Predictive Assessment Tool for Beach Conditions Using Video Imaging and Neural Network Analysis. Beaches are vital part of Australian lifestyle and economic development. Monitoring of variable beach conditions is vital for beach safety and for management of storm erosion. The aim of this project is to develop an assessment tool which will permit a rating system of beach conditions both from an environmental as well as a leisure aspect. This tool will be developed into a software analysis system ....Predictive Assessment Tool for Beach Conditions Using Video Imaging and Neural Network Analysis. Beaches are vital part of Australian lifestyle and economic development. Monitoring of variable beach conditions is vital for beach safety and for management of storm erosion. The aim of this project is to develop an assessment tool which will permit a rating system of beach conditions both from an environmental as well as a leisure aspect. This tool will be developed into a software analysis system which will include components of artificial intelligence to enable the system to use feedback loops to create a better prediction of the beach morphology relative to the breaking wave characteristics.Read moreRead less
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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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.Read moreRead less
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.Read moreRead less
Emergency Control of Catastrophic Disturbances in a Power System. Following the tragic events of 11 September 2001, there are increased concerns about the security and robustness of power systems to evolving spectra of threats, such as natural disasters (e.g., earthquakes and hurricanes), equipment failure, human error, or deliberate sabotage and attack by terrorists. In this project, pattern recognition of local parameter changes in distributed monitoring systems will be used to identify any th ....Emergency Control of Catastrophic Disturbances in a Power System. Following the tragic events of 11 September 2001, there are increased concerns about the security and robustness of power systems to evolving spectra of threats, such as natural disasters (e.g., earthquakes and hurricanes), equipment failure, human error, or deliberate sabotage and attack by terrorists. In this project, pattern recognition of local parameter changes in distributed monitoring systems will be used to identify any threatened breakdown in the power system. Once identified, methods based on intelligent agents will be used to trigger the appropriate countermeasures to maintain the integrity of transmission grids.Read moreRead less
An Advanced Numerical Technique for Stability Analysis of Mining Excavations in Jointed/Faulted Rock Masses under High Stresses. The aim of this project is to develop a sophisticated mathematical model and computational technique for the stability analysis of mining excavations in jointed/faulted rock masses. The development involves a novel solution method based on current work in finite element method, boundary element method and large-scale optimisation with partial differential equation cons ....An Advanced Numerical Technique for Stability Analysis of Mining Excavations in Jointed/Faulted Rock Masses under High Stresses. The aim of this project is to develop a sophisticated mathematical model and computational technique for the stability analysis of mining excavations in jointed/faulted rock masses. The development involves a novel solution method based on current work in finite element method, boundary element method and large-scale optimisation with partial differential equation constraints. The work is extremely important to the mining industry in Australia, as the outcomes of the project will provide engineers with an innovative simulation technique to optimise mine design and to predict and control rock failure so as to reduce personnel injuries and death toll in mine sites.Read moreRead less
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.Read moreRead less
Computer simulation techniques to reduce the incidence of femoral fracture after hip replacement surgery. Australia's ageing population is driving an increase of 5% to 10% a year in the number of primary total hip replacements. We will move beyond conventional surgical techniques, to deliver the science for an accurate, reliable computer-based system that is significantly more accurate and reliable. Optimising implant selection criteria to better match patients' activity levels and bone physiolo ....Computer simulation techniques to reduce the incidence of femoral fracture after hip replacement surgery. Australia's ageing population is driving an increase of 5% to 10% a year in the number of primary total hip replacements. We will move beyond conventional surgical techniques, to deliver the science for an accurate, reliable computer-based system that is significantly more accurate and reliable. Optimising implant selection criteria to better match patients' activity levels and bone physiology and minimise revision rates; this has major implications for the national health budget and patients' quality of life. Our advances will allow the implementation of improved surgical techniques that minimise the risk of implant related bone failure.Read moreRead less
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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OPTIMISATION OF COMPACT BOILING HEAT EXCHANGERS USING ARTIFICIAL NEURAL NETWORK. Compact heat exchangers are increasingly considered for duties in many industrial applications, involving phase change processes of boiling and condensation. In many cases such applications are completely new and no previous experience or information is available for constructive design of compact heat exchangers. This project aims to develop a commercially-viable design methodology that will be innovative and novel ....OPTIMISATION OF COMPACT BOILING HEAT EXCHANGERS USING ARTIFICIAL NEURAL NETWORK. Compact heat exchangers are increasingly considered for duties in many industrial applications, involving phase change processes of boiling and condensation. In many cases such applications are completely new and no previous experience or information is available for constructive design of compact heat exchangers. This project aims to develop a commercially-viable design methodology that will be innovative and novel with in mind of robust and speedy computations of key design parameters of compact boiling heat exchangers through the artificial neural networks (ANN) model and maintaining the inherent accuracy associated with the solutions of the boiling flow and heat transfer processes from computational fluid dynamics (CFD) and validated using experimental data. It will provide a cutting edge to the Industry Partner to compete successfully on the local and global market fronts in designing and manufacturing compact boiling heat exchangers.Read moreRead less