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Scheme : Linkage Projects
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Research Topic : computational modelling
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  • Funded Activity

    Linkage Projects - Grant ID: LP0347881

    Funder
    Australian Research Council
    Funding Amount
    $71,099.00
    Summary
    A Robust Optimization Technique for Identifying Geomechanical Parameters Using In-situ Measurements. The aim of this project is to develop a robust optimisation technique for identifying geomechanical parameters for subsequent stability analysis of rock structures in particular open pits. The development involves a novel solution method based on current work in finite element method and large-scale optimisation with partial differential equation constraints. The outcomes of the project will prov .... A Robust Optimization Technique for Identifying Geomechanical Parameters Using In-situ Measurements. The aim of this project is to develop a robust optimisation technique for identifying geomechanical parameters for subsequent stability analysis of rock structures in particular open pits. The development involves a novel solution method based on current work in finite element method and large-scale optimisation with partial differential equation constraints. The outcomes of the project will provide a sophisticated numerical technique for geotechnical engineers/scientists to determine geomechanical parameters accurately from in-situ observation and displacement measurements, leading to the optimal design of rock structures in subsequent analysis.
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    Funded Activity

    Linkage Projects - Grant ID: LP0347648

    Funder
    Australian Research Council
    Funding Amount
    $75,599.00
    Summary
    Better Batteries via Controlling the Properties of Electrolytic Manganese Dioxide. Physical properties of electrolytic manganese dioxide (EMD) such as crystal structure, morphology and electrochemical characteristics determine its usefulness in alkaline batteries. However, the relationship between these parameters is not well understood. This APAI project will attempt to address these shortcomings in the current understanding of the production process by focussing on the relationships between fu .... Better Batteries via Controlling the Properties of Electrolytic Manganese Dioxide. Physical properties of electrolytic manganese dioxide (EMD) such as crystal structure, morphology and electrochemical characteristics determine its usefulness in alkaline batteries. However, the relationship between these parameters is not well understood. This APAI project will attempt to address these shortcomings in the current understanding of the production process by focussing on the relationships between fundamental physical, chemical and electrochemical properties of EMD. The results will be of benefit in optimising the process and ensuring that EMD with superior performance can be consistently produced.
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    Funded Activity

    Linkage Projects - Grant ID: LP0562008

    Funder
    Australian Research Council
    Funding Amount
    $446,599.00
    Summary
    Investment Approaches and Applications in Financial Markets: Evolutionary Kernel Based Subset Time-Series Using Semi-Parametric Approaches. The project will develop new investment assessments based on subset time-series modeling. Innovative evolutionary kernel smoothing algorithms using semi-parametric approaches will be introduced. The project will make three important applications of this modeling in financial markets: a) benchmarking and evaluation of inflation-indexed bonds; b) evaluation of .... Investment Approaches and Applications in Financial Markets: Evolutionary Kernel Based Subset Time-Series Using Semi-Parametric Approaches. The project will develop new investment assessments based on subset time-series modeling. Innovative evolutionary kernel smoothing algorithms using semi-parametric approaches will be introduced. The project will make three important applications of this modeling in financial markets: a) benchmarking and evaluation of inflation-indexed bonds; b) evaluation of the performance of global diversified investment funds; and c) prediction to provide early warning of the emergence of destabilising deflation or inflation. These three applications will lead to improved risk management practices and investment performance. Recursive algorithms will provide new statistical methods to study investment asset price movements and market volatility.
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    Funded Activity

    Linkage Projects - Grant ID: LP0989811

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    Investment approaches and opportunities in renewable energy and financial resource markets, using semi-parametric approaches to evolutionary subset time-series lattice-ladder modelling. The project findings will help Australian exporters and importers understand and manage energy and resource price risks more effectively. The investment community will benefit through selecting optimal asset allocations and enhancing value to investors. It will also benefit many other agencies, particularly in th .... Investment approaches and opportunities in renewable energy and financial resource markets, using semi-parametric approaches to evolutionary subset time-series lattice-ladder modelling. The project findings will help Australian exporters and importers understand and manage energy and resource price risks more effectively. The investment community will benefit through selecting optimal asset allocations and enhancing value to investors. It will also benefit many other agencies, particularly in the service industries. It is not well recognised that in developed countries, including Australia, the financial service and related sectors account for more than 60 percent of economic activity and employment, so it is critical that more sophisticated statistical methods be established, and practical applications conducted, in order to advance the understanding of complexity management in the financial service and related sectors.
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    Funded Activity

    Linkage Projects - Grant ID: LP0883801

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    The improvement of investment approaches by developing and applying bootstrap methods to innovative evolutionary kernel-based subset time-series modelling. With over $1 trillion of investors' monies in the hands of fund managers, the importance of efficient investment decisions across all industry sectors is self evident. Even if the modest target of systematically improving decision making by 1 or 2 % is set, the aggregate economic benefit achieved, given the compounding effects will be enormou .... The improvement of investment approaches by developing and applying bootstrap methods to innovative evolutionary kernel-based subset time-series modelling. With over $1 trillion of investors' monies in the hands of fund managers, the importance of efficient investment decisions across all industry sectors is self evident. Even if the modest target of systematically improving decision making by 1 or 2 % is set, the aggregate economic benefit achieved, given the compounding effects will be enormous. Any developed or developing country will profit from such advanced decision-making approaches. Therefore it is critical that more sophisticated statistical methods be established, and practical applications conducted, in order to advance the understanding of complexity management in the financial investment and other relevant sectors.
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    Funded Activity

    Linkage Projects - Grant ID: LP0347461

    Funder
    Australian Research Council
    Funding Amount
    $345,000.00
    Summary
    Why is the photosynthetic CO2-fixing enzyme, Rubisco, so inefficient? Dissection of the catalytic chemistry by computational simulation and experimental testing. Fixation of CO2 by the enzyme Rubisco during photosynthesis produces organic compounds which feed all life. Despite this critical role, Rubisco catalyses its reaction sluggishly and, worse, discriminates poorly between CO2 and O2, leading to useless products. Our combined expertise equips us to analyse Rubisco's mechanism using quantum- .... Why is the photosynthetic CO2-fixing enzyme, Rubisco, so inefficient? Dissection of the catalytic chemistry by computational simulation and experimental testing. Fixation of CO2 by the enzyme Rubisco during photosynthesis produces organic compounds which feed all life. Despite this critical role, Rubisco catalyses its reaction sluggishly and, worse, discriminates poorly between CO2 and O2, leading to useless products. Our combined expertise equips us to analyse Rubisco's mechanism using quantum-chemical methods and then test predictions experimentally. We will capitalise on our previous successful studies of Rubisco by addressing emergent issues which are the keys to understanding catalytic efficiency and CO2/O2 selectivity: the roles of a carbamylated lysine; the way CO2 addition is rendered irreversible; and the spin inversion inherent in O2 addition.
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    Funded Activity

    Linkage Projects - Grant ID: LP0347620

    Funder
    Australian Research Council
    Funding Amount
    $240,000.00
    Summary
    Formally-Based Security Evaluation Procedures. Guaranteeing information security is of critical national importance, especially in the current political climate. Devices intended to safeguard Australia's electronic communications must be proven secure using leading-edge techniques. Currently, evaluation of such devices relies on informal procedures and the experience of individuals. This project will introduce more rigour into security evaluations by adapting techniques from the fields of saf .... Formally-Based Security Evaluation Procedures. Guaranteeing information security is of critical national importance, especially in the current political climate. Devices intended to safeguard Australia's electronic communications must be proven secure using leading-edge techniques. Currently, evaluation of such devices relies on informal procedures and the experience of individuals. This project will introduce more rigour into security evaluations by adapting techniques from the fields of safety analysis and formal methods. In particular, mathematical concepts will be introduced using notations suitable for use by security personnel with no prior formal methods experience. The outcomes of this project will enable more efficient and effective information security evaluations.
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    Funded Activity

    Linkage Projects - Grant ID: LP0455343

    Funder
    Australian Research Council
    Funding Amount
    $70,668.00
    Summary
    DEVELOPING A SMART FIRE RISK ADVISORY SYSTEM USING FIRE MODELLING AND KNOWLEDGE-BASED SYSTEMS TECHNOLOGIES. This project aims to develop a prototype fire risk advisory system for fire prevention and protection. Intelligent knowledge-based systems technologies will be tailored to provide a standardised approach for fire risk analysis by using collective expertise of fire engineers and fire modelling. This project will lead to a significant advancement to the development of intelligent systems tec .... DEVELOPING A SMART FIRE RISK ADVISORY SYSTEM USING FIRE MODELLING AND KNOWLEDGE-BASED SYSTEMS TECHNOLOGIES. This project aims to develop a prototype fire risk advisory system for fire prevention and protection. Intelligent knowledge-based systems technologies will be tailored to provide a standardised approach for fire risk analysis by using collective expertise of fire engineers and fire modelling. This project will lead to a significant advancement to the development of intelligent systems techniques for industrial applications and provide a better fire risk analysis tool for fire protection and preventions with the benefit of reduced risk for buildings.
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