Developing Contemporary Driving Risk Assessment Tools to Improve Fleet Safety. The development of effective driving risk management tools will provide valuable insight into methods to reduce a significant community and national problem, as work-related road crashes cost Australia $15 billion a year. Importantly, the project has the potential to benefit both urban and rural areas of Queensland and Australia, as road crashes are a national problem. The research study also has the potential to cr ....Developing Contemporary Driving Risk Assessment Tools to Improve Fleet Safety. The development of effective driving risk management tools will provide valuable insight into methods to reduce a significant community and national problem, as work-related road crashes cost Australia $15 billion a year. Importantly, the project has the potential to benefit both urban and rural areas of Queensland and Australia, as road crashes are a national problem. The research study also has the potential to create business cost savings from reductions in productivity loss and medical expenses, as well as flow through to the general population in terms of better (a) fleet management, and (b) driver attitudes and behaviour.Read moreRead less
ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this ....ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this Centre is to create innovative mathematical and statistical models that can uncover the knowledge concealed within the size and complexity of these big data sets, with a focus on using the models to deliver insight into problems vital to the Centre's Collaborative Domains: Healthy People, Sustainable Environments and Prosperous Societies.Read moreRead less
An intelligent maintenance decision system for the water utility industry. The reliability and maintenance of pump stations is of paramount importance to the water utility industries. In Australia, the maintenance of assets for the water and wastewater industry amounts to $927m per annum. This research will develop an intelligent maintenance decision support system to reduce maintenance costs in pumping stations with increased reliability. The outcomes of the research will significantly improve ....An intelligent maintenance decision system for the water utility industry. The reliability and maintenance of pump stations is of paramount importance to the water utility industries. In Australia, the maintenance of assets for the water and wastewater industry amounts to $927m per annum. This research will develop an intelligent maintenance decision support system to reduce maintenance costs in pumping stations with increased reliability. The outcomes of the research will significantly improve the reliability and supply security of water systems to Queensland's rural and regional communities and industries. It will also advance the body of knowledge of the field of integrated asset management and enhance Australia's international standing in this field.Read moreRead less
Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discove ....Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discovery and validation of group structure in data mining applications will considerably enhance knowledge management and decision support in science, industry, and government.
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On-line and Incremental EM-based Neural Networks: Application to Hospital Utlilization and Gene Expression Data. Artificial neural networks have been widely applied as universal classifiers in many fields, such as biomedicine. However, misunderstanding of fundamental statistical principles, which can cause misleading findings, has been frequently observed in the literature. This project aims to integrate statistical methodologies in neural networks to provide a unified approach to improve its ....On-line and Incremental EM-based Neural Networks: Application to Hospital Utlilization and Gene Expression Data. Artificial neural networks have been widely applied as universal classifiers in many fields, such as biomedicine. However, misunderstanding of fundamental statistical principles, which can cause misleading findings, has been frequently observed in the literature. This project aims to integrate statistical methodologies in neural networks to provide a unified approach to improve its applicability and efficiency in implementation. The system developed from this proposed cross-disciplinary research will be applied to hospital utilization data (hospital morbidity database, Western Australia) and gene expression data (DNA microarrays databases, Harvard University). This collaborative research will advance the international standard of Australian research communities.
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