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Scheme : Linkage Projects
Field of Research : Human Information Behaviour
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  • Funded Activity

    Linkage Projects - Grant ID: LP150100400

    Funder
    Australian Research Council
    Funding Amount
    $191,394.00
    Summary
    Information Seeking & Research Adoption: Assessing Communication Strategies. This project aims to determine the best ways to communicate wine research and to design tools to support research adoption. Adoption of research relies on effective use of information and technology by employees. Research into employees’ information practices in the workplace has been conducted in health care, education and other areas; however, the wine industry’s use of information and technology for adoption is unexp .... Information Seeking & Research Adoption: Assessing Communication Strategies. This project aims to determine the best ways to communicate wine research and to design tools to support research adoption. Adoption of research relies on effective use of information and technology by employees. Research into employees’ information practices in the workplace has been conducted in health care, education and other areas; however, the wine industry’s use of information and technology for adoption is unexplored. The project plans to assess the strategies used to share research with winemakers and grape growers (e.g. seminars, websites, social media), from information behaviour or web useability perspectives, to ensure industry needs are met appropriately. This research aims to have a direct and immediate impact on the wine industry. In addition to the immediate impact of new research innovations that will be implemented by our partner wine companies, the project will also change industry-wide approaches to extension. The partner organisations use extension strategies to showcase new innovations and our research will assess these organisations’ current practices, providing evidence to shape the design of future activities in Australia.
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    Funded Activity

    Linkage Projects - Grant ID: LP140100995

    Funder
    Australian Research Council
    Funding Amount
    $275,000.00
    Summary
    Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learnin .... Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax and semantics of individual gestures and actions, nor the multi-gesture information fusion required for understanding, which could significantly enhance efficiency, for example, in sorting through named entities in an investigation. All of this is done naturally by most human beings, using biological neural networks.
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