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Development of an international knowledgebase on urban transport policy instruments. This project will produce an on-line knowledgebase on urban transport policy instruments providing an understanding of the performance of such instruments from international experience. It will allow assessment of given instruments in different contexts, and identify opportunities for integration of policy instruments. It will assist decision-makers and interest groups to understand the role and potential of dif ....Development of an international knowledgebase on urban transport policy instruments. This project will produce an on-line knowledgebase on urban transport policy instruments providing an understanding of the performance of such instruments from international experience. It will allow assessment of given instruments in different contexts, and identify opportunities for integration of policy instruments. It will assist decision-makers and interest groups to understand the role and potential of different measures and provide a key source for transport researchers and educators. It will significantly assist achievement of urban transport policy objectives of reduced congestion; enhanced environment; greater safety; improved public health; better access; fairer opportunities; improved quality of life and increased sustainability.Read moreRead less
Control of Transitions in Wakes and Swirling Flows. We will attack industrially-important problems in fluid mechanics by building new, and substantially enhancing existing, international collaborations between key complementary teams of internationally-recognised French and Australian researchers. Funding will support the exchange of 6 senior staff and 3 graduate students, which, in turn, will measurably benefit the research output of a further 20 graduate students and 7 post-doctoral fellows as ....Control of Transitions in Wakes and Swirling Flows. We will attack industrially-important problems in fluid mechanics by building new, and substantially enhancing existing, international collaborations between key complementary teams of internationally-recognised French and Australian researchers. Funding will support the exchange of 6 senior staff and 3 graduate students, which, in turn, will measurably benefit the research output of a further 20 graduate students and 7 post-doctoral fellows associated with closely-related projects. From the Australian perspective, the planned exchanges will bring new research expertise, knowledge and skills, which will be focussed on a diverse range of applications. Target industries (with existing collaborations) include Airbus and Dassault Aviation in Europe, and Aerosonde and Warman pumps in Australia. Read moreRead less
Validation of Synthetic Regional Gravity Field Models. This research will further develop the theoretical and practical methods required to test any model of the Earth's gravity field. Previously, geodesists have had to rely on analytical error estimates, usually based on observed data. A synthetic Earth gravity model avoids this scenario by giving an exact validation technique of the methods used. The synthetic model will allow users of geoid models (e.g., for GPS heighting) to have much mor ....Validation of Synthetic Regional Gravity Field Models. This research will further develop the theoretical and practical methods required to test any model of the Earth's gravity field. Previously, geodesists have had to rely on analytical error estimates, usually based on observed data. A synthetic Earth gravity model avoids this scenario by giving an exact validation technique of the methods used. The synthetic model will allow users of geoid models (e.g., for GPS heighting) to have much more confidence in their results. When used with a precise geoid model, GPS is faster and cheaper than conventional spirit-levelling, offering around 800% productivity gains. Read moreRead less
Extending a family of garbage collectors. Garbage collection is a key component in the automatic management of storage in computer systems. It is an essential property of modern programming systems that frees the programmer from a significant error-prone task. Our interest is in garbage collection in distributed systems involving a number of networked computers. Using our novel construction methodology, we have jointly produced a family of collection algorithms that are significantly simpler and ....Extending a family of garbage collectors. Garbage collection is a key component in the automatic management of storage in computer systems. It is an essential property of modern programming systems that frees the programmer from a significant error-prone task. Our interest is in garbage collection in distributed systems involving a number of networked computers. Using our novel construction methodology, we have jointly produced a family of collection algorithms that are significantly simpler and more efficient than previous work. Here we wish to extend this family to operate effectively in a specific architecture increasingly favoured by many modern distributed high-performance computing systems.Read moreRead less
Asymptotic Geometric Analysis and Machine Learning. Phenomena in large dimensions appear in a number of domains of Mathematics and adjacent domains of science (e.g. Computer Science), dealing with functions of infinitely growing number of parameters. Here, we focus on several questions naturally linked to Asymptotic Geometric Analysis which have natural applications to Statistical Learning Theory. We intend to use geometric, probabilistic and combinatorial methods to investigate these problems, ....Asymptotic Geometric Analysis and Machine Learning. Phenomena in large dimensions appear in a number of domains of Mathematics and adjacent domains of science (e.g. Computer Science), dealing with functions of infinitely growing number of parameters. Here, we focus on several questions naturally linked to Asymptotic Geometric Analysis which have natural applications to Statistical Learning Theory. We intend to use geometric, probabilistic and combinatorial methods to investigate these problems, with an emphasis on modern tools in Empirical Processes Theory and the theory of Random Matrices.Read moreRead less
Managing Knowledge in Web-Driven Organisational Evolution. Organisations are increasingly concerned with the effective utilisation of Web technologies, and especially the ways in which these technologies can be used to improve their business. Effective management of knowledge about the interplay between the organisation and technical drivers of this technology adoption will enable a much-enhanced process for leveraging emerging information and communication technologies. This project aims to li ....Managing Knowledge in Web-Driven Organisational Evolution. Organisations are increasingly concerned with the effective utilisation of Web technologies, and especially the ways in which these technologies can be used to improve their business. Effective management of knowledge about the interplay between the organisation and technical drivers of this technology adoption will enable a much-enhanced process for leveraging emerging information and communication technologies. This project aims to link related research at UTS and Southampton University to understand how tools might support this knowledge management. Outcomes will include the creation of specific tools (and techniques for using them) within the context of managing organisational uptake of new technologies.Read moreRead less
Quantum correlations in ultra-cold Fermi gases. The field of ultra-cold Fermi gases provides a unique opportunity to develop and test theoretical methods for novel experimental environments of exceptional purity and simplicity. This improved understanding will have potential applications in many fields, ranging from the astrophysics of neutron stars to condensed matter systems such as superconductors or nanostructures. Just as importantly, the project will develop linkages with world leading the ....Quantum correlations in ultra-cold Fermi gases. The field of ultra-cold Fermi gases provides a unique opportunity to develop and test theoretical methods for novel experimental environments of exceptional purity and simplicity. This improved understanding will have potential applications in many fields, ranging from the astrophysics of neutron stars to condensed matter systems such as superconductors or nanostructures. Just as importantly, the project will develop linkages with world leading theoretical groups, which will greatly aid research student education. There are direct applications to experiments on molecule formation with ultra-cold fermions in the ARC Centre of Excellence for Quantum-Atom Optics.Read moreRead less
An Integrated Ground Deformation Monitoring System Based on the Integration of InSAR, GPS and GIS Technologies. Interferometric Synthetic Aperture Radar (InSAR) can be used to monitor ground deformation at high spatial resolution. When integrated with Global Positioning Systems (GPS) so that atmospheric disturbance in InSAR result can be corrected, deformation can be resolved at sub-centimetre accuracy. The corrected InSAR result can be exported as a data layer into Geographic Information System ....An Integrated Ground Deformation Monitoring System Based on the Integration of InSAR, GPS and GIS Technologies. Interferometric Synthetic Aperture Radar (InSAR) can be used to monitor ground deformation at high spatial resolution. When integrated with Global Positioning Systems (GPS) so that atmospheric disturbance in InSAR result can be corrected, deformation can be resolved at sub-centimetre accuracy. The corrected InSAR result can be exported as a data layer into Geographic Information Systems (GIS) for further analysis. In collaboration with Hong Kong Polytechnic University researchers, the integrated InSAR-GPS-GIS system will be tested in both Hong Kong and Australia. The expected outcomes include a suite of algorithms and software tools capable of operational, cost-effective ground deformation monitoring.Read moreRead less
Investigations into machine learning applications in link analysis. Link analysis is an emerging tool for the detection of patterns in structured data. The detection of pattern in such data can lead to the detection of fraud occurrence, security breaches in computer systems, and patterns of social interactions with a community. It is also popularly applied to applications such as Web search engine designs and marketing analysis. This project aims to advance the area of link analysis by allowing ....Investigations into machine learning applications in link analysis. Link analysis is an emerging tool for the detection of patterns in structured data. The detection of pattern in such data can lead to the detection of fraud occurrence, security breaches in computer systems, and patterns of social interactions with a community. It is also popularly applied to applications such as Web search engine designs and marketing analysis. This project aims to advance the area of link analysis by allowing the incorporation of contextual information which accounts for relationships among actors properly. Advances in link detection will allow improvements in security and Web services on which a wide field of national bodies rely. This project can help to place Australia at the forefront of this research area.Read moreRead less
Ensembles of Collaborative Neural Networks. Artificial neural networks have been used successfully for data mining and control. A neural network ensemble(NNE) is a collection of networks that exhibits properties of self-organization, plasticity, and adaptive behaviour. The aim of this research is to develop an efficient and theoretically sound algorithm for NNE learning. The outcomes of the project will include insights into self-organization of complex NNE and automatic problem decomposition an ....Ensembles of Collaborative Neural Networks. Artificial neural networks have been used successfully for data mining and control. A neural network ensemble(NNE) is a collection of networks that exhibits properties of self-organization, plasticity, and adaptive behaviour. The aim of this research is to develop an efficient and theoretically sound algorithm for NNE learning. The outcomes of the project will include insights into self-organization of complex NNE and automatic problem decomposition and an efficient algorithm for constructing and training NNE. Practical outcomes will include research training for early career researchers and new modelling tools for data mining, robotics and multi-agent systems. The project contributes to the national priority area of smart information use.Read moreRead less