Next Generation Grid Enabled Cluster Computers: Performance Optimisation for e-Science. In partnership with a local computer company this project will develop cost effective cluster computing solutions assembled from off-the-shelf parts for $50,000-$200,000. This price range is currently relatively poorly serviced by the multinational computer vendors, who tend to focus on the high density compute systems necessary for very large cluster systems. As a consequence the development of high performa ....Next Generation Grid Enabled Cluster Computers: Performance Optimisation for e-Science. In partnership with a local computer company this project will develop cost effective cluster computing solutions assembled from off-the-shelf parts for $50,000-$200,000. This price range is currently relatively poorly serviced by the multinational computer vendors, who tend to focus on the high density compute systems necessary for very large cluster systems. As a consequence the development of high performance computing in Australia has been somewhat stifled compared to the US or UK, where there exist small niche companies servicing this market sector. This project aims to change this, developing affordable high performance cluster computing systems for the Australian market place and beyond.Read moreRead less
Learning Medical Image Knowledge. We aim to develop Machine Learning and Knowledge Acquisition techniques for automated recognition of features in medical images, and to provide decision support for diagnosis from medical images. The project is innovative in its use of layered learning, where the computer first learns to recognise low-level image features that are then used to learn more complex features. The project is also innovative in combining a variety of automatic learning methods, includ ....Learning Medical Image Knowledge. We aim to develop Machine Learning and Knowledge Acquisition techniques for automated recognition of features in medical images, and to provide decision support for diagnosis from medical images. The project is innovative in its use of layered learning, where the computer first learns to recognise low-level image features that are then used to learn more complex features. The project is also innovative in combining a variety of automatic learning methods, including relational learning, with human-assisted knowledge acquisition methods. The expected outcomes will be new techniques for image understanding, particularly for our test domain, namely, High Resolution Computed Tomography scans of the lung.Read moreRead less
Integrating Model Checking and Knowledge Dynamics for System Verification. The task of system verification is to ensure the correctness of system design and specification in some automatic way. The aim of this project is to develop a new methodology and technology for computer software system verification by integrating traditional model checking approach and knowledge dynamics modeling. By deriving the results of this project, we will understand how model checking and knowledge dynamics modelin ....Integrating Model Checking and Knowledge Dynamics for System Verification. The task of system verification is to ensure the correctness of system design and specification in some automatic way. The aim of this project is to develop a new methodology and technology for computer software system verification by integrating traditional model checking approach and knowledge dynamics modeling. By deriving the results of this project, we will understand how model checking and knowledge dynamics modeling can be integrated for more effective software verification and modification, which will significantly improve current software design and development procedures, increase the correctness and stability of software systems, and provide high security for e-Commerce transaction systems.Read moreRead less
Feature Detection and Computer-aided Diagnosis with Longitudinal Tracking of Benign Asbestos-Related Pleural Disease in CT images. This project seeks to develop smart and novel feature extraction and knowledge acquisition techniques to assist radiologists in automated diagnosis and assessment of lung diseases. These outcomes will lead to improved delivery of health services in Australia, including in rural regions. They will lead to more accurate assessment of asbestos related pleural diseases f ....Feature Detection and Computer-aided Diagnosis with Longitudinal Tracking of Benign Asbestos-Related Pleural Disease in CT images. This project seeks to develop smart and novel feature extraction and knowledge acquisition techniques to assist radiologists in automated diagnosis and assessment of lung diseases. These outcomes will lead to improved delivery of health services in Australia, including in rural regions. They will lead to more accurate assessment of asbestos related pleural diseases for compensation and treatment and better followup, leading to earlier treatment and better quality of life for patients suffering from lung diseases. The project will also save costs due to automated assessment as well as the potential for fewer patient scans.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
Intelligent Design Advisor for Manufacturing Process Knowledge within Concurrent Engineering in the Aerospace Industry. At present the design of engineering components in the aerospace industry is accomplished by experts from design and manufacturing either sequentially or in collaboration. If performed in sequence then time and quality is jeopardised. If performed in collaboration then more manpower than is necessary is expended. The aim of this project is to develop an intelligent design advis ....Intelligent Design Advisor for Manufacturing Process Knowledge within Concurrent Engineering in the Aerospace Industry. At present the design of engineering components in the aerospace industry is accomplished by experts from design and manufacturing either sequentially or in collaboration. If performed in sequence then time and quality is jeopardised. If performed in collaboration then more manpower than is necessary is expended. The aim of this project is to develop an intelligent design advisor for Manufacturing Process Knowledge that will provide this expert knowledge to the design engineer in order to speed up the design process while reducing costs and still maintaining the high standard of quality necessary in the Aerospace industry.Read moreRead less
A novel cooperative global information system for healthcare. This project will develop a global model for healthcare based on the groundbreaking Protocol Hypothesis Testing (PHT) system, allowing expert groups of clinicians to create and share knowledge across organizations. The PHT is a unique functioning knowledge management system that allows clinicians to record patient and treatment data as it is generated in clinical practice and applies scientific methods to generate clinical knowledge, ....A novel cooperative global information system for healthcare. This project will develop a global model for healthcare based on the groundbreaking Protocol Hypothesis Testing (PHT) system, allowing expert groups of clinicians to create and share knowledge across organizations. The PHT is a unique functioning knowledge management system that allows clinicians to record patient and treatment data as it is generated in clinical practice and applies scientific methods to generate clinical knowledge, all in real-time. The project will develop and test a framework for the PHT system to be used cooperatively by expert groups across virtual organizations, refining the PHT system in the process.Read moreRead less
Intelligent Decision Support for Neonatal Analysis and Trend Detection. Nearly five percent of newborn babies require intensive care after birth. Several electronic instruments monitor a baby's vital signs such as blood oxygen, blood pressure and heart rate. A major limitation in neonatal clinical management is that the physiological data generated by the monitors is not extracted to provide an integrated picture of the baby's condition or to enable detection of trends and patterns in clinical a ....Intelligent Decision Support for Neonatal Analysis and Trend Detection. Nearly five percent of newborn babies require intensive care after birth. Several electronic instruments monitor a baby's vital signs such as blood oxygen, blood pressure and heart rate. A major limitation in neonatal clinical management is that the physiological data generated by the monitors is not extracted to provide an integrated picture of the baby's condition or to enable detection of trends and patterns in clinical and real-time physiological data. This project will develop a methodology and technology that supports neonatal analysis incorporating a framework to mine data for trend detection, resulting in higher survival rates.Read moreRead less
High Frequency Data Stream Event Correlation for Complex Neonatal Medical Alerts. Nearly twenty percent of newborn babies require intensive care after birth. Several electronic instruments monitor a baby's vital signs such as blood oxygen, blood pressure and heart rate. A major limitation in neonatal clinical management is that the data generated by these monitors is not integrated to enable the alerting of condition deterioration or early warning of possible condition onset. This project will d ....High Frequency Data Stream Event Correlation for Complex Neonatal Medical Alerts. Nearly twenty percent of newborn babies require intensive care after birth. Several electronic instruments monitor a baby's vital signs such as blood oxygen, blood pressure and heart rate. A major limitation in neonatal clinical management is that the data generated by these monitors is not integrated to enable the alerting of condition deterioration or early warning of possible condition onset. This project will develop a methodology and technology that supports the cross correlation of neonatal clinical and physiological data for complex neonatal medical alerts, through the use of agents within an event stream processor, resulting in higher survival rates.Read moreRead less
Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are a ....Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are at high risk of incurring debt and defaulting on paying taxes. In turn, the early identification of clients in financial distress will allow the ATO to give them assistance so that they can reduce their debts and meet their financial obligations.Read moreRead less