Discovery Early Career Researcher Award - Grant ID: DE160100630
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Relating function of complex networks to structure using information theory. This project aims to investigate networks in order to translate network function to a universal language of information flows. Network science has used common tools to reveal universal connection structures within various biological and man-made networks – our brains, social networks and power grids are all networks of interacting components. Yet there is no common method to study the function of these networks and how ....Relating function of complex networks to structure using information theory. This project aims to investigate networks in order to translate network function to a universal language of information flows. Network science has used common tools to reveal universal connection structures within various biological and man-made networks – our brains, social networks and power grids are all networks of interacting components. Yet there is no common method to study the function of these networks and how such function is coupled with structure. This project aims to relate network structure to function by using measures of information processing as a generally-applicable framework. This will deliver a theory of how structure gives rise to dynamics and how structure can be optimised for desired dynamics.Read moreRead less
Intelligent pattern recognition of water end uses enabling recommendations. This project aims to develop a hybrid machine learning method for autonomously disaggregating high- and low-resolution water flow data received from smart meters into discrete end-use events, and a customised recommender system for efficient resource demand management. Project novelty and significance relates to this coupling and autonomous disaggregation of datasets from advanced sensors, enabling more efficient utility ....Intelligent pattern recognition of water end uses enabling recommendations. This project aims to develop a hybrid machine learning method for autonomously disaggregating high- and low-resolution water flow data received from smart meters into discrete end-use events, and a customised recommender system for efficient resource demand management. Project novelty and significance relates to this coupling and autonomous disaggregation of datasets from advanced sensors, enabling more efficient utility services delivery and lower customer utility bills. Project benefits include enabling utilities to better manage and plan resources in the information age, while empowering customers with real-time water end-use data and behaviour changing consumption recommendations.Read moreRead less
A Phase III Trial Comparing Adjuvant Versus Salvage Radiotherapy For High Risk Patients Post Radical Prostatectomy
Funder
National Health and Medical Research Council
Funding Amount
$819,138.00
Summary
About half of all patients Treated with an operation to remove their prostate cancer have a high chance of the cancer coming back. Giving immediate radiotherapy to all patients will improve cure rates but does not benefit all men and can cause significant side effects. This study explores whether it is safe to wait and only give radiotherapy when there is a rising PSA after surgery indicating active cancer. A total of 470 men from Australasia will enter this study comparing the two approaches.
A Randomised Control Trial Of Non-specific Clinical Management Versus CBT In Chronic Anorexia Nervosa
Funder
National Health and Medical Research Council
Funding Amount
$555,843.00
Summary
Anorexia nervosa (AN) is a serious mental illness that usually starts in adolescence and often runs a chronic course. With an estimated prevalence rate between 0.5% and 3.7% of women, and up to 50% remaining chronically ill, the illness poses a disproportionate burden on health and social services. AN has inpatient costs alone that exceed that for schizophrenia. Chronic AN has the highest mortality rate of any mental illness. Chronic AN patients are known for their ambivalence about engaging in ....Anorexia nervosa (AN) is a serious mental illness that usually starts in adolescence and often runs a chronic course. With an estimated prevalence rate between 0.5% and 3.7% of women, and up to 50% remaining chronically ill, the illness poses a disproportionate burden on health and social services. AN has inpatient costs alone that exceed that for schizophrenia. Chronic AN has the highest mortality rate of any mental illness. Chronic AN patients are known for their ambivalence about engaging in treatment and poor motivation to change their eating disorder behaviours. They often fail to respond to traditional treatments and develop a history of negative treatment experiences and repeated treatment failures. A new approach is needed to reduce both the personal suffering and the burden of the illness on social and medical services. To date, there has been little scientific investigation into the development of specific treatment for those patients with chronic AN. This study will trial a recently manualised therapy - non-specific supportive clinical management - which initial evidence suggests may hold promise for chronic AN because it offers a more indirect, motivationally-matched approach. This treatment will be compared to the establishment therapy Cognitive Behavioural Therapy. Patients will be randomly allocated to one of the two treatment conditions and will receive 40 sessions over 12 months. They will be thoroughly assessed prior to during and after they have completed treatment and followed up for 6 months. This is the worlds first trial of a psychological treatment for chronic AN; it is hoped the study will establish an effective treatment for this debilitating and expensive illness. Further, as the project aims to explore the core, but often over-looked, feature of AN - poor motivation for recovery - it will also be in a position to shed light on the deep psychological processes that maintain this illness.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
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
Visual methods for advanced automation of underwater manipulation. This project will increase the autonomy of underwater robotic systems engaged in intervention and inspection tasks. Such activities are essential for the operation of subsea robotic systems used in offshore industries, scientific exploration and defence. Our approach will improve perception and situational awareness through the principled fusion of multiple navigation and camera sensors. We will use this improved scene understand ....Visual methods for advanced automation of underwater manipulation. This project will increase the autonomy of underwater robotic systems engaged in intervention and inspection tasks. Such activities are essential for the operation of subsea robotic systems used in offshore industries, scientific exploration and defence. Our approach will improve perception and situational awareness through the principled fusion of multiple navigation and camera sensors. We will use this improved scene understanding to effectively plan the motion of vehicles and manipulators through larger and more complex workspaces, enabling semi-supervised and autonomous task execution. Our project will demonstrate these capabilities in real-world deployments relevant to industry and marine science.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