Relevant bibliographies by topics / Prediction of Australia

Academic literature on the topic 'Prediction of Australia'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Prediction of Australia"

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Cowan, Tim, Matthew Wheeler, and Roger Stone. "Prediction of Northern Australian Rainfall Onset Using the ACCESS-Seasonal Model." Proceedings 36, no. 1 (April 8, 2020): 189. http://dx.doi.org/10.3390/proceedings2019036189.

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The development of the Australian Community Climate Earth-System Simulator-Seasonal version 1 (ACCESS-S1) prediction system signifies a major step in addressing predictive limitations in multi-week to seasonal forecasting. It is anticipated that ACCESS-S1 will provide greater skill in its prediction of the wet season onset and intensity, which are crucial to the viability of cattle grazing across northern Australia. We evaluate the hindcast skill of the ACCESS-S1 for the northern rainfall onset, defined as the date when 50 mm of precipitation has accumulated at a given location from the 1st of September, heralding the start of the seasonal dry-to-wet transition over northern Australia. We show that the raw ACCESS-S1 hindcasts, regridded to a 5 km observed grid, capture the broad-scale features of the median onset, including an early October onset over the western Top End and southeast Queensland. However, the hindcasts fail to capture the later December onsets over central Australia. The greatest improvement in onset skill comes from first calibrating the hindcasts using observations, which outperform the raw model and bias corrected hindcasts over central Australia and the far west in the Pilbara-Gascoyne basin. Based on its simulation of realistic northern rainfall onset dates and variability alone, ACCESS-S1’s prediction performance can be considered an improvement over the older predictive system. As the real-time onset forecasts have were issued using ACCESS-S1 in July 2019, it is expected that the calibrated predictions will help improve the resilience of cattle producers and graziers to drought across northern Australia.
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Lim, Eun-Pa, Harry H. Hendon, David L. T. Anderson, Andrew Charles, and Oscar Alves. "Dynamical, Statistical–Dynamical, and Multimodel Ensemble Forecasts of Australian Spring Season Rainfall." Monthly Weather Review 139, no. 3 (March 1, 2011): 958–75. http://dx.doi.org/10.1175/2010mwr3399.1.

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Abstract The prediction skill of the Australian Bureau of Meteorology dynamical seasonal forecast model Predictive Ocean Atmosphere Model for Australia (POAMA) is assessed for probabilistic forecasts of spring season rainfall in Australia and the feasibility of increasing forecast skill through statistical postprocessing is examined. Two statistical postprocessing techniques are explored: calibrating POAMA prediction of rainfall anomaly against observations and using dynamically predicted mean sea level pressure to infer regional rainfall anomaly over Australia (referred to as “bridging”). A “homogeneous” multimodel ensemble prediction method (HMME) is also introduced that consists of the combination of POAMA’s direct prediction of rainfall anomaly together with the two statistically postprocessed predictions. Using hindcasts for the period 1981–2006, the direct forecasts from POAMA exhibit skill relative to a climatological forecast over broad areas of eastern and southern Australia, where El Niño and the Indian Ocean dipole (whose behavior POAMA can skillfully predict at short lead times) are known to exert a strong influence in austral spring. The calibrated and bridged forecasts, while potentially offering improvement over the direct forecasts because of POAMA’s ability to predict the main drivers of springtime rainfall (e.g., El Niño and the Southern Oscillation), show only limited areas of improvement, mainly because strict cross-validation limits the ability to capitalize on relatively modest predictive signals with short record lengths. However, when POAMA and the two statistical–dynamical rainfall forecasts are combined in the HMME, higher deterministic and probabilistic skill is achieved over any of the single models, which suggests the HMME is another useful method to calibrate dynamical model forecasts.
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Li, Chen, Jing-Jia Luo, Shuanglin Li, Harry Hendon, Oscar Alves, and Craig MacLachlan. "Multimodel Prediction Skills of the Somali and Maritime Continent Cross-Equatorial Flows." Journal of Climate 31, no. 6 (March 2018): 2445–64. http://dx.doi.org/10.1175/jcli-d-17-0272.1.

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Predictive skills of the Somali cross-equatorial flow (CEF) and the Maritime Continent (MC) CEF during boreal summer are assessed using three ensemble seasonal forecasting systems, including the coarse-resolution Predictive Ocean Atmospheric Model for Australia (POAMA, version 2), the intermediate-resolution Scale Interaction Experiment–Frontier Research Center for Global Change (SINTEX-F), and the high-resolution seasonal prediction version of the Australian Community Climate and Earth System Simulator (ACCESS-S1) model. Retrospective prediction results suggest that prediction of the Somali CEF is more challenging than that of the MC CEF. While both the individual models and the multimodel ensemble (MME) mean show useful skill (with the anomaly correlation coefficient being above 0.5) in predicting the MC CEF up to 5-month lead, only ACCESS-S1 and the MME can skillfully predict the Somali CEF up to 2-month lead. Encouragingly, the CEF seesaw index (defined as the difference of the two CEFs as a measure of the negative phase relation between them) can be skillfully predicted up to 4–5 months ahead by SINTEX-F, ACCESS-S1, and the MME. Among the three models, the high-resolution ACCESS-S1 model generally shows the highest skill in predicting the individual CEFs, the CEF seesaw, as well as the CEF seesaw index–related precipitation anomaly pattern in Asia and northern Australia. Consistent with the strong influence of ENSO on the CEFs, the skill in predicting the CEFs depends on the model’s ability in predicting not only the eastern Pacific SST anomaly but also the anomalous Walker circulation that brings ENSO’s influence to bear on the CEFs.
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Rathore, Saurabh, Nathaniel L. Bindoff, Caroline C. Ummenhofer, Helen E. Phillips, Ming Feng, and Mayank Mishra. "Improving Australian Rainfall Prediction Using Sea Surface Salinity." Journal of Climate 34, no. 7 (April 2021): 2473–90. http://dx.doi.org/10.1175/jcli-d-20-0625.1.

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AbstractThis study uses sea surface salinity (SSS) as an additional precursor for improving the prediction of summer [December–February (DJF)] rainfall over northeastern Australia. From a singular value decomposition between SSS of prior seasons and DJF rainfall, we note that SSS of the Indo-Pacific warm pool region [SSSP (150°E–165°W and 10°S–10°N) and SSSI (50°–95°E and 10°S–10°N)] covaries with Australian rainfall, particularly in the northeast region. Composite analysis that is based on high or low SSS events in the SSSP and SSSI regions is performed to understand the physical links between the SSS and the atmospheric moisture originating from the regions of anomalously high or low, respectively, SSS and precipitation over Australia. The composites show the signature of co-occurring La Niña and negative Indian Ocean dipole with anomalously wet conditions over Australia and conversely show the signature of co-occurring El Niño and positive Indian Ocean dipole with anomalously dry conditions there. During the high SSS events of the SSSP and SSSI regions, the convergence of incoming moisture flux results in anomalously wet conditions over Australia with a positive soil moisture anomaly. Conversely, during the low SSS events of the SSSP and SSSI regions, the divergence of incoming moisture flux results in anomalously dry conditions over Australia with a negative soil moisture anomaly. We show from the random-forest regression analysis that the local soil moisture, El Niño–Southern Oscillation (ENSO), and SSSP are the most important precursors for the northeast Australian rainfall whereas for the Brisbane region ENSO, SSSP, and the Indian Ocean dipole are the most important. The prediction of Australian rainfall using random-forest regression shows an improvement by including SSS from the prior season. This evidence suggests that sustained observations of SSS can improve the monitoring of the Australian regional hydrological cycle.
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McCrabb, G. J., and R. A. Hunter. "Prediction of methane emissions from beef cattle in tropical production systems." Australian Journal of Agricultural Research 50, no. 8 (1999): 1335. http://dx.doi.org/10.1071/ar99009.

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The northern beef cattle herd accounts for more than half of Australia’s beef cattle population, and is a major source of anthropogenic methane emissions for Australia. National Greenhouse Gas Inventory predictions of methane output from Australian beef cattle are based on a predictive equation developed for British breeds of sheep and cattle offered temperate forage-based diets. However, tropical forage diets offered to cattle in northern Australia differ markedly from temperate forage-based diets used in the United Kingdom to develop the predictive equations. In this paper we review recent respiration chamber measurements of daily methane production for Brahman cattle offered a tropical forage or high grain diet, and compare them with values predicted using methodologies of the Australian National Greenhouse Gas Inventory Committee and the Intergovernmental Panel on Climate Change. We conclude that a reliable inventory of methane emissions for cattle in northern Australia can only be achieved after a wider range of tropical forage species has been investigated. Some opportunities for reducing methane emissions of beef cattle by dietary manipulation are discussed.
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Wu, Peng, and Yongze Song. "Land Use Quantile Regression Modeling of Fine Particulate Matter in Australia." Remote Sensing 14, no. 6 (March 11, 2022): 1370. http://dx.doi.org/10.3390/rs14061370.

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Small data samples are still a critical challenge for spatial predictions. Land use regression (LUR) is a widely used model for spatial predictions with observations at a limited number of locations. Studies have demonstrated that LUR models can overcome the limitation exhibited by other spatial prediction models which usually require greater spatial densities of observations. However, the prediction accuracy and robustness of LUR models still need to be improved due to the linear regression within the LUR model. To improve LUR models, this study develops a land use quantile regression (LUQR) model for more accurate spatial predictions for small data samples. The LUQR is an integration of the LUR and quantile regression, which both have advantages in predictions with a small data set of samples. In this study, the LUQR model is applied in predicting spatial distributions of annual mean PM2.5concentrations across the Greater Sydney Region, New South Wales, Australia, with observations at 19 valid monitoring stations in 2020. Cross validation shows that the goodness-of-fit can be improved by 25.6–32.1% by LUQR models when compared with LUR, and prediction root mean squared error (RMSE) and mean absolute error (MAE) can be reduced by 10.6–13.4% and 19.4–24.7% by LUQR models, respectively. This study also indicates that LUQR is a more robust model for the spatial prediction with small data samples than LUR. Thus, LUQR has great potentials to be widely applied in spatial issues with a limited number of observations.
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Gregory, Paul A., Lawrie J. Rikus, and Jeffrey D. Kepert. "Testing and Diagnosing the Ability of the Bureau of Meteorology’s Numerical Weather Prediction Systems to Support Prediction of Solar Energy Production." Journal of Applied Meteorology and Climatology 51, no. 9 (September 2012): 1577–601. http://dx.doi.org/10.1175/jamc-d-10-05027.1.

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AbstractThe ability of the Australian Bureau of Meteorology’s numerical weather prediction (NWP) systems to predict solar exposure (or insolation) was tested, with the aim of predicting large-scale solar energy several days in advance. The bureau’s Limited Area Prediction System (LAPS) and Mesoscale Assimilation model (MALAPS) were examined for the 2008 calendar year. Comparisons were made with estimates of solar exposure obtained from satellites for the whole Australian continent, as well as site-based exposure observations taken at eight locations across Australia. Monthly-averaged forecast solar exposure over Australia showed good agreement with satellite estimates; the day-to-day exposure values showed some consistent biases, however. Differences in forecast solar exposure were attributed to incorrect representation of convective cloud in the tropics during summer as well as clouds formed by orographic lifting over mountainous areas in southeastern Australia. Comparison with site-based exposure observations was conducted on a daily and hourly basis. The site-based exposure measurements were consistent with the findings from the analysis against satellite data. Hourly analysis at selected sites confirmed that models predicted the solar exposure accurately through low-level clouds (e.g., cumulus), provided that the forecast cloud coverage was accurate. The NWP models struggle to predict solar exposure through middle and high clouds formed by ice crystals (e.g., altocumulus). Sites located in central Australia showed that the monthly-averaged errors in daily solar exposure forecast by the NWP systems were within 5%–10%, up to two days in advance. These errors increased to 20%–30% in the tropics and coastal areas.
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Polkinghorne, R., J. M. Thompson, R. Watson, A. Gee, and M. Porter. "Evolution of the Meat Standards Australia (MSA) beef grading system." Australian Journal of Experimental Agriculture 48, no. 11 (2008): 1351. http://dx.doi.org/10.1071/ea07177.

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The Australian Beef Industry identified variable eating quality as a major contributor to declining beef consumption in the early 1990s and committed research funding to address the problem. The major issue was the ability to predict the eating quality of cooked beef before consumption. The Meat Standards Australia (MSA) program developed a consumer testing protocol, which led to MSA grading standards being defined by consumer score outcomes. Traditional carcass grading parameters proved to be of little value in predicting consumer outcomes. Instead a broader combination of factors forms the basis of an interactive prediction model that performs well. The grading model has evolved from a fixed parameter ‘Pathway’ approach, to a computer model that predicts consumer scores for 135 ‘cut by cooking method’ combinations for each graded carcass. The body of research work conducted in evaluating critical control points and in developing the model predictions and interactions has involved several Australian research groups with strong support and involvement from the industry.
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Speer, MS, LM Leslie, JR Colquhoun, and E. Mitchell. "The Sydney Australia Wildfires of January 1994 - Meteorological Conditions and High Resolution Numerical Modeling Experiments." International Journal of Wildland Fire 6, no. 3 (1996): 145. http://dx.doi.org/10.1071/wf9960145.

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Southeastern Australia is particularly vulnerable to wildfires during the spring and summer months, and the threat of devastation is present most years. In January 1994, the most populous city in Australia, Sydney, was ringed by wildfires, some of which penetrated well into suburban areas and there were many other serious fires in coastal areas of New South Wales (NSW). In recent years much research activity in Australia has focussed on the development of high resolution limited area models, for eventual operational prediction of meteorological conditions associated with high levels of wildfire risk. In this study, the period January 7-8, 1994 was chosen for detailed examination, as it was the most critical period during late December 1993/early January 1994 for the greater Sydney area. Routine forecast guidance from the Australian Bureau of Meteorology's operational numerical weather prediction (NWP) models was very useful in that both the medium and short range models predicted synoptic patterns suggesting extreme fire weather conditions up to several days in advance. However, vital information of a detailed nature was lacking. A new high resolution model was run at the operational resolution of 150 km and the much higher resolutions of 25 km and 5 km. The new model showed statistically significant greater skill in predicting details of wind, relative humidity and temperature patterns both near the surface and above the boundary layer. It also produced skilful predictions of the Forest Fire Danger Index.
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Rahimi, Iman, Amir H. Gandomi, Panagiotis G. Asteris, and Fang Chen. "Analysis and Prediction of COVID-19 Using SIR, SEIQR, and Machine Learning Models: Australia, Italy, and UK Cases." Information 12, no. 3 (March 3, 2021): 109. http://dx.doi.org/10.3390/info12030109.

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The novel coronavirus disease, also known as COVID-19, is a disease outbreak that was first identified in Wuhan, a Central Chinese city. In this report, a short analysis focusing on Australia, Italy, and UK is conducted. The analysis includes confirmed and recovered cases and deaths, the growth rate in Australia compared with that in Italy and UK, and the trend of the disease in different Australian regions. Mathematical approaches based on susceptible, infected, and recovered (SIR) cases and susceptible, exposed, infected, quarantined, and recovered (SEIQR) cases models are proposed to predict epidemiology in the above-mentioned countries. Since the performance of the classic forms of SIR and SEIQR depends on parameter settings, some optimization algorithms, namely Broyden–Fletcher–Goldfarb–Shanno (BFGS), conjugate gradients (CG), limited memory bound constrained BFGS (L-BFGS-B), and Nelder–Mead, are proposed to optimize the parameters and the predictive capabilities of the SIR and SEIQR models. The results of the optimized SIR and SEIQR models were compared with those of two well-known machine learning algorithms, i.e., the Prophet algorithm and logistic function. The results demonstrate the different behaviors of these algorithms in different countries as well as the better performance of the improved SIR and SEIQR models. Moreover, the Prophet algorithm was found to provide better prediction performance than the logistic function, as well as better prediction performance for Italy and UK cases than for Australian cases. Therefore, it seems that the Prophet algorithm is suitable for data with an increasing trend in the context of a pandemic. Optimization of SIR and SEIQR model parameters yielded a significant improvement in the prediction accuracy of the models. Despite the availability of several algorithms for trend predictions in this pandemic, there is no single algorithm that would be optimal for all cases.
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Dissertations / Theses on the topic "Prediction of Australia"

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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 &amp 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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Books on the topic "Prediction of Australia"

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2020 Vision: How global business leaders see Australia's future. Sydney: Allen & Unwin, 2003.

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Macgregor, Duncan, ed. Imagining Australia: Ideas for our future. Crows Nest, NSW: Allen & Unwin, 2004.

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Meeting, of Experts on Climate Information and Prediction Services (1995 Melbourne Australia). Report from the Meeting of Experts on Climate Information and Prediction Services (CLIPS), Melbourne, Australia, 28 to 31 March 1995. Geneva, Switzerland: World Meteorological Organization, 1995.

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Battlelines. Carlton, Vic: Melbourne University Publishing, 2010.

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Richards, Thomas. A predictive model of Aboriginal archaeological site distribution in the Otway Range. [Melbourne]: Aboriginal Affairs Victoria, 1998.

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1955-, Garnett Stephen, ed. Future options for north Australia. Darwin, N.T: Charles Darwin University Press, 2008.

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Greenhalgh, Alan. The Glass Half Full. Lulu.com, 2007.

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Cary, Geoffrey, David Lindenmayer, and Stephen Dovers, eds. Australia Burning. CSIRO Publishing, 2003. http://dx.doi.org/10.1071/9780643090965.

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The phenomenon of fire in the Australian landscape traverses many interests and disciplines. At a national level, there is an urgent need for the integration of both the natural and social sciences in the formulation of public policy. With contributions from 30 leading experts, Australia Burning draws together these issues, under the themes: Ecology and the environment Fire behaviour and fire regime science People and property Policy, institutional arrangements and the legal framework Indigenous land and fire management The book examines some of the key questions that relate to the ecology, prediction and management of fire, urban planning, law, insurance, and community issues, including indigenous and non-indigenous concerns. It looks at what we need to know to inform public policy, given the present risks and uncertainty, and explores the avenues for closer integration between science, policy and the community.
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Pike, Deborah, Camilla Nelson, and Georgina Ledvinka. On Happiness: New Ideas for the Twenty-First Century. UWA Publishing, 2015.

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On Happiness: New Ideas for the Twenty-First Century. UWA Publishing, 2015.

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Book chapters on the topic "Prediction of Australia"

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White, David, Drew Collins, and Mark Howden. "Drought in Australia: Prediction, Monitoring, Management, and Policy." In Drought Assessment, Management, and Planning: Theory and Case Studies, 213–36. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-3224-8_12.

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Hasler, Claude-Alain, Erwin W. Adams, Rachel A. Wood, and Tony Dickson. "Fine-Scale Forward Modelling of a Devonian Patch Reef, Canning Basin, Western Australia." In Analogue and Numerical Modelling of Sedimentary Systems: From Understanding to Prediction, 37–64. Oxford, UK: Wiley-Blackwell, 2009. http://dx.doi.org/10.1002/9781444303131.ch2.

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Golding, Brian, Jenny Sun, Michael Riemer, Nusrat Yussouf, Helen Titley, Joanne Robbins, Beth Ebert, et al. "Connecting Weather and Hazard: A Partnership of Physical Scientists in Connected Disciplines." In Towards the “Perfect” Weather Warning, 149–200. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98989-7_6.

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AbstractAchieving consistency in the prediction of the atmosphere and related environmental hazards requires careful design of forecasting systems. In this chapter, we identify the benefits of seamless approaches to hazard prediction and the challenges of achieving them in a multi-institution situation. We see that different modelling structures are adopted in different disciplines and that these often relate to the user requirements for those hazards. We then explore the abilities of weather prediction to meet the requirements of these different disciplines. We find that differences in requirement and language can be major challenges to seamless data processing and look at some ways in which these can be resolved. We conclude with examples of partnerships in flood forecasting in the UK and wildfire forecasting in Australia.
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Luo, Wenkai, Guomin Zhang, Huu Dung Tran, Sujeeva Setunge, and Lei Hou. "Implementing Proactive Building Asset Management Through Deterioration Prediction: A Case Study in Australia." In Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate, 951–65. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8892-1_67.

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Mohseni, H., S. Setunge, G. Zhang, and P. Kalutara. "Deterioration Prediction of Superstructure Elements of Community Buildings in Australia Using a Probabilistic Approach." In Lecture Notes in Mechanical Engineering, 689–98. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4993-4_59.

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Fox, Nathan, Anita Parbhakar-Fox, and Bernd Lottermoser. "Prediction of Metal Mobility from Sulfidic Waste Rocks Using Micro-analytical Tools, Baal Gammon, Northern Australia." In Environmental Indicators in Metal Mining, 243–62. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42731-7_14.

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Zhang, Ming, Jie-tang Lv, Hong-jun Wang, Dian-ao Wang, Yong Yang, and Gui-hong Wang. "The Methodology to Run CBM Reservoir Prediction by Maximum Utilizing Seismic and Well Data in Australia." In Springer Series in Geomechanics and Geoengineering, 816–29. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2485-1_73.

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Anderson, Cheryl L., Jane Rovins, David M. Johnston, Will Lang, Brian Golding, Brian Mills, Rainer Kaltenberger, et al. "Connecting Forecast and Warning: A Partnership Between Communicators and Scientists." In Towards the “Perfect” Weather Warning, 87–113. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98989-7_4.

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AbstractIn this chapter, we examine the ways that warning providers connect and collaborate with knowledge sources to produce effective warnings. We first look at the range of actors who produce warnings in the public and private sectors, the sources of information they draw on to comprehend the nature of the hazard, its impacts and the implications for those exposed and the process of drawing that information together to produce a warning. We consider the wide range of experts who connect hazard data with impact data to create tools for assessing the impacts of predicted hazards on people, buildings, infrastructure and business. Then we look at the diverse ways in which these tools need to take account of the way their outputs will feed into warnings and of the nature of partnerships that can facilitate this. The chapter includes examples of impact prediction in sport, health impacts of wildfires in Australia, a framework for impact prediction in New Zealand, and communication of impacts through social media in the UK.
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Beard, Grant, Graham de Hoedt, and Neil Plummer. "Operational Seasonal Predictions in Australia." In Early Warning Systems for Natural Disaster Reduction, 375–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55903-7_48.

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Holmes, J. D. "Extreme Wind Prediction – The Australian Experience." In Lecture Notes in Civil Engineering, 365–75. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12815-9_29.

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Conference papers on the topic "Prediction of Australia"

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Vuckovic, V. "Prediction of Fracture Gradients Offshore Australia." In SPE Asia-Pacific Conference. Society of Petroleum Engineers, 1989. http://dx.doi.org/10.2118/19468-ms.

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Hansen, K. S., N. Nouri, B. A. Cooper, P. Schutjens, J. W. Dudley, and M. M. Arasteh. "Integrated Pre-drill Pore Pressure, Fracture Gradient and Borehole Stability Predictions for Evans Shoal Field, Australia." In First EAGE Workshop on Pore Pressure Prediction. Netherlands: EAGE Publications BV, 2017. http://dx.doi.org/10.3997/2214-4609.201700055.

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He, Zhixuan. "Rain Prediction In Australia With Active Learning Algorithm." In 2021 International Conference on Computers and Automation (CompAuto). IEEE, 2021. http://dx.doi.org/10.1109/compauto54408.2021.00010.

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Sausan, Sarah, Zulfikar Simatupang, Adekunle Olayinka Osundina, and Geovani Christopher Kaeng. "Overpressure Prediction Challenges in Deepwater Sundaland." In International Conference and Exhibition, Melbourne, Australia 13-16 September 2015. Society of Exploration Geophysicists and American Association of Petroleum Geologists, 2015. http://dx.doi.org/10.1190/ice2015-2224204.

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Suzuki, Hajime, David Robertson, Nisal L. Ratnayake, and Karla Ziri-Castro. "Prediction and Measurement of Multiuser MIMO-OFDM Channel in Rural Australia." In 2012 IEEE Vehicular Technology Conference (VTC 2012-Spring). IEEE, 2012. http://dx.doi.org/10.1109/vetecs.2012.6240211.

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Huang, Jing, Lawrence Rikus, and Yi Qin. "Probabilistic solar irradiance forecasting using numerical weather prediction ensembles over Australia." In 2020 IEEE 47th Photovoltaic Specialists Conference (PVSC). IEEE, 2020. http://dx.doi.org/10.1109/pvsc45281.2020.9300836.

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Kumar*, Rajeev. "Integrated Pore Pressure Prediction Approach for Successful Drilling in Tectonic Area." In International Conference and Exhibition, Melbourne, Australia 13-16 September 2015. Society of Exploration Geophysicists and American Association of Petroleum Geologists, 2015. http://dx.doi.org/10.1190/ice2015-2153265.

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Phan, The Danh. "Housing Price Prediction Using Machine Learning Algorithms: The Case of Melbourne City, Australia." In 2018 International Conference on Machine Learning and Data Engineering (iCMLDE). IEEE, 2018. http://dx.doi.org/10.1109/icmlde.2018.00017.

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"Forecasting daily reference evapotranspiration for Shepparton, Victoria, Australia using numerical weather prediction outputs." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.l16.perera.

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Li, Bingnan, Zi Chen, and Samsung Lim. "Geolocation Prediction from Tweets: A Case Study of Influenza-like Illness in Australia." In 6th International Conference on Geographical Information Systems Theory, Applications and Management. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0009345101600167.

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Reports on the topic "Prediction of Australia"

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Smit, Amelia, Kate Dunlop, Nehal Singh, Diona Damian, Kylie Vuong, and Anne Cust. Primary prevention of skin cancer in primary care settings. The Sax Institute, August 2022. http://dx.doi.org/10.57022/qpsm1481.

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Overview Skin cancer prevention is a component of the new Cancer Plan 2022–27, which guides the work of the Cancer Institute NSW. To lessen the impact of skin cancer on the community, the Cancer Institute NSW works closely with the NSW Skin Cancer Prevention Advisory Committee, comprising governmental and non-governmental organisation representatives, to develop and implement the NSW Skin Cancer Prevention Strategy. Primary Health Networks and primary care providers are seen as important stakeholders in this work. To guide improvements in skin cancer prevention and inform the development of the next NSW Skin Cancer Prevention Strategy, an up-to-date review of the evidence on the effectiveness and feasibility of skin cancer prevention activities in primary care is required. A research team led by the Daffodil Centre, a joint venture between the University of Sydney and Cancer Council NSW, was contracted to undertake an Evidence Check review to address the questions below. Evidence Check questions This Evidence Check aimed to address the following questions: Question 1: What skin cancer primary prevention activities can be effectively administered in primary care settings? As part of this, identify the key components of such messages, strategies, programs or initiatives that have been effectively implemented and their feasibility in the NSW/Australian context. Question 2: What are the main barriers and enablers for primary care providers in delivering skin cancer primary prevention activities within their setting? Summary of methods The research team conducted a detailed analysis of the published and grey literature, based on a comprehensive search. We developed the search strategy in consultation with a medical librarian at the University of Sydney and the Cancer Institute NSW team, and implemented it across the databases Embase, MEDLINE, PsycInfo, Scopus, Cochrane Central and CINAHL. Results were exported and uploaded to Covidence for screening and further selection. The search strategy was designed according to the SPIDER tool for Qualitative and Mixed-Methods Evidence Synthesis, which is a systematic strategy for searching qualitative and mixed-methods research studies. The SPIDER tool facilitates rigour in research by defining key elements of non-quantitative research questions. We included peer-reviewed and grey literature that included skin cancer primary prevention strategies/ interventions/ techniques/ programs within primary care settings, e.g. involving general practitioners and primary care nurses. The literature was limited to publications since 2014, and for studies or programs conducted in Australia, the UK, New Zealand, Canada, Ireland, Western Europe and Scandinavia. We also included relevant systematic reviews and evidence syntheses based on a range of international evidence where also relevant to the Australian context. To address Question 1, about the effectiveness of skin cancer prevention activities in primary care settings, we summarised findings from the Evidence Check according to different skin cancer prevention activities. To address Question 2, about the barriers and enablers of skin cancer prevention activities in primary care settings, we summarised findings according to the Consolidated Framework for Implementation Research (CFIR). The CFIR is a framework for identifying important implementation considerations for novel interventions in healthcare settings and provides a practical guide for systematically assessing potential barriers and facilitators in preparation for implementing a new activity or program. We assessed study quality using the National Health and Medical Research Council (NHMRC) levels of evidence. Key findings We identified 25 peer-reviewed journal articles that met the eligibility criteria and we included these in the Evidence Check. Eight of the studies were conducted in Australia, six in the UK, and the others elsewhere (mainly other European countries). In addition, the grey literature search identified four relevant guidelines, 12 education/training resources, two Cancer Care pathways, two position statements, three reports and five other resources that we included in the Evidence Check. Question 1 (related to effectiveness) We categorised the studies into different types of skin cancer prevention activities: behavioural counselling (n=3); risk assessment and delivering risk-tailored information (n=10); new technologies for early detection and accompanying prevention advice (n=4); and education and training programs for general practitioners (GPs) and primary care nurses regarding skin cancer prevention (n=3). There was good evidence that behavioural counselling interventions can result in a small improvement in sun protection behaviours among adults with fair skin types (defined as ivory or pale skin, light hair and eye colour, freckles, or those who sunburn easily), which would include the majority of Australians. It was found that clinicians play an important role in counselling patients about sun-protective behaviours, and recommended tailoring messages to the age and demographics of target groups (e.g. high-risk groups) to have maximal influence on behaviours. Several web-based melanoma risk prediction tools are now available in Australia, mainly designed for health professionals to identify patients’ risk of a new or subsequent primary melanoma and guide discussions with patients about primary prevention and early detection. Intervention studies have demonstrated that use of these melanoma risk prediction tools is feasible and acceptable to participants in primary care settings, and there is some evidence, including from Australian studies, that using these risk prediction tools to tailor primary prevention and early detection messages can improve sun-related behaviours. Some studies examined novel technologies, such as apps, to support early detection through skin examinations, including a very limited focus on the provision of preventive advice. These novel technologies are still largely in the research domain rather than recommended for routine use but provide a potential future opportunity to incorporate more primary prevention tailored advice. There are a number of online short courses available for primary healthcare professionals specifically focusing on skin cancer prevention. Most education and training programs for GPs and primary care nurses in the field of skin cancer focus on treatment and early detection, though some programs have specifically incorporated primary prevention education and training. A notable example is the Dermoscopy for Victorian General Practice Program, in which 93% of participating GPs reported that they had increased preventive information provided to high-risk patients and during skin examinations. Question 2 (related to barriers and enablers) Key enablers of performing skin cancer prevention activities in primary care settings included: • Easy access and availability of guidelines and point-of-care tools and resources • A fit with existing workflows and systems, so there is minimal disruption to flow of care • Easy-to-understand patient information • Using the waiting room for collection of risk assessment information on an electronic device such as an iPad/tablet where possible • Pairing with early detection activities • Sharing of successful programs across jurisdictions. Key barriers to performing skin cancer prevention activities in primary care settings included: • Unclear requirements and lack of confidence (self-efficacy) about prevention counselling • Limited availability of GP services especially in regional and remote areas • Competing demands, low priority, lack of time • Lack of incentives.
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Aguilar, Glenn, Dan Blanchon, Hamish Foote, Christina Pollonais, and Asia Mosee. Queensland Fruit Fly Invasion of New Zealand: Predicting Area Suitability Under Future Climate Change Scenarios. Unitec ePress, October 2017. http://dx.doi.org/10.34074/pibs.rs22015.

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The Queensland fruit fly (Bactrocera tryoni) is a significant horticultural pest in Australia, and has also established in other parts of the Pacific. There is a significant risk to New Zealand of invasion by this species, and several recent incursions have occurred. The potential effects of climate change on the distribution and impacts of invasive species are well known. This paper uses species distribution modelling using Maxent to predict the suitability of New Zealand to the Queensland fruit fly based on known occurrences worldwide and Bioclim climatic layers. Under current climatic conditions the majority of the country was generally in the lower range, with some areas in the medium range. Suitability prediction maps under future climate change conditions in 2050 and 2070, at lower emission (RCP 2.6) and higher emission (RCP 8.5) scenarios generally show an increase in suitability in both the North and South Islands. Calculations of the shift of suitable areas show a general movement of the centroid towards the south-east, with the higher emission scenario showing a greater magnitude of movement.
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Reeder, Michael J., Noel E. Davidson, Jeffrey D. Kepert, Peter J. Steinle, Kevin J. Tory, and Graig H. Bishop. Initialization, Prediction and Diagnosis of the Rapid Intensification of Tropical Cyclones Using the Australian Community Climate and Earth System Simulator, ACCESS. Fort Belvoir, VA: Defense Technical Information Center, January 2010. http://dx.doi.org/10.21236/ada539048.

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Reeder, Michael J., Noel E. Davidson, Craig H. Bishop, Jeffrey D. Kepert, Peter Steinle, Kevin J. Tory, Yi Xiao, et al. Initialization, Prediction and Diagnosis of the Rapid Intensification of Tropical Cyclones using the Australian Community Climate and Earth System Simulator, ACCESS. Fort Belvoir, VA: Defense Technical Information Center, October 2012. http://dx.doi.org/10.21236/ada572282.

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Reeder, Michael J., Noel E. Davidson, Craig H. Bishop, Jeffrey D. Kepert, Peter Steinle, Kevin J. Tory, and Yimin Ma. Initialization, Prediction and Diagnosis of the Rapid Intensification of Tropical Cyclones using the Australian Community Climate and Earth System Simulator, ACCESS. Fort Belvoir, VA: Defense Technical Information Center, November 2011. http://dx.doi.org/10.21236/ada555155.

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Allison, Stephen C., Bruce S. Cohen, Edward J. Zambraski, Mark Jaffrey, and Robin Orr. Predictive Models to Estimate Probabilities of Injuries, Poor Physical Fitness, and Attrition Outcomes in Australian Defense Force Army Recruit Training. Fort Belvoir, VA: Defense Technical Information Center, November 2015. http://dx.doi.org/10.21236/ad1000577.

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Elizur, Abigail, Amir Sagi, Gideon Hulata, Clive Jones, and Wayne Knibb. Improving Crustacean Aquaculture Production Efficiencies through Development of Monosex Populations Using Endocrine and Molecular Manipulations. United States Department of Agriculture, June 2010. http://dx.doi.org/10.32747/2010.7613890.bard.

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Background Most of Australian prawn aquaculture production is based on P. monodon. However, the Australian industry is under intense competition from lower priced overseas imports. The availability of all-female monosex populations, by virtue of their large size and associated premium prize, will offer competitive advantage to the industry which desperately needs to counteract competitors within this market. As for the redclaw production in Israel, although it is at its infancy, the growers realized that the production of males is extremely advantageous and that such management strategy will change the economic assumptions and performances of this aquaculture to attract many more growers. Original objectives (as in original proposal) Investigating the sex inheritance mechanism in the tiger prawn. Identification of genes expressed uniquely in the androgenic gland (AG) of prawns and crayfish. The above genes and/or their products will be used to localize the AG in the prawn and manipulate the AG activity in both species. Production of monosex populations through AG manipulation. In the prawn, production of all-female populations and in the crayfish, all-male populations. Achievements In the crayfish, the AG cDNA library was further screened and a third AG specific transcript, designated Cq-AG3, had been identified. Simultaneously the two AG specific genes, which were previously identified, were further characterized. Tissue specificity of one of those genes, termed Cq-AG2, was demonstrated by northern blot hybridization and RNA in-situ hybridization. Bioinformatics prediction, which suggested a 42 amino acid long signal anchor at the N-terminus of the deduced Cq-AG2, was confirmed by immunolocalization of a recombinant protein. Cq-IAG's functionality was demonstrated by dsRNA in-vivo injections to intersex crayfish. Cq-IAGsilencing induced dramatic sex-related alterations, including male feature feminization, reduced sperm production, extensive testicular apoptosis, induction of the vitellogeningene expression and accumulation of yolk proteins in the ovaries. In the prawn, the AG was identified and a cDNA library was created. The putative P. monodonAG hormone encoding gene (Pm-IAG) was identified, isolated and characterized for time of expression and histological localization. Implantation of the AG into prawn post larvae (PL) and juveniles resulted in phenotypic transformation which included the appearance of appendix masculina and enlarged petasma. The transformation however did not result in sex change or the creation of neo males thus the population genetics stage to be executed with Prof. Hulata did not materialized. Repeated AG implantation is currently being trialed. Major conclusions and Implications, both scientific and agricultural Cq-IAG's involvement in male sexual differentiation had been demonstrated and it is strongly suggested that this gene encodes an AG hormone in this crayfish. A thorough screening of the AG cDNA library shows Cq-IAG is the prominent transcript within the library. However, the identification of two additional transcripts hints that Cq-IAG is not the only gene mediating the AG effects. The successful gene silencing of Cq-IAG, if performed at earlier developmental stages, might accomplish full and functional sex reversal which will enable the production of all-male crayfish populations. Pm-IAG is likely to play a similar role in prawns. It is possible that repeated administration of the AG into prawn will lead to the desired full sex reversal, so that WZ neo males, crossed with WZ females can result in WW females, which will form the basis for monosex all-female population.
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