Toward a complete view of life on earth via single cell genomics. Genome sequencing has revolutionised biology, but for most microorganisms this revolution has not arrived because the majority cannot be grown in the laboratory. This project will address this grand challenge by targeted sequencing of single cells from the environment that will fill in many major gaps in the microbial tree of life.
Macroecology of reptiles and frogs over latitudinal and temporal gradients. This project aims to address major macroecological concepts in reptile and frog communities through time, focusing on environmental and climatic gradients in species diversity and body-size variation. This project expects to generate a unique macroecological dataset by integrating data from Quaternary fossil sites spanning a 3000km latitudinal gradient with current ecological data. Expected outcomes include the first com ....Macroecology of reptiles and frogs over latitudinal and temporal gradients. This project aims to address major macroecological concepts in reptile and frog communities through time, focusing on environmental and climatic gradients in species diversity and body-size variation. This project expects to generate a unique macroecological dataset by integrating data from Quaternary fossil sites spanning a 3000km latitudinal gradient with current ecological data. Expected outcomes include the first comprehensive ecological assessment of Australian reptile and frog communities through Pleistocene climate oscillations, with predictions into the future. This research will benefit Australian society by providing evidence-based knowledge of faunal community composition through time in association with changing climates.Read moreRead less
A Grid based platform for multi-scaled biological simulation. Heart disease currently affects over 3.5 million Australians. In 2006 it claimed the lives of almost 46,000 Australians (34% of all deaths). We will develop enabling technology that underpins cardiac disease research, offering potential for new treatments and pharmaceutical therapies. Even a small improvement in this area can translate into significant national benefit. Further, the mathematical techniques and software tools we will d ....A Grid based platform for multi-scaled biological simulation. Heart disease currently affects over 3.5 million Australians. In 2006 it claimed the lives of almost 46,000 Australians (34% of all deaths). We will develop enabling technology that underpins cardiac disease research, offering potential for new treatments and pharmaceutical therapies. Even a small improvement in this area can translate into significant national benefit. Further, the mathematical techniques and software tools we will develop, whilst focused on heart tissue, will have broader applicability, and may underpin advancements in other disciplines. Finally, we expect that the software solutions and infrastructure will have both commercial and strategic value in their own right.Read moreRead less
Mapping Trusted Systems Technologies to E-security Requirements. A new software based approach, strongly guided by national and international security standards based upon mandatory access control, is required to simplify for management the protection of their information infrastructure. This will be in the form of a security definition toolset aligned to trusted systems technologies currently under consideration internationally. No such trusted system has been developed to address current comme ....Mapping Trusted Systems Technologies to E-security Requirements. A new software based approach, strongly guided by national and international security standards based upon mandatory access control, is required to simplify for management the protection of their information infrastructure. This will be in the form of a security definition toolset aligned to trusted systems technologies currently under consideration internationally. No such trusted system has been developed to address current commercial IT product environments. The safety and security of information systems against attack and illicit usage form an essential component of ?National Information Infrastructure Protection (NIIP)?, a move to better ?e-security?. Existing commercial (untrusted) operating systems lack the critical security bases for e-security making e-applications vulnerable to tampering and bypass which can cause failures in overall system security.Read moreRead less
A Novel Framework for Optimised Ensemble Classifier. The project aims to develop a novel framework for creating an optimised ensemble classifier that will improve data analysis and the accuracy of many real-world applications such as document analysis, robotics and medical diagnosis. The project plans to develop and investigate novel methods for generating diverse training environment layers, base classifiers and fusion of classifiers. It also plans to design a multi-objective evolutionary algor ....A Novel Framework for Optimised Ensemble Classifier. The project aims to develop a novel framework for creating an optimised ensemble classifier that will improve data analysis and the accuracy of many real-world applications such as document analysis, robotics and medical diagnosis. The project plans to develop and investigate novel methods for generating diverse training environment layers, base classifiers and fusion of classifiers. It also plans to design a multi-objective evolutionary algorithm-based search obtain the optimal number of layers, clusters and base classifiers. The expected outcomes of the proposed framework are advances in classifier learning. The final outcome may be novel methods which will bring in diversity during the learning of the base classifiers and provide an optimal ensemble classifier for real-world applications.Read moreRead less
Deep Learning Architecture with Context Adaptive Features for Image Parsing. This project aims to develop a novel deep learning network architecture with contextual adaptive features for image parsing that can improve the object detection accuracy in real-world applications. A number of innovative methods for deep learning, contextual features and network parameter selection will be developed and investigated. The impact of the proposed architecture and features will be improved object-detection ....Deep Learning Architecture with Context Adaptive Features for Image Parsing. This project aims to develop a novel deep learning network architecture with contextual adaptive features for image parsing that can improve the object detection accuracy in real-world applications. A number of innovative methods for deep learning, contextual features and network parameter selection will be developed and investigated. The impact of the proposed architecture and features will be improved object-detection accuracy and advances in deep learning network architecture for image parsing. The intended outcomes are deep learning network architecture, contextual feature extraction techniques and network parameter optimisation techniques for image parsing.Read moreRead less
Diversification and conservation of Australian frogs. Australia's 216 known species of frogs are exceptionally diverse, 98 per cent are found nowhere else in the world and many of them are in trouble. This project will test ideas concerning the tempo of Australian frog diversification, identify previously cryptic new species and provide information critical to the conservation of Australia's declining frogs.
Ontologically-based Evaluation, Comparison and Engineering of Integrated Process Modelling Techniques. Integrated process modelling techniques such as UML and ARIS form the conceptual platform for many management and IT projects. Though most IS development tools contain these techniques, anecdotal evidence indicates many shortcomings. This project uses a well-established theory developed in philosophy and applied in information systems domains for the evaluation of these techniques. The expec ....Ontologically-based Evaluation, Comparison and Engineering of Integrated Process Modelling Techniques. Integrated process modelling techniques such as UML and ARIS form the conceptual platform for many management and IT projects. Though most IS development tools contain these techniques, anecdotal evidence indicates many shortcomings. This project uses a well-established theory developed in philosophy and applied in information systems domains for the evaluation of these techniques. The expected outcomes are evaluations of ARIS and UML. Thus, this project contributes to the development of two of the most popular modelling techniques. Based on the theory used and the results of an international empirical study, suggestions for the further development of these techniques will be derived.Read moreRead less
Cross-Entropy Methods in Complex Biological Systems. The Cross-Entropy method provides a powerful new way to find superior solutions to complicated optimisation problems in biology, ranging from better design and implementation of medical treatments to an increased understanding of complex ecosystems.
A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extrac ....A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extractor for automatically extracting features, an optimiser for finding optimal parameters and non-iterative ensemble learning technique for classification of features into classes. The impact of this project will be automatic feature extractors and classifiers for real-world applications.Read moreRead less