Visual interaction methods for clustered graphs. This project aims to improve human understanding of huge network data sets, such as those arising in social networks, biological networks, and very large software structures. The project will enable analysts to explore and interact with such data sets, leading to better understanding.
Control points in nitrogen uptake: enhancing the response of cereals to nitrogen supply and demand. Vast amounts of nitrogen fertiliser are applied to cereal crops to maintain yields. By uncovering what limits nitrogen uptake in cereals, this project will provide the scientific basis for improving nitrogen use efficiency and decreasing fertiliser use, with significant economic and environmental benefits.
Investigation and Development of Parallel Large Scale Record Linkage Techniques. Record linkage aims at matching records of the same entity (like customer or patient) in large (administrative) databases. The outcomes of the proposed research will improve current techniques in terms of efficiency, accuracy and the need for human intervention. Through experimental studies and stochastic modelling the performance of traditional and new methods for data cleaning, standardisation and linkage will be ....Investigation and Development of Parallel Large Scale Record Linkage Techniques. Record linkage aims at matching records of the same entity (like customer or patient) in large (administrative) databases. The outcomes of the proposed research will improve current techniques in terms of efficiency, accuracy and the need for human intervention. Through experimental studies and stochastic modelling the performance of traditional and new methods for data cleaning, standardisation and linkage will be assessed. The effect of the statistical dependency of attribute values will be studied. New methods using clustering for blocking large datasets, and predictive models including interaction terms will be implemented, analysed and evaluated on high-performance computers and office-based PC clusters.
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Algebraic Methods in Design and Analysis of Stream Ciphers. The project investigates the problem of communication security in the mobile environment where both confidentiality and authenticity are of prime concern. Stream ciphers are a very natural choice in mobile environment as they provide an efficient cryptographic protection using a limited computing resources. We model stream cipher as a system of multivariate equations. In this approach, security of stream ciphers can be measured as the c ....Algebraic Methods in Design and Analysis of Stream Ciphers. The project investigates the problem of communication security in the mobile environment where both confidentiality and authenticity are of prime concern. Stream ciphers are a very natural choice in mobile environment as they provide an efficient cryptographic protection using a limited computing resources. We model stream cipher as a system of multivariate equations. In this approach, security of stream ciphers can be measured as the complexity of an algorithm that solves the appropriate system of equations. This project leads to new techniques for the design and analysis of stream ciphers.Read moreRead less
Genome-wide determination of Puccinia psidii s.l. rust resistance in eucalypts. Recently, guava rust was detected in Australia, posing significant risks to native flora, plantations, and timber exports. Scientists from The University of Melbourne and Victorian Department of Primary Industries together with tree breeders, forest growers and forest managers aim to use tree genomics rust resistance breeding to enable management and operational responses and inform policy development.
Development of biosensors and bioindicators for gold exploration and processing in Australia. In times of increasing demand for gold and shrinking rates of discovery in Australia, biosensor and bioindicator techniques deliver significant advantages to the Australian mining industry and allow it to retain its international competiveness. The new understanding of the biogeochemical behaviour of gold in soils and other weathered materials developed in a previous ARC Linkage Project enables the deve ....Development of biosensors and bioindicators for gold exploration and processing in Australia. In times of increasing demand for gold and shrinking rates of discovery in Australia, biosensor and bioindicator techniques deliver significant advantages to the Australian mining industry and allow it to retain its international competiveness. The new understanding of the biogeochemical behaviour of gold in soils and other weathered materials developed in a previous ARC Linkage Project enables the development of biosensor and bioindicator technology that will allow mineral explorers to differentiate mineralised from non-mineralised zones using specific (meta) genomic community responses. The new technology will provide cost-efficient and environmentally sustainable techniques for improving exploration success and optimising ore processing.Read moreRead less
From genotype to phenotype: Molecular photofitting for criminal investigations. DNA found at crime scenes has the potential to provide a physical description of the donor in the same way as an eyewitness statement can be used to make a facial reconstruction. This project will investigate those physical traits which can be derived from the analysis of DNA present in samples collected in relation to criminal activities.
Developing a robust model for pricing inter-related volatility-based financial derivative contracts. Volatility-based financial contracts were developed in the late 1990s to provide an easy way for investors to gain exposure to the future level of volatility and thus provide a means by which they could speculate on its future levels and also hedge unpredictable volatility risk. This would potentially save them from losing vast quantities of money. However these products can only be efficient pr ....Developing a robust model for pricing inter-related volatility-based financial derivative contracts. Volatility-based financial contracts were developed in the late 1990s to provide an easy way for investors to gain exposure to the future level of volatility and thus provide a means by which they could speculate on its future levels and also hedge unpredictable volatility risk. This would potentially save them from losing vast quantities of money. However these products can only be efficient products for trading and risk management if they are priced correctly. This project will benefit investors by providing empirically viable models that will be able to be easily implemented to provide accurate and fast pricing solutions.Read moreRead less
Multi-phase modelling and characterisation of mudrush hazard in cave mining. A mudrush is a sudden, uncontrolled flow of wet fine particles (mud) into an underground mine that damages equipment, infrastructure, and can even cause fatalities. This project aims to develop cost-effective management and monitoring of mudrush hazards within the at-risk Carrapateena cave mine operated by OZ Minerals. Building on recent technological and numerical advances, a novel experimental–theoretical–numerical ap ....Multi-phase modelling and characterisation of mudrush hazard in cave mining. A mudrush is a sudden, uncontrolled flow of wet fine particles (mud) into an underground mine that damages equipment, infrastructure, and can even cause fatalities. This project aims to develop cost-effective management and monitoring of mudrush hazards within the at-risk Carrapateena cave mine operated by OZ Minerals. Building on recent technological and numerical advances, a novel experimental–theoretical–numerical approach will be used to simulate mudrush risk based on moisture content, particle sizes, compaction, geological conditions, and seismic energy. Outputs will include a practical framework to boost the safety, productivity, and profitability of caving operations to benefit miners and the broader resources industry.Read moreRead less
Identifying technological trajectories using machine learning algorithms. This project aims to improve our understanding of why scientific knowledge progresses in certain directions and what causes it to grow faster or slower across fields. The project will create new neural-network machine-learning algorithms to scan patent and scientific article texts (specifications and claims) for natural language concepts. The results will potentially be used by patent offices to improve their own database ....Identifying technological trajectories using machine learning algorithms. This project aims to improve our understanding of why scientific knowledge progresses in certain directions and what causes it to grow faster or slower across fields. The project will create new neural-network machine-learning algorithms to scan patent and scientific article texts (specifications and claims) for natural language concepts. The results will potentially be used by patent offices to improve their own database search, by business analytics companies to reveal new technologies and potential collaborators, and by academic economists to understand how knowledge travels and accumulates.
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