Improving the modelling of insolvency risk and financial health assessment of global companies using hybrid intelligent techniques. The social and economic impacts of corporate collapses are severe, and much research has modelled financial health and insolvency risk of companies. Most research, however, uses simple and out-dated financial ratios used by Altman (1968), and attempts to develop a universal model valid for specific (non-global) markets. Our approach is to improve the relevance of th ....Improving the modelling of insolvency risk and financial health assessment of global companies using hybrid intelligent techniques. The social and economic impacts of corporate collapses are severe, and much research has modelled financial health and insolvency risk of companies. Most research, however, uses simple and out-dated financial ratios used by Altman (1968), and attempts to develop a universal model valid for specific (non-global) markets. Our approach is to improve the relevance of the information provided to the models (including measures of strategy, recent accounting metrics, global context). We also challenge the merits of a universal model by developing and testing a novel hybrid intelligent approach combining neural networks, genetic algorithms and self-organising maps, applicable to global markets.Read moreRead less
Vision Model Based Perceptual Digital Video Coding. Digital video coding and compression is an enabling technology and has diversified applications in audiovisual communications, multimedia computing, digital television broadcast and electronic entertainment industries. The project aims at spearheading research in theory, techniques and implementation of perceptual video coding in order to achieve constant and guaranteed quality in visual communications and services. It will explore a new appr ....Vision Model Based Perceptual Digital Video Coding. Digital video coding and compression is an enabling technology and has diversified applications in audiovisual communications, multimedia computing, digital television broadcast and electronic entertainment industries. The project aims at spearheading research in theory, techniques and implementation of perceptual video coding in order to achieve constant and guaranteed quality in visual communications and services. It will explore a new approach to digital video coding other than the constant bit rate coding techniques which have dominated digital video research for the past four decades. It will form a part of the theoretical foundation and principles for the next generation video coding and compression techniques, and may lead to new standards and practice.Read moreRead less
Intelligent techniques to exploit the dynamic temporal structure in detection of attacks in credit application fraud. Obtaining credit using fraudulent information costs financial institutions billions of dollars. This project develops fraud detection methods in credit applications, working with credit bureau data. Existing fraud detection models are mostly applicable to transaction fraud, rather than application fraud, and are static. Fraudsters however constantly change their method of attack. ....Intelligent techniques to exploit the dynamic temporal structure in detection of attacks in credit application fraud. Obtaining credit using fraudulent information costs financial institutions billions of dollars. This project develops fraud detection methods in credit applications, working with credit bureau data. Existing fraud detection models are mostly applicable to transaction fraud, rather than application fraud, and are static. Fraudsters however constantly change their method of attack. The temporal characteristics of fraud attacks provide an additional source of information that can be exploited to gain increased predictive power. We propose a hybrid intelligent approach to construct models that are sensitive to the temporal dynamics of fraud attacks, and evolve to acknowledge the changing behaviour of fraudsters.Read moreRead less
On Line Real Time Inspection of Vehicle Structures. The aim of this project is to develop an automated, on-line, real-time, inspection system that can detect incorrect placement or absence of specific components on the underside of a vehicle structure. The inspection system is to be integrated with a factory wide quality control and information gathering system. Development of an automated inspection system will enable the reliable identification of defects and tracking of quality levels in the ....On Line Real Time Inspection of Vehicle Structures. The aim of this project is to develop an automated, on-line, real-time, inspection system that can detect incorrect placement or absence of specific components on the underside of a vehicle structure. The inspection system is to be integrated with a factory wide quality control and information gathering system. Development of an automated inspection system will enable the reliable identification of defects and tracking of quality levels in the final assembly station. The expected outcome is the design and implementation in prototype form, of an intelligent, automated inspection system that can accommodate a wide range of product variants.Read moreRead less
Development of an Integrated Platform for Performance-Based Safety Assessment. Building fires are the cause of major fatalities and injuries amongst all types of accidental fires in Australia. With significant advancement in numerical simulation technique, computer models are becoming acceptable tools for fire safety designs. Nonetheless, these methods still suffer from large amount of manual inputs and lengthy computational times. This research project will address the prevalent deficiency in m ....Development of an Integrated Platform for Performance-Based Safety Assessment. Building fires are the cause of major fatalities and injuries amongst all types of accidental fires in Australia. With significant advancement in numerical simulation technique, computer models are becoming acceptable tools for fire safety designs. Nonetheless, these methods still suffer from large amount of manual inputs and lengthy computational times. This research project will address the prevalent deficiency in many of these computer models and develop a novel and innovative design methodology. The success of this project will revolutionize the computational tools for the industry realizing a convenient, robust and time-saving integrated platform catering for increasing future market demand.Read moreRead less
Smart Task Allocation Support for Small-Scale Printing Factory. The outcomes will give the Australian small-scale printing industry the capability to be competitive and cost-effective while looking after the wellbeing of its workforce. The understanding of complex relationships between various tasks in small-scale printing environments will improve the wellbeing of workers. The smart computer system will provide a frontier technology that will improve the profitability and efficiency. It will al ....Smart Task Allocation Support for Small-Scale Printing Factory. The outcomes will give the Australian small-scale printing industry the capability to be competitive and cost-effective while looking after the wellbeing of its workforce. The understanding of complex relationships between various tasks in small-scale printing environments will improve the wellbeing of workers. The smart computer system will provide a frontier technology that will improve the profitability and efficiency. It will also result in a cutting edge technology that is applicable to other similar industries.Read moreRead less
Explainable machine learning for electrification of everything. The energy sector is the largest contributor to greenhouse gas emissions. "Electrification of Everything" combined with electricity generation from renewables is a key solution to decarbonise the energy and transport sectors. This project aims to develop an explainable machine learning based data-driven technology to accurately predict the impact of electrification on consumers energy consumption and cost. The expected outcome of th ....Explainable machine learning for electrification of everything. The energy sector is the largest contributor to greenhouse gas emissions. "Electrification of Everything" combined with electricity generation from renewables is a key solution to decarbonise the energy and transport sectors. This project aims to develop an explainable machine learning based data-driven technology to accurately predict the impact of electrification on consumers energy consumption and cost. The expected outcome of this project includes a data-informed decision support technology to help consumers choose the best electrification technologies and solutions. This should provide significant benefits, such as increasing community engagement with electrification, and thus reducing their carbon footprint.Read moreRead less
Intelligently Activated Sensor Clusters for E-Commerce Applications. This project will investigate intelligent management of large sensor clusters installed in mechanical structures for use in Electronic Commerce applications. Finding algorithms for optimised placement of remotely controlled power supply and the communication unit in each sensor cluster is the first aim. Development of a sensor management algorithm that process user inputs submitted through the Internet and that exploits past se ....Intelligently Activated Sensor Clusters for E-Commerce Applications. This project will investigate intelligent management of large sensor clusters installed in mechanical structures for use in Electronic Commerce applications. Finding algorithms for optimised placement of remotely controlled power supply and the communication unit in each sensor cluster is the first aim. Development of a sensor management algorithm that process user inputs submitted through the Internet and that exploits past sensor data is the second aim. Since there is no such system available in the market, the project will have strong impacts in E-Commerce applications and bridge instrumentation systems useful to a wider community also advancing the research in clustering and expert systems.Read moreRead less
Maximising the Effectiveness of Public Health Policies: The Case of Smoke-Free Policies. Promoting good health and well being for all Australians is a key National Research Priority. Tobacco smoking is the largest single preventable cause of death in Australia, and while much has been achieved in tobacco control in Australia, there has been little systematic effort to understand or improve the relationship between research and policy implementation. This project will provide a deeper and more so ....Maximising the Effectiveness of Public Health Policies: The Case of Smoke-Free Policies. Promoting good health and well being for all Australians is a key National Research Priority. Tobacco smoking is the largest single preventable cause of death in Australia, and while much has been achieved in tobacco control in Australia, there has been little systematic effort to understand or improve the relationship between research and policy implementation. This project will provide a deeper and more sophisticated understanding of both how to maximise the effectiveness of smoke-free policies, and, through that increased understanding, how to best manage the implementation of public policies that seek to facilitate changes in the behaviour of individual citizens. Read moreRead less
Congestion management in key road networks of a major city through real time data collection, intelligent forecasting and real time routing. The project researches the issues for allowing Australian Road Traffic Authorities to automatically capture road traffic data, forecast traffic flows and smartly route traffic flows to avoid congestion on road networks. This will lead to several benefits, such as (a) reducing traffic congestion, shorten travel time and lower pollution, (b) better utilizati ....Congestion management in key road networks of a major city through real time data collection, intelligent forecasting and real time routing. The project researches the issues for allowing Australian Road Traffic Authorities to automatically capture road traffic data, forecast traffic flows and smartly route traffic flows to avoid congestion on road networks. This will lead to several benefits, such as (a) reducing traffic congestion, shorten travel time and lower pollution, (b) better utilization of existing road infrastructure by diffusing traffic to alternate routes, (c) provide economic benefit by allowing one to delay infrastructure expansion, (d) monitoring of aberrant behaviour by road users to ensure a safer road environment, and (e) improved flexibility in deployment of the Wireless Sensor Network to meet the needs of the road authorities and community.Read moreRead less