Modelling the stability and efficiency of ring spinning. This research will benefit the animal fibre industry, particularly the multi-billion dollar wool industry. Low spinning efficiency adds a significant cost to the conversion of animal fibres into textile products, which reduces the competitive position of these natural fibres. The proposed research will lead to improvement in the efficiency of ring spinning. It has been estimated that a 1% improvement in spinning efficiency will add about $ ....Modelling the stability and efficiency of ring spinning. This research will benefit the animal fibre industry, particularly the multi-billion dollar wool industry. Low spinning efficiency adds a significant cost to the conversion of animal fibres into textile products, which reduces the competitive position of these natural fibres. The proposed research will lead to improvement in the efficiency of ring spinning. It has been estimated that a 1% improvement in spinning efficiency will add about $16 million to the wool industry alone. Read moreRead less
Modelling and minimising energy consumption in ring spinning. Australia's 4-billion dollar natural fibre production is spun into yarns via ring spinning mainly. A major drawback of this spinning system is its high energy consumption. This project will examine, theoretically and experimentally, the key factors contributing to energy consumption in ring spinning. It will generate new knowledge on the relationship between yarn hairiness and the air drag on a rapidly rotating yarn package and on a b ....Modelling and minimising energy consumption in ring spinning. Australia's 4-billion dollar natural fibre production is spun into yarns via ring spinning mainly. A major drawback of this spinning system is its high energy consumption. This project will examine, theoretically and experimentally, the key factors contributing to energy consumption in ring spinning. It will generate new knowledge on the relationship between yarn hairiness and the air drag on a rapidly rotating yarn package and on a ballooning yarn, and predict how this air drag affects the energy consumption during package build-up in ring spinning. This will lead to ways of minimising energy consumption in this most important spinning process.Read moreRead less
Investigating evidence of control system dynamics in visuomotor skill acquisition using multimodal functional magnetic resonance imaging. This project brings together mathematical and engineering methods with cognitive neuroscience in a novel way to better understand the fundamental processes associated with brain imaging, and the acquisition of motor skills. An improved understanding of the function of regions within the motor network will have a direct benefit for the rehabilitation of patient ....Investigating evidence of control system dynamics in visuomotor skill acquisition using multimodal functional magnetic resonance imaging. This project brings together mathematical and engineering methods with cognitive neuroscience in a novel way to better understand the fundamental processes associated with brain imaging, and the acquisition of motor skills. An improved understanding of the function of regions within the motor network will have a direct benefit for the rehabilitation of patients suffering motor deficits from developmental causes, following traumatic brain injuries, and after stroke and other neurodegenerative diseases. The outcomes of the research will also contribute to our understanding of the complexity of brain networks involved in motor skill acquisition.Read moreRead less
Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering ap ....Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.Read moreRead less
Generalised quantum models of complexity with application to cognitive systems. Non-separable systems surround us. Our transportation, taxation, schooling, environmental and social policies are all interrelated, and it is increasingly recognised that we cannot consider them in isolation. Such systems are generally deemed complex, and it is often impossible to separate them from one another. Despite this, many of our most advanced modelling techniques are grounded in principles of separability a ....Generalised quantum models of complexity with application to cognitive systems. Non-separable systems surround us. Our transportation, taxation, schooling, environmental and social policies are all interrelated, and it is increasingly recognised that we cannot consider them in isolation. Such systems are generally deemed complex, and it is often impossible to separate them from one another. Despite this, many of our most advanced modelling techniques are grounded in principles of separability and non-contextuality. This project will develop a new set of models of non-separable systems and complexity that will in turn lead to new frontier technologies and theories.Read moreRead less
3D Image segmentation and shape characterisation driven by topological persistence. Tomographic imaging is emerging as a new tool to help tackle a remarkable array of scientific challenges. What distinguishes healthy bone from that of osteoporosis sufferers? How does groundwater contamination spread? Why is a macadamia nut so hard to crack? What causes the iridescence in a butterfly wing? These are just a few of the questions being answered at tomographic facilities in Australia alone. By co ....3D Image segmentation and shape characterisation driven by topological persistence. Tomographic imaging is emerging as a new tool to help tackle a remarkable array of scientific challenges. What distinguishes healthy bone from that of osteoporosis sufferers? How does groundwater contamination spread? Why is a macadamia nut so hard to crack? What causes the iridescence in a butterfly wing? These are just a few of the questions being answered at tomographic facilities in Australia alone. By combining sophisticated mathematics with cutting edge image-processing algorithms, this project will yield a new class of topology driven image analysis techniques that will improve the accuracy and reliability of predictions made from tomographic images.Read moreRead less
Automated Determination of the Pose of a Human from Visual Information - Markerless 3D Pose Recovery of Humans from Videos. The development of 3D human pose recovery has been sought by computer vision researchers for many years. Our results will, firstly, have benefit for Australia's standing in the international computer vision community. Over time, the research outcomes will be developed into a software product for rehabilitation analysis by recognizing discrepancies between the walking pat ....Automated Determination of the Pose of a Human from Visual Information - Markerless 3D Pose Recovery of Humans from Videos. The development of 3D human pose recovery has been sought by computer vision researchers for many years. Our results will, firstly, have benefit for Australia's standing in the international computer vision community. Over time, the research outcomes will be developed into a software product for rehabilitation analysis by recognizing discrepancies between the walking patterns of healthy individuals and those with abnormalities as a result of accidents or diseases. The Australian economy will benefit by the reduction in the lifetime cost of injuries. This software will also provide benefits to the movie animation, computer games industry, and the training of athletes.Read moreRead less
Bayesian inference for complex regression models using mixtures. The project will use mixtures to flexibly model complex regression functions and will develop Bayesian methods for carrying out statistical inference on these models. The models will deal with both Gaussian and non-Gaussian data. Multiple explanatory variables are dealt with by mixing simple additives to produce flexible high dimensional function estimates. Variable selection and model averaging will be used to identify important v ....Bayesian inference for complex regression models using mixtures. The project will use mixtures to flexibly model complex regression functions and will develop Bayesian methods for carrying out statistical inference on these models. The models will deal with both Gaussian and non-Gaussian data. Multiple explanatory variables are dealt with by mixing simple additives to produce flexible high dimensional function estimates. Variable selection and model averaging will be used to identify important variables and thus make the estimation more efficient. The methods will be extended to multivariate responses where account will taken be taken of the structure of the dependence between responses.Read moreRead less
The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop si ....The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop significantly faster and more accurate algorithms for this time varying eigenvalue problem than currently exist. Very modern techniques will be employed to achieve this aim, and the potential benefits to Australian hi-tech industries are great.
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Options For Proofs: New Perspectives on Propositional Logic. Philosophers and logicians recognise that proof is important, but they do not agree on what proofs are. Recent research in logic has greatly expanded our notion of proof, but this research is not unified. We need a coherent, general and applicable concept of proof. This project will unify the literature on proof and bring these insights to bear in the philosophy of language. It will show how proof can help analyse many features of ....Options For Proofs: New Perspectives on Propositional Logic. Philosophers and logicians recognise that proof is important, but they do not agree on what proofs are. Recent research in logic has greatly expanded our notion of proof, but this research is not unified. We need a coherent, general and applicable concept of proof. This project will unify the literature on proof and bring these insights to bear in the philosophy of language. It will show how proof can help analyse many features of language (more than just logical constants) but that the role of inference does not justify one kind of proof in preference to others.Read moreRead less