Brook catchment in Western Australia has been pursued using the ?downward approach?, which is a systematic approach to determine the model with the minimum level of complexity, with parameter values that in theory are derivable from existing physiographic data relating to the catchment. Through the analysis of the rainfall-runoff response at different timescales, and the exploration of the climate, soil and vegetation controls on the water balance response, an initial model structure was formulated, and a priori model parameter values estimated. Further investigation with the use of auxiliary data such as deuterium concentration in the stream and groundwater level data exposed inadequacies in the model structure. Two more model structures were then proposed and investigated through formulating alternative hypotheses regarding the underlying causes of observed variability, including those associated with the absence of a contribution of deep groundwater flow to the streamflow, which was indicated by deuterium concentration and internal dynamics characterized by the observed groundwater levels. ... These differences are due to differences in the time delay between rainfall and recharge between upland and riparian regions. The ages of water recharging the groundwater and discharging from the catchment were estimated by assuming a piston flow mechanism. In the deeper, upland soils, the age of recharging water was considerably larger than the unsaturated zone delay would suggest; a recharge response 16 days after an infiltration event may involve water as much as 160 days old. On the other hand, the delay and the age of recharging water were much lower in the shallow riparian zone. Where the upland zone contributes significantly to discharge, the predicted difference between the rainfall-discharge response time and the average age of discharging water can be significant.
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Siddiqi, Muhammad Junaid. "Remote sensing and GIS techniques for monitoring and predicting land degradation and impacts of engineering solutions in an area." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/2427.
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Salinity, waterlogging and drought are major causes of land degradation and serious threats to sustainable agricultural productivity in the south-west agricultural region of Western Australia (WA). The spectral signatures of pasture plants under drought, waterlogging and nutrient deficiency were examined in a greenhouse study using both a field and an analytical laboratory spectrometer (400 to 2,500 nm wavelength). Drought stress group (RWC, 39.9%) has the highest reflectance of 48.2%, waterlogging group (RWC, 49.7%) with a magnitude of 43.1% reflectance and control group (RWC, 61.5%) has the lowest of 41.9%. The highest separability based on magnitude among control, waterlogging and drought stress groups is located at reflection band at 1,666 nm, 1,818 nm and 2,216 nm and at 1,450 nm absorption bands. Remote sensing and GIS techniques were used to predict risks of soil salinity and waterlogging in the study area. Time-sequenced Landsat TM satellite data and groundwater data were analysed to delineate areas where major changes in soil salinity, waterlogging have taken place before and after engineering interventions of deep drains.The rainfall data analysis of all cities in the south-west of Western Australia indicate that annual rainfall has been decreasing since 1969 for some cities in the region and rainfall is decreasing in some cities since 1975. The winter season rainfall shows a downward trend and summer season rainfall shows an upward trend linked to an increase in the frequency of summer storm events in the south-west, in the Wheatbelt and in the east of Western Australia. The annual rainfall and summer season rainfalls have been increasing in the north of Western Australia and both annual rainfall and summer season rainfalls show an increasing trend. Climate change was studied for northern, eastern, Wheatbelt and south-west of WA and its impacts of on surface runoff, groundwater recharge, and land degradation were studied.Deep open drains were monitored in the two major drainage districts of Narembeen and Dumbleyung in Wheatbelt of Western Australia. The efficacy of drains in mitigating the problems of waterlogging and salinity in the area was studied. Information on monitoring of drains in six coastal districts in Western Australia, from Australia and other countries was collated and a coastal drainage best management practices ‘BMP Toolbox’ has been developed.
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Watters, Robyn. "Exploring the impacts of organisational change : a structured prediction approach." Thesis, 2011. https://vuir.vu.edu.au/18967/.
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This was a qualitative, single case study that investigated the operational and relational dynamics of a multifaceted change process within a large Australian company. The Company had an extremely complex organisation and supply-chain structure and often its entities were severely impacted by change in a number of different ways, at various levels within the organisation. This set in play a cause and effect scenario of dysfunctional events resulting in supply-chain procedural anomalies and operational inefficiencies. The literature revealed other industry types were also susceptible to change and had suffered operational inefficiencies as a result. This study adopted a multi-theoretical approach to explore the complexity of organisation change with a number of paradigms used to guide the data collection and analysis processes. Moreover, the study combined qualitative case study and systems analysis and design (SA&D) methods in the research design, which added to the quality and reliability of the research findings. The data analysis methods used included triangulation and conceptual modelling.
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Thomas, Mark. "Multiscale prediction of saline-sodic land degradation processes in two South Australian regions." 2007. http://hdl.handle.net/2440/57337.
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Title page, table of contents and abstract only. The complete thesis in print form is available from the University of Adelaide Library.In this thesis, the distribution of saline-sodic properties forming part of a complex pattern of soils in two varied upland agricultural regions in South Asutralia were predicted at multiple scales using DSM and allied approaches.
http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1283986
Thesis (Ph.D.) -- University of Adelaide, School of Earth and Environmental Sciences, 2007
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Thomas, Mark. "Multiscale prediction of saline-sodic land degradation processes in two South Australian regions." Thesis, 2007. http://hdl.handle.net/2440/57337.
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In this thesis, the distribution of saline-sodic properties forming part of a complex pattern of soils in two varied upland agricultural regions in South Asutralia were predicted at multiple scales using DSM and allied approaches.Thesis (Ph.D.) -- University of Adelaide, School of Earth and Environmental Sciences, 2007
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Latimer, Shane Leon. "Characteristics of university students with self-reported learning disabilities on selected measures of basic academic achievement and cognitive ability." Thesis, 1997. http://hdl.handle.net/1885/145349.
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Khanghahi, Houshang Farabi. "A risk-based approach to control of water quality impacts caused by forest road systems." Phd thesis, 2005. http://hdl.handle.net/1885/151699.
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Wong, Geraldine H. "Drought predictions: applications in Australia." Thesis, 2010. http://hdl.handle.net/2440/64290.
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Drought is a global and recurrent natural phenomenon, the inevitable consequence of meteorological variability. This natural hazard brings about devastating effects because water is one of the most fundamental commodities for human survival, and a lack of water can result in varying consequences, from mere inconvenience to life threatening instances. Drought cannot be prevented but its effects can be mitigated through the design of appropriate water resource infrastructure and management strategies. The goal of this thesis is to model the spatial and temporal characteristics of drought occurrence in Australia, the driest continent. In doing so predictions can be made, levels of risk can be evaluated and conditional estimates of drought can be based on climatic state variables.
For insight into the nature of drought in Australia, multivariate models of drought characteristics are developed. Preliminary analysis demonstrates high correlations between several drought characteristics, these are the drought severity, intensity and duration. This thesis applies the copula concept, which is a versatile means of modelling their dependence
structure. Copulas are multivariate uniform distributions, which allow the joint behaviour of variables to be modelled independently from their marginal distributions. This research
extends the application of copulas by investigating the effect of climate variability on copula models and subsequent drought characteristics. Two different copula families are fitted to the drought characteristics to demonstrate the importance of tail dependence when modelling extreme climatic events. An important application of these models is the calculation of return periods of extreme drought events exceeding certain thresholds, taking account of variability in climatic indices.
A second objective is to forecast drought at various spatial resolutions. The most straightforward method are regression and ARMA models that incorporate global climatic indicators. The effect of climatic variation on Australia's precipitation is examined by investigating the association between climatic indices and the multivariate distribution of drought at numerous sites across Australia. Two classification strategies for forecasting rainfall are compared using significance testing based on multiple comparison techniques. Further to this, rainfall forecasting relationships are explored using global sea-surface temperature anomalies.
The versatility of copula models is demonstrated through short-term rainfall predictions for neighbouring rainfall districts, using separate copulas conditioned on antecedent climate
conditions. This technique is shown to improve rainfall predictions in neighbouring districts and improve estimates of drought probability.Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2010
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Yan, Hong. "Frost prediction for Australian tree species in China." Phd thesis, 2001. http://hdl.handle.net/1885/147130.
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Roachanakanan, Raywadee. "Predicting the dynamics of rainforests in Australia." Phd thesis, 2004. http://hdl.handle.net/1885/150227.
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Goda, Hussam M. "Prediction of special core parameters for Australian hydrocarbon basins." Thesis, 2006. http://hdl.handle.net/2440/74882.
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The determination, validation and understanding, and proper use of special core analysis relationships are paramount in the assessment of recovery efficiency of petroleum reservoirs. The most reliable information, resulting in representative relationships, such as for relative permeability and capillary pressure, may be obtained from laboratory experiments. However, being time-consuming and expensive, the number of core samples typically subjected to such investigations tends to be limited, often resulting in data deficiencies and hence improper understanding of the necessary relationships, which are essential for conducting detailed reservoir engineering and simulation studies, with the aim of maximising the extraction of petroleum. For the above reasons, over the past decades, the establishment of mathematical models to predict the required properties has received considerable attention from petroleum engineers, and is one of the active research areas today.
In an attempt to predict valid relationships, difficulties are primarily related to complexity and variability of rocks, in terms of pore structure and mineralogy and associated fundamental properties: porosity, absolute permeability, and fluid saturation. Such variation is a function of the original deposition of grains and subsequent alteration or diagenesis of a geological formation, most notably rock. compaction upon burial, but also other significant alteration, for example the generation of different types of clays, filling part of the pore structure. In addition to pore structure variation, the second complication is associated with the surface chemistry between fluids and the varied rock grains, as well as the interaction between fluids themselves, for example oil and water contained in the pores. Thirdly, in conducting laboratory experiments, the precise experimental conditions may greatly influence results obtained: pressure, temperature and the types of fluids used and their properties, most notably fluid viscosity, flow velocity and interfacial tension. Investigations by co-researchers and others into single-phase flow and the identification of appropriate geological entities, or facies, representative of (homogeneous) flow behaviour, have led to the conclusion that the Carman-Kozeny model is ideally suited to bridge the gap between the differing views of geologists and engineers. As this model is able to elegantly unify the parameters for single phase flow for the majority of petroleum rocks, the formulation was subsequently extended to two phase flow situations by the principal supervisor. These concepts were then utilised in this research and further extended, and a number of new relationships were established, which may be used to validate experimental data and relationships or predict such relationships from more fundamental properties. In deriving the above formulations, an extensive database was utilised, semi-empirically fitting the data for establishing some of the relationships. In other cases the data was used to validate new models, comparing model-generated and experimental results. The database was created by utilising laboratory data generated by commercial laboratories and made available by several petroleum companies, covering onshore and offshore Australian hydrocarbon basins. Both, capillary pressure and relative permeability models were validated using this data, and the new models were demonstrated to have excellent performance in predicting two-phase flow relationships. In a further attempt to validate these models, comparison studies were also conducted with well-known models used by the oil and gas industry. The Brooks and Corey capillary pressure model was used for comparison with the newly established capillary pressure model, and the performance of the new relative permeability model was checked against that of the modified Brook and Corey model, also known as the power law model. Relative permeability and capillary pressure models depend on the primary parameters mentioned above but are actually formulated in terms of several secondary parameters, functions of primary parameters. As such irreducible water saturation is most significant. If this quantity has not been measured in the laboratory, it may be predicted. New models were established to predict irreducible water saturation, based on an artificial neural network approach. A semi-empirical model, based on trapping parameters, was also investigated, resulting in an alternate formulation for irreducible water saturation, and a universal analytical form that should be applicable to the range of geological formations. As mentioned above, relative permeability relationships are also controlled by wettability. For the purpose of predicting relative permeability, a new model to link the USBM wettability index to pore structure parameters was also established by this research. As with relative permeability, capillary pressure and irreducible water saturation models, the model was created and validated using the Australian database. However, the general form of the equation would lend itself for use with any data set. Finally, the ratio of effective (or relative) permeability endpoints may be taken as an indictor of wettability. Equations to predict effective permeability to oil at irreducible water saturation and effective permeability to water at residual oil saturation have been formulated. Both equations are extensions of the Carman-Kozeny formulation.Thesis (Ph.D.) -- University of Adelaide, Australian School of Petroleum, 2006
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Hatangala, Chinthana. "Identifying the Future Directions of Australian Excess Stock Returns and Their Determinants Using Binary Models." Thesis, 2016. https://vuir.vu.edu.au/32888/.
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The predictability of excess stock returns has been debated by researchers over time, with many studies proving that stock returns can be predicted to some extent. To enable an effective investment strategy, it is vital for investors to identify the future directions of stock returns and the factors causing directional changes. This study sought to determine whether Australian monthly excess stock return signs are predictable, and identify the key determinants of Australian monthly excess stock return directions. Three different binary models were considered to predict stock directions: discriminant, logistic and probit models. The predictive powers of benchmark static logistic and probit models were also compared with dynamic, autoregressive and dynamic autoregressive models. In order to identify the key determinants, this study considered various economic, international and financial factors, as well as past volatility measures of explanatory variables. It also tested a United States (US) binary recession indicator and Organisation for Economic Co-operation and Development (OECD) composite leading indicator as explanatory variables in the predictive models.