Reconceiving Machine Learning. The proposed research will develop a new way to consider problems to which machine learning can be applied. Machine learning is crucial enabler of the digital economy. The research will provide better opportunities for Australian industry to gain a competitive advantage with machine learning technology. The framework developed will enable better opportunities for collaborative research and will build and strengthen international linkages.
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
Managing quality of experience delivery in new generation telecommunications networks with e-negotiation. New generation telecommunications networks are required to support increasingly demanding services, including interactive multimedia and conferencing. The success of these networks will rely on the users' perception of their quality of experience. The management of these networks will rely on the ability of informed decision making that competes effectively for limited resources in such a ....Managing quality of experience delivery in new generation telecommunications networks with e-negotiation. New generation telecommunications networks are required to support increasingly demanding services, including interactive multimedia and conferencing. The success of these networks will rely on the users' perception of their quality of experience. The management of these networks will rely on the ability of informed decision making that competes effectively for limited resources in such a highly dynamic environment. This project will design information distribution strategies and smart decision making agents that negotiate a user's quality of experience using market mechanisms. Designs from this project will be trialled and validated in the partner's commercial networks.Read moreRead less
Smart communications network management: Delivering bundled interdependent services across internetworked heterogeneous domains. Sophisticated communications network management (data, voice, video) is crucial to the global economy. The field is worth several billion dollars per annum. This project will generate expertise that addresses and solves an important problem in communications management, will enable Australia to use communications networks more effectively, and will advance communicatio ....Smart communications network management: Delivering bundled interdependent services across internetworked heterogeneous domains. Sophisticated communications network management (data, voice, video) is crucial to the global economy. The field is worth several billion dollars per annum. This project will generate expertise that addresses and solves an important problem in communications management, will enable Australia to use communications networks more effectively, and will advance communications technology. 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
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
Web Services Reputation Management. This project directly supports the National Research Priority 4: Safeguarding Australia. More specifically, it aims at creating mechanisms that will make it more difficult to use the Internet as a platform for launching attacks against the business processes of Australian organisations that provide and consume Web services. At the same time this will stimulate the establishment of high quality WS markets. As direct social benefit of this research, Australian o ....Web Services Reputation Management. This project directly supports the National Research Priority 4: Safeguarding Australia. More specifically, it aims at creating mechanisms that will make it more difficult to use the Internet as a platform for launching attacks against the business processes of Australian organisations that provide and consume Web services. At the same time this will stimulate the establishment of high quality WS markets. As direct social benefit of this research, Australian organisations will be able to integrate the best quality Web services as part of their business processes, and thereby avoid being negatively impacted by low quality and deceptive Web services. Read moreRead less
Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected ....Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected outcomes include the
development of software that allows the solution of hitherto unsolved machine
learning problems, and the ability to solve problems larger than those solvable
by the current generation of machine learning tools.Read moreRead less
Discovering Activity Patterns Driven by High Impacts in Heterogeneous and Imbalanced Data. The identification of high impact activities is important for detecting and preventing their occurrences and reducing resulting risks and losses to our society. This project will deliver cutting-edge techniques for effectively extracting activity patterns driven by high business impacts. It can safeguard Australia and build and transform Australian industries by delivering frontier techniques and smart pre ....Discovering Activity Patterns Driven by High Impacts in Heterogeneous and Imbalanced Data. The identification of high impact activities is important for detecting and preventing their occurrences and reducing resulting risks and losses to our society. This project will deliver cutting-edge techniques for effectively extracting activity patterns driven by high business impacts. It can safeguard Australia and build and transform Australian industries by delivering frontier techniques and smart prevention and intervention capabilities to enhance key industries such as finance compliance, national security and crime reduction. The resulting activity mining system, researchers trained and high quality publications will further enhance Australia's global leading role in tackling critical data mining challenges and applications.Read moreRead less
Developing optimal synthesis strategies in distributed expert systems. The aim of this project is to investigate synthesis strategies in distributed expert systems (DESs). Such strategies are used to synthesize multiple solutions to the same task from different experts (either human experts or expert systerms) in order to obtain the final solution to the task. These strategies could be used in a wide application of domains such as insurance agencies and medical diagnosis systems. The expected ....Developing optimal synthesis strategies in distributed expert systems. The aim of this project is to investigate synthesis strategies in distributed expert systems (DESs). Such strategies are used to synthesize multiple solutions to the same task from different experts (either human experts or expert systerms) in order to obtain the final solution to the task. These strategies could be used in a wide application of domains such as insurance agencies and medical diagnosis systems. The expected outcomes are to develop computational strategies, neural network strategies, and case-based strategies for solving different synthesis cases.Read moreRead less