Asset Intelligence: Maximising Operational Effectiveness for Digital Era . The primary aim of this project is to develop an innovative lifecycle semantic–based decision making approach through asset intelligence so as to maximize the operational effectiveness maintenance, repair and rehabilitation planning of infrastructure assets, such as concrete pavement. The research intends to address an important gap by providing logical formalisms and real-time capability to life-cycle asset information t ....Asset Intelligence: Maximising Operational Effectiveness for Digital Era . The primary aim of this project is to develop an innovative lifecycle semantic–based decision making approach through asset intelligence so as to maximize the operational effectiveness maintenance, repair and rehabilitation planning of infrastructure assets, such as concrete pavement. The research intends to address an important gap by providing logical formalisms and real-time capability to life-cycle asset information through computational intelligence. The expected outcome will be an intelligent asset management platform that provides structured and semantically enriched lifecycle asset information for optimised solutions to help reduce the cost, time and effort in asset information storage and retrieval, and decision-making. Read moreRead less
Achieving higher availability of storage subsystems through application of a self learning expert system. In todays global business environment the management, storage and security of enterprise data (data unavailability, data loss and corruption, systems performance) has become the heart of so-called Enterprise computing. The storage subsystems increasingly have become the critical subcomponent and single point of failure. Discovering the cause of failure in complex environments involving mul ....Achieving higher availability of storage subsystems through application of a self learning expert system. In todays global business environment the management, storage and security of enterprise data (data unavailability, data loss and corruption, systems performance) has become the heart of so-called Enterprise computing. The storage subsystems increasingly have become the critical subcomponent and single point of failure. Discovering the cause of failure in complex environments involving multiple vendors, machines, software products, topologies and cultures (languages) is in many cases time consuming and difficult resulting in unacceptable systems downtime and high maintenance costs. A more sophisticated tool is needed allowing the accumulation of knowledge, the ability to deal with complexity and change, the ability to interface with unlike knowledge bases and predict solution probability based on experience and feedback. Multi-lingual support and capability through the development of a Natural Language interface would provide a functional capability suited to managing enterprise data in todays global businesses.Read moreRead less
Optimizing steel industry supply chains through constraint and market-oriented programming. Supply chain optimization is a difficult problem, but of considerable significance to business enterprises. Constraint programming technology is a promising approach to solving such problems, but is inadequate in the context of dynamic supply chains. Market-oriented programming solves resource allocation problems by setting up artificial computational economies of trading software agents and holds promise ....Optimizing steel industry supply chains through constraint and market-oriented programming. Supply chain optimization is a difficult problem, but of considerable significance to business enterprises. Constraint programming technology is a promising approach to solving such problems, but is inadequate in the context of dynamic supply chains. Market-oriented programming solves resource allocation problems by setting up artificial computational economies of trading software agents and holds promise both as an optimization tool and as a tool that supports explicit market negotiation. This project seeks to address several open questions relating to the integrated deployment of these two classes of techniques, in the context of building a practical supply chain optimization system for BHP Steel.Read moreRead less
Integrated constraint-based planning and scheduling. Constraint programming is a relatively new technology based on artificial intellgence techniques that is becoming a popular tool for developing industrial optimisation solutions. While constraint programming has been used extensively for solving industrial scheduling problems, very little has been done in developing constraint-based integrated producting planning and scheduling systems. The size and complexity of typical production planning a ....Integrated constraint-based planning and scheduling. Constraint programming is a relatively new technology based on artificial intellgence techniques that is becoming a popular tool for developing industrial optimisation solutions. While constraint programming has been used extensively for solving industrial scheduling problems, very little has been done in developing constraint-based integrated producting planning and scheduling systems. The size and complexity of typical production planning and scheduling problems requires the innovative use of the latest developments in constraint programming technology, together with a variety of other artificial intelligence techniques. This project seeks to develop and implement a new conceptual framework for integrated constraint-based planning and scheduling, using BHP Steel as a test - bed.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
Incremental Knowledge Acquisition for Machine Translation from Multiple Experts. With increasing globalisation and an increasing amount of electronically available documents the need for machine translation is growing dramatically. The state-of-the-art in machine translation is still far from satisfactory. Substantial post-editing is necessary for most non-technical texts and even for many technical documents to make the translation really understandable. This project will develop a new approach ....Incremental Knowledge Acquisition for Machine Translation from Multiple Experts. With increasing globalisation and an increasing amount of electronically available documents the need for machine translation is growing dramatically. The state-of-the-art in machine translation is still far from satisfactory. Substantial post-editing is necessary for most non-technical texts and even for many technical documents to make the translation really understandable. This project will develop a new approach for buildingmachine translation systems by extending the unorthodox approach of Ripple-Down Rules, which proved very successful for building expert systems in the medical domain.It is intended to build a machine translation system by integrating the knowledge from many experts.Read moreRead less
Development of a fuel control system for small two-stroke engines. The two-stroke engine is well known not only for its mechanical simplicity and power-to-weight advantages, but also for its high hydrocarbon emission caused by fuel short-circuiting. Driven by new regulations, developing new technologies for small two-stroke engines to meet pollutant emission standards has become urgent. This project aims to develop a fuel control system for reducing hydrocarbon and other emissions of a two-strok ....Development of a fuel control system for small two-stroke engines. The two-stroke engine is well known not only for its mechanical simplicity and power-to-weight advantages, but also for its high hydrocarbon emission caused by fuel short-circuiting. Driven by new regulations, developing new technologies for small two-stroke engines to meet pollutant emission standards has become urgent. This project aims to develop a fuel control system for reducing hydrocarbon and other emissions of a two-stroke engine designed and produced by Australia's leading lawnmower manufacturer. The knowledge and technology developed will be broadly applicable. By reducing engine pollutant emissions and improving fuel energy efficiency, this research addresses environmental and energy efficiency imperatives.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
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
Thermo-mechanical interactive atlas of basin evolution. We propose to create a thermo-mechanical interactive atlas of basin evolution as a desktop geodynamic modelling resource for exploration geologists. The atlas will allow the user to iteratively run our 2D/3D basin modelling software ELLIPSIS to alter model parameters until they match observed basin geometries or thermal history. Model iteration will be based on interactive user evaluation of model outputs and genetic algorithms, which pr ....Thermo-mechanical interactive atlas of basin evolution. We propose to create a thermo-mechanical interactive atlas of basin evolution as a desktop geodynamic modelling resource for exploration geologists. The atlas will allow the user to iteratively run our 2D/3D basin modelling software ELLIPSIS to alter model parameters until they match observed basin geometries or thermal history. Model iteration will be based on interactive user evaluation of model outputs and genetic algorithms, which progressively modify the solution set by mimicking the evolutionary behavior of biological systems (selection, cross-over and mutation), until an acceptable result is achieved. The interactive atlas will be applied to Australian and international case studies.Read moreRead less