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Field of Research : Applied Statistics
Scheme : Discovery Projects
Australian State/Territory : SA
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  • Funded Activity

    Discovery Projects - Grant ID: DP0877707

    Funder
    Australian Research Council
    Funding Amount
    $645,000.00
    Summary
    WaterLog - A mathematical model to implement recommendations of The Wentworth Group. In 2003, The Wentworth Group of Concerned Scientists released their 'Blueprint for a national water plan' with the primary objective to 'protect river health and the rights of all Australians to clean usable water'. Currently, there are significant water restrictions in all the Australian mainland capital cities. In January 2007, the Prime Minister of Australia, announced a bold plan to rescue the Murray-Darling .... WaterLog - A mathematical model to implement recommendations of The Wentworth Group. In 2003, The Wentworth Group of Concerned Scientists released their 'Blueprint for a national water plan' with the primary objective to 'protect river health and the rights of all Australians to clean usable water'. Currently, there are significant water restrictions in all the Australian mainland capital cities. In January 2007, the Prime Minister of Australia, announced a bold plan to rescue the Murray-Darling Basin. The plan incorporates political management changes, and an investment of $10Bn. Now is the time to develop improved techniques for management of water storage systems. This project will develop the fundamental mathematical principles required for this improved management.
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    Funded Activity

    Discovery Projects - Grant ID: DP0663567

    Funder
    Australian Research Council
    Funding Amount
    $339,000.00
    Summary
    Complexity Constrained Iterative Information Processing. The contribution of Information and Communications Technologies to the National Economy has been widely recognized. ICT enables wealth creation, employment and exports, and underpins many innovation processes. Immediate project benefits will be: Contribution to the knowledge base and fundamental capabilities in high-speed wireless communications networks; Education of future Australian academic and industrial innovators; Raising the inter .... Complexity Constrained Iterative Information Processing. The contribution of Information and Communications Technologies to the National Economy has been widely recognized. ICT enables wealth creation, employment and exports, and underpins many innovation processes. Immediate project benefits will be: Contribution to the knowledge base and fundamental capabilities in high-speed wireless communications networks; Education of future Australian academic and industrial innovators; Raising the international profile of Australian research in the area of information technology. Applied development of the outcomes will lead to the generation of valuable intellectual property. Close links to Australian industry ensures that Australian ICT companies stand to gain commercial advantage.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200101281

    Funder
    Australian Research Council
    Funding Amount
    $380,000.00
    Summary
    Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project .... Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project aims to develop novel and effective algorithmic techniques and statistical methods for a class of branching processes with dependences. We will use these results to study significant problems in the conservation of endangered island bird populations in Oceania, and to help inform their conservation management.
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    Funded Activity

    Discovery Projects - Grant ID: DP0344856

    Funder
    Australian Research Council
    Funding Amount
    $180,000.00
    Summary
    Iterative Architechtures for Data Communications. Growing markets for data intensive applications such as real-time video or speech necessitate continual improvements of communications systems. Iterative information processing algorithms have recently received attention for communications equipment design, however theoretical understanding of these methods is still lacking. Within an iterative processing paradigm, the project aim is the optimization of complex communications systems subject to c .... Iterative Architechtures for Data Communications. Growing markets for data intensive applications such as real-time video or speech necessitate continual improvements of communications systems. Iterative information processing algorithms have recently received attention for communications equipment design, however theoretical understanding of these methods is still lacking. Within an iterative processing paradigm, the project aim is the optimization of complex communications systems subject to constraints on computational complexity. Theoretical analysis and design methodologies for such systems will be developed, resulting in basic contributions to statistical science and in cheaper communications infrastructures supporting a wider range of services through better use of limited bandwidth, power and computational complexity.
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    Funded Activity

    Discovery Projects - Grant ID: DP0772218

    Funder
    Australian Research Council
    Funding Amount
    $219,000.00
    Summary
    Markov Field Theory applied to Sensor Networks Analysis and Design. Ad hoc and sensor networks have a wide range of applications in defence, emergency services and agriculture because they do not require telecommunications infrastructure such as base stations or access points, hence are relatively easy to deploy in harsh environments. This project aims at improving the theoretical understanding of sensor and ad hoc networks, which enable improvements in performance in such networks. Australian d .... Markov Field Theory applied to Sensor Networks Analysis and Design. Ad hoc and sensor networks have a wide range of applications in defence, emergency services and agriculture because they do not require telecommunications infrastructure such as base stations or access points, hence are relatively easy to deploy in harsh environments. This project aims at improving the theoretical understanding of sensor and ad hoc networks, which enable improvements in performance in such networks. Australian defence industry and emergency services will benefit from this research by gaining access to improved ad hoc communications networks. The agricultural sector will also benefit from the improved sensor networks in applications such as monitoring soil conditions, stock and crop levels.
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    Funded Activity

    Discovery Projects - Grant ID: DP0880553

    Funder
    Australian Research Council
    Funding Amount
    $235,000.00
    Summary
    Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise deve .... Visual tracking of multiple objects: A stochastic geometrical approach. Reliable real-time visual multiple-object tracking techniques will open up new applications that enhance the quality of life such as driving safety, traffic monitoring, home security, security and surveillance of public facilities. These new applications have huge commercial potentials, and the technology developed from this project will provide the catalyst for vibrant new industries to grow. In addition, the expertise developed from the project will provide a competitive edge for Australian industries in aerospace, oceanography, robotics, remote sensing, and biomedical engineering.
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    Funded Activity

    Discovery Projects - Grant ID: DP0450632

    Funder
    Australian Research Council
    Funding Amount
    $110,000.00
    Summary
    Designing microarray experiments. Microarrays are powerful tools for surveying the expression levels of many thousands of genes simultaneously. They belong to the new genomics technologies which have important applications in the biological, pharmaceutical and agricultural sciences. There are many sources of uncertainty in microarray experimentation and good statistical designs are essential for ensuring that the effects of interest to scientists are accurately and precisely measured. This Pr .... Designing microarray experiments. Microarrays are powerful tools for surveying the expression levels of many thousands of genes simultaneously. They belong to the new genomics technologies which have important applications in the biological, pharmaceutical and agricultural sciences. There are many sources of uncertainty in microarray experimentation and good statistical designs are essential for ensuring that the effects of interest to scientists are accurately and precisely measured. This Project will develop novel designs for microarray experiments and focus on the advancement of topics crucial to Australia's success in technological research.
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    Funded Activity

    Discovery Projects - Grant ID: DP0773794

    Funder
    Australian Research Council
    Funding Amount
    $510,000.00
    Summary
    Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure present .... Hierarchical Bayesian Models for Human Conceptual Learning. This project seeks to understand the nature of human conceptual learning. With the shift to an information-based economy, it becomes important to understand what assumptions a real-world learning system should make. Even given the impressive growth of machine learning and artificial intelligence, the human mind remains the most successful example of such a system. In this light, the scientific study of human conceptual structure presents the opportunity to discover how an intelligent thinking system should operate. In addition, many important problems facing an information economy involve being able to understand how people behave. An understanding of the concepts people use is central to this endeavour.
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    Funded Activity

    Discovery Projects - Grant ID: DP180101192

    Funder
    Australian Research Council
    Funding Amount
    $342,194.00
    Summary
    Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the mat .... Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the matching of the clusters across the entities in the class. The project will use a statistical approach to automatically match the clusters, since the overall mixture model provides a template for the class. It will provide a basis for discriminating between different classes in addition to the identification of atypical data points within a sample and of anomalous samples within a class. Key applications include biological image analysis and the analysis of data in flow cytometry which is one of the fundamental research tools for the life scientist.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210103700

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into so .... Mathematical modelling of information flow in social networks. This proposal aims to develop new mathematical and statistical methods to understand information flow in social networks. By using novel information theoretic techniques, it will create new methods to characterise social information flow in social networks. These tools will allow derivation of fundamental limits of predictability for AI methods applied to digital data. New mathematics of information flow will produce insights into social influence in online social networks. Benefits include: better understanding of how echo chambers may form in social networks, predictive models for how misinformation can spread online such as during an emergency, and a framework for intercomparison of AI methods applied to digital data on individuals.
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