Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop ne ....Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop new privacy-preserving algorithms on EHD database federations, which can provide efficient data access yet block inside attacks. It will significantly improve the data available for medical research, while reducing the cost of EHD system management and providing visualised decision supports to medical staff and the government health resource planners.Read moreRead less
Effective Recommendations based on Multi-Source Data. Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to ....Effective Recommendations based on Multi-Source Data. Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to represent the extracted semantic relationships and novel linkage-analysis based algorithms will be developed for ranking objects. The results from this project will underpin many critical applications such as healthcare.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101610
Funder
Australian Research Council
Funding Amount
$403,398.00
Summary
Towards Explainable Multi-source Multivariate Time-series Analysis. The aim of this project is to build deep learning models with transparent reasoning behind the results that can be easily interpreted by humans. The research rests on translating pertinent knowledge from multiple sources of complex data containing event sequences into graph form and embedding those knowledge graphs into a sophisticated deep learning model. Such an accomplishment represents the next great advance in machine intel ....Towards Explainable Multi-source Multivariate Time-series Analysis. The aim of this project is to build deep learning models with transparent reasoning behind the results that can be easily interpreted by humans. The research rests on translating pertinent knowledge from multiple sources of complex data containing event sequences into graph form and embedding those knowledge graphs into a sophisticated deep learning model. Such an accomplishment represents the next great advance in machine intelligence and will lay the theoretical foundations for building intelligent analysis tools that truly work in tandem with people. The potential benefits to science, society, and the Australian economy, particularly in finance, sensor technologies, and emergency health services would be appreciable.Read moreRead less
Automatic cartilage segmentation in magnetic resonance imaging. Osteoarthritis (OA) is the most common form of arthritis, affecting nearly 1.4 million Australians. This research aims at engineering new tools for use in Magnetic Resonance Imaging systems to enable automated analyses of the cartilage and bones in joint images. The goals of the work are to assist with improved diagnosis and treatment planning for both chronic disease, such as OA, and acute injuries, such as cartilage and ligament ....Automatic cartilage segmentation in magnetic resonance imaging. Osteoarthritis (OA) is the most common form of arthritis, affecting nearly 1.4 million Australians. This research aims at engineering new tools for use in Magnetic Resonance Imaging systems to enable automated analyses of the cartilage and bones in joint images. The goals of the work are to assist with improved diagnosis and treatment planning for both chronic disease, such as OA, and acute injuries, such as cartilage and ligament tears in sporting injuries and other traumas.
The software developed will be provided on the project’s partner (Siemens) platform and will therefore be available worldwide and have a consequently large impact on the field.
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Techniques to use stereo vision for improving person identification systems based on face recognition. The broad aim of this project is to use three-dimensional information available by processing images from stereo cameras in order to bridge the gap between constrained face recognition systems and viable systems that work well under varying illumination, changes in pose and variations in spectacles, facial hair and attire. Such a system will be useful in passenger verification at airports and a ....Techniques to use stereo vision for improving person identification systems based on face recognition. The broad aim of this project is to use three-dimensional information available by processing images from stereo cameras in order to bridge the gap between constrained face recognition systems and viable systems that work well under varying illumination, changes in pose and variations in spectacles, facial hair and attire. Such a system will be useful in passenger verification at airports and as a component of personal identification systems to counter terrorism. The key to successful face location and recognition is an effective combination of all data - range, luminance and colour - and techniques for this will be the discovered outcomes.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130101311
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Predicting health status of geriatric patients from user trusted multimedia observations. The information technology developed in this project will provide health care specialists with a better window into the lives of elderly patients. Their behaviour can then be accurately interpreted, potentially leading to earlier recognition of problems and better treatment.
Discovery Early Career Researcher Award - Grant ID: DE190101118
Funder
Australian Research Council
Funding Amount
$339,000.00
Summary
High performance density-based clustering in parallel environments. This project aims to conduct a comprehensive study on density-based clustering to improve data management in parallel computing environments. Clustering, a fundamental task in data management, is to group a set of objects such that objects in the same group (called a cluster) are more similar to each other than those in other groups in order to simplify retrieval of similar information. Clustering is widely used in many fields i ....High performance density-based clustering in parallel environments. This project aims to conduct a comprehensive study on density-based clustering to improve data management in parallel computing environments. Clustering, a fundamental task in data management, is to group a set of objects such that objects in the same group (called a cluster) are more similar to each other than those in other groups in order to simplify retrieval of similar information. Clustering is widely used in many fields including machine learning, pattern recognition, information retrieval, bioinformatics and image analysis. It is expected that the developed clustering techniques will provide significant performance improvements in industry sectors where decisions are made based on clustering data analytics, such as the sectors of finance, renewable energy and artificial intelligence.Read moreRead less
Exploiting Views in Extensible Markup Language (XML) Data Processing. This project addresses an important technical issue in smart information use, which is among Australian National Research Priorities. The techniques developed in this project will enable Australian organizations to build smarter and more efficient information systems, hence making them more competitive in the global market. The problems in this project are technically challenging, solving them in Australia will enhance Austr ....Exploiting Views in Extensible Markup Language (XML) Data Processing. This project addresses an important technical issue in smart information use, which is among Australian National Research Priorities. The techniques developed in this project will enable Australian organizations to build smarter and more efficient information systems, hence making them more competitive in the global market. The problems in this project are technically challenging, solving them in Australia will enhance Australia's international research reputation. The project will also boost Australia's research capability by training PhD and honours students.
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Monitoring online topic evolvements with near-duplicate videos. This project will make a major impact on social media mining, and open up a new research direction for topic discovery. The project's advances will bring economic/social benefits to Australia, where collaborative access of large amount of Web/media information is vital, for example, data sharing and management, broadcasting, advertising, opinion gathering, etc.
Design and Development of a Web-based Intelligent Multimedia Mining System. Increasing amounts of digital multimedia data in the form of video is being captured and stored. However, even the most advanced storage and retrieval techniques lack the features required to be used singly, or in combination, to fulfil a wide range of user needs and rapid access to multimedia resources, even in a very large video database. The core challenges are indeed to develop efficient, smart and intelligent web-ba ....Design and Development of a Web-based Intelligent Multimedia Mining System. Increasing amounts of digital multimedia data in the form of video is being captured and stored. However, even the most advanced storage and retrieval techniques lack the features required to be used singly, or in combination, to fulfil a wide range of user needs and rapid access to multimedia resources, even in a very large video database. The core challenges are indeed to develop efficient, smart and intelligent web-based multimedia mining in Australia and elsewhere. In this project, we will explore techniques and develop algorithms for content-based multimedia retrieval and mining in multimedia databases.Read moreRead less