Novel technology for enhanced coal seam gas production utilising mechanisms of stimulated cleat permeability through graded particle injection. This cross-disciplinary project will develop a new integrated technology for well productivity enhancement in coal seam gas, shale, tight gas and geothermal reservoirs - the world’s fastest growing unconventional clean energy resources. It will improve our understanding of the multi scale physics of natural gas and energy production.
New perspectives on computing methods for mathematical signal processing. This project determines how best to design computing methods for challenging demands in signal processing. The expected conceptual & algorithmic advances will have significant repercussions in a number of fields including optimal filtering theory and will contribute to applications ranging from bio-informatics to electrical engineering. The new techniques will allow development of software that will benefit Australian in ....New perspectives on computing methods for mathematical signal processing. This project determines how best to design computing methods for challenging demands in signal processing. The expected conceptual & algorithmic advances will have significant repercussions in a number of fields including optimal filtering theory and will contribute to applications ranging from bio-informatics to electrical engineering. The new techniques will allow development of software that will benefit Australian industries and technologies. The formation of a strong research team across four universities in Australia, USA and Japan will enhance our scientific standing in the international community and will place Australian researchers at the forefront of world-class research methods. Read moreRead less
Optimal Transforms of Random Vectors. This proposal focusses on development of optimal transforms to describe and model nonlinear phenomena when only statistical information is known. An optimal transform is a mathematical procedure that enables us to process information in a way that is most suited to the task in hand. These transforms have been successfully used in approximation, information theory, communications, control theory and signal and image processing. Applications include modelli ....Optimal Transforms of Random Vectors. This proposal focusses on development of optimal transforms to describe and model nonlinear phenomena when only statistical information is known. An optimal transform is a mathematical procedure that enables us to process information in a way that is most suited to the task in hand. These transforms have been successfully used in approximation, information theory, communications, control theory and signal and image processing. Applications include modelling of physical, chemical and biological systems, filtering and compression of signals and data classification and clustering. We propose two new hybrid models for realistic transforms in a general structural framework.
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Perturbation and approximation methods for linear operators with applications to train control, water resource management and evolution of physical systems. Linear equations are used to solve practical problems. In realistic problems the equations and their solutions depend on parameters obtained by measurement of physical quantities and on data derived from observations and experiments. Changes to the values of the key parameters will lead to changes in the solutions. This project will devel ....Perturbation and approximation methods for linear operators with applications to train control, water resource management and evolution of physical systems. Linear equations are used to solve practical problems. In realistic problems the equations and their solutions depend on parameters obtained by measurement of physical quantities and on data derived from observations and experiments. Changes to the values of the key parameters will lead to changes in the solutions. This project will develop methods to better understand the relationships between the key parameters and the solutions and will apply the new insights to practical problems such as the minimization of fuel consumption in trains, optimal resource management in water supply systems and the evolution of physical systems.Read moreRead less
Construction of utility functions from observations of consumer behaviour with application to resource modelling and water management strategies. The optimisation techniques developed will be on the forefront of applied mathematical sciences and will increase the prestige of the Australian mathematical community. The expected results will also be of value because they can be used to improve the CGE modelling technique. The implementation of the CGE model of one of Victoria's agricultural regions ....Construction of utility functions from observations of consumer behaviour with application to resource modelling and water management strategies. The optimisation techniques developed will be on the forefront of applied mathematical sciences and will increase the prestige of the Australian mathematical community. The expected results will also be of value because they can be used to improve the CGE modelling technique. The implementation of the CGE model of one of Victoria's agricultural regions will be used to improve the accuracy of regional economic models and will contribute to efficient regional resource management. This has the potential to positively affect the economic growth and employment in the region. The expected outcomes of the project are especially important taking into account the need for predicting the socio-economic consequences of the 1994 COAG water reforms. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101565
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodol ....Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodologies in finite mixture modelling using skew component distributions to provide better models for handling data with non-normal features (such as skewness, heavy/light tails, and multimodality). Applications may include security intrusion detection, clinical diagnosis and prognosis, and flow and mass cytometry.Read moreRead less
Microchip Impedance Biosensor for Biomedical Diagnostics. This research proposal uses an innovative engineering approach based on novel nanomaterials with the aim of developing a new and generic biosensing technology with the potential to be widely applied in many areas including medical diagnostics, environmental control, industry and biosecurity. The outcomes from this project will benefit Australia by contributing through the development of novel materials, new technologies and new devices. ....Microchip Impedance Biosensor for Biomedical Diagnostics. This research proposal uses an innovative engineering approach based on novel nanomaterials with the aim of developing a new and generic biosensing technology with the potential to be widely applied in many areas including medical diagnostics, environmental control, industry and biosecurity. The outcomes from this project will benefit Australia by contributing through the development of novel materials, new technologies and new devices. The development of technological innovations based on fabricated nanomaterials, will also enhance capacity in frontier technology such as nanotechnology, and build Australia’s strength in using new biosensing technologies.Read moreRead less
Ubiquity of K-theory and T-duality. An abstract mathematical tool, called K-theory, has recently found application in two, not obviously related, areas of physics: the classification of D-branes in String Theory, and topological phases in Condensed Matter Theory. This project aims to advance the development of K-theory using ideas from physics. In particular, the project aims to generalise previous constructions, such as T-duality, to loop spaces, and to develop the K-theory relevant to the clas ....Ubiquity of K-theory and T-duality. An abstract mathematical tool, called K-theory, has recently found application in two, not obviously related, areas of physics: the classification of D-branes in String Theory, and topological phases in Condensed Matter Theory. This project aims to advance the development of K-theory using ideas from physics. In particular, the project aims to generalise previous constructions, such as T-duality, to loop spaces, and to develop the K-theory relevant to the classification of topological phases in strongly interacting systems. This project involves postgraduate training as a crucial tool in achieving its aims and enhances Australia's position at the forefront of international research.Read moreRead less
Electrochemical biosensors for detection of cardiac disease markers in blood. Cardiovascular diseases leading to heart failure have a prevalence of over 16 per cent in Australia. The social, economic and health burden is higher than for any other disease group. Hence, it is critically important to develop fit-for-purpose sensors of known cardiac biomarkers, which alert patients and clinicians of the risk of imminent heart failure.
Higher Line Bundles in Geometry and Physics. This project seeks to develop a theory of geometric objects, `higher line bundles', which realise elements of higher dimensional cohomology groups. In particular this project will develop a theory of differential geometry for these objects, allowing one to interpret differential forms representing cohomology classes as the `curvature' of a higher line bundle. This will have applications in quantum field theory and string/brane theory.