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Research Topic : missing data
Field of Research : Database Management
Australian State/Territory : VIC
Australian State/Territory : NSW
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  • Funded Activity

    Linkage Projects - Grant ID: LP140100816

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling rese .... Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling research and practical solutions for this important cloud and big data research area; benefiting key big data application areas on the cloud, such as hospitals, insurance companies and government information services; and helping to maintain Australia at the forefront of cloud and big data research with innovative industry applications.
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    Active Funded Activity

    A Secure Smart Sensing And Industry Analytics Facility For Industry 4.

    Funder
    Australian Research Council
    Funding Amount
    $538,350.00
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    Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE180100158

    Funder
    Australian Research Council
    Funding Amount
    $348,026.00
    Summary
    A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and .... A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and evaluation of IoT technologies and services. The project will also serve as a vehicle for the education and training of Australia’s next generation of scholars and engineers, and contribute to Australia’s scientific visibility.
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    Funded Activity

    Discovery Projects - Grant ID: DP170100136

    Funder
    Australian Research Council
    Funding Amount
    $400,500.00
    Summary
    BigPrivacy: Scaling privacy preservation for big data applications on cloud. This project aims to research scalable privacy preservation for big data applications on cloud. Privacy preservation is a major concern for big data applications on cloud, such as health data analysis where user privacy must be preserved. Scalable solutions can preserve privacy so that data analysis such as health diagnosis can be performed quickly. The expected deliverable is a unified scalable privacy preservation fra .... BigPrivacy: Scaling privacy preservation for big data applications on cloud. This project aims to research scalable privacy preservation for big data applications on cloud. Privacy preservation is a major concern for big data applications on cloud, such as health data analysis where user privacy must be preserved. Scalable solutions can preserve privacy so that data analysis such as health diagnosis can be performed quickly. The expected deliverable is a unified scalable privacy preservation framework with associated algorithms and its prototype, which cloud systems can deploy for big data applications.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180100758

    Funder
    Australian Research Council
    Funding Amount
    $540,000.00
    Summary
    Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over ti .... Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over time and captured by different sensors and identify correlations between historic security incidents and current data attacks. This project will significantly help to secure data on cloud for organisations in Australia and benefit fast-growing security sensitive data hosting and applications on cloud.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180100114

    Funder
    Australian Research Council
    Funding Amount
    $782,874.00
    Summary
    Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended .... Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE130101002

    Funder
    Australian Research Council
    Funding Amount
    $375,000.00
    Summary
    Efficiently querying uncertain spatial space. Location-based services are becoming increasingly popular due to exponentially increased usage of smartphones and cheap wireless network. This project aims to provide efficient solutions for various location-based queries applicable to different travelling domains such as road networks, Euclidean space with obstacles and indoor space.
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    Funded Activity

    Discovery Projects - Grant ID: DP180103411

    Funder
    Australian Research Council
    Funding Amount
    $357,675.00
    Summary
    Next-generation search on social networks. This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in utilizing the geographical locations of queries and social network data to provide more relevant results, acknowledging and handling inherent uncertainties in the data, and exploiting knowledge graphs to produce intelligent search results. Expected outcomes of this project i .... Next-generation search on social networks. This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in utilizing the geographical locations of queries and social network data to provide more relevant results, acknowledging and handling inherent uncertainties in the data, and exploiting knowledge graphs to produce intelligent search results. Expected outcomes of this project include a next-generation social network search system. The success of this project will support and enhance a wide range of applications such as law enforcement, health, national security, marketing, and advertisement.
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    Funded Activity

    Discovery Projects - Grant ID: DP110102937

    Funder
    Australian Research Council
    Funding Amount
    $210,000.00
    Summary
    Efficient structure search over large graphs. The project aims to develop advanced search technology to support large-scale graph applications. The success of the project not only brings a breakthrough in technology development but also provides training for high quality personnel in this important and growing area, and brings considerable economic and social benefits to Australia.
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    Showing 1-9 of 9 Funded Activites

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