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Field of Research : Information Systems
Field of Research : Expert Systems
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Information Systems (6)
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  • Researchers (13)
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  • Funded Activity

    Linkage Projects - Grant ID: LP0560861

    Funder
    Australian Research Council
    Funding Amount
    $72,444.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0211874

    Funder
    Australian Research Council
    Funding Amount
    $50,000.00
    Summary
    Formalising and automating the elicitation and reconciliation of requirements from multiple stakeholders. It is well recognised that requirements specifications are often error-prone and that it is much cheaper to detect and fix these errors early in the software development life cycle than later. A major problem with requirements determination is that each and every stakeholder has his/her own representation of the enterprise reality. This project seeks to take these views and use set-theore .... Formalising and automating the elicitation and reconciliation of requirements from multiple stakeholders. It is well recognised that requirements specifications are often error-prone and that it is much cheaper to detect and fix these errors early in the software development life cycle than later. A major problem with requirements determination is that each and every stakeholder has his/her own representation of the enterprise reality. This project seeks to take these views and use set-theoretical techniques from Formal Concept Analysis (FCA) to automatically generate and compare the underlying conceptual models. A process model based on FCA has been proposed which we will extend and empirically evaluate in this project. The result will be a more rigorous and yet pragmatic approach to requirements engineering which offers the greatest economic leverage.
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    Funded Activity

    Linkage Projects - Grant ID: LP0561518

    Funder
    Australian Research Council
    Funding Amount
    $72,444.00
    Summary
    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.
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    Funded Activity

    Linkage Projects - Grant ID: LP0349279

    Funder
    Australian Research Council
    Funding Amount
    $73,099.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP180102050

    Funder
    Australian Research Council
    Funding Amount
    $342,518.00
    Summary
    Continuous intent tracking for virtual assistance using big contextual data. Recently launched Virtual Assistant products such as Amazon Echo and Google Home are commanded by voice and can call apps to do simple tasks like setting timers and playing music. The next-generation virtual assistants will recommend things to be done proactively rather than waiting for commands passively. This project aims to develop algorithms that can predict what a user intends to do and therefore help virtual assis .... Continuous intent tracking for virtual assistance using big contextual data. Recently launched Virtual Assistant products such as Amazon Echo and Google Home are commanded by voice and can call apps to do simple tasks like setting timers and playing music. The next-generation virtual assistants will recommend things to be done proactively rather than waiting for commands passively. This project aims to develop algorithms that can predict what a user intends to do and therefore help virtual assistants make recommendations that suit users’ needs accurately. It will benefit many service industry sectors of Australia by enabling virtual assistants to provide services proactively.
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    Funded Activity

    Linkage Projects - Grant ID: LP0347984

    Funder
    Australian Research Council
    Funding Amount
    $87,100.00
    Summary
    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.
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