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
Effective and Efficient Video Search. This project will add a much desired level of sophistication to the current data management and search technologies. Success of this project will not only establish us as an internationally leading research group but also bring significant economic and social benefits to Australia. Many Australia organizations specializing in media communication, entertainment, management and services will be benefited by saving enormous cost, improving service quality, prot ....Effective and Efficient Video Search. This project will add a much desired level of sophistication to the current data management and search technologies. Success of this project will not only establish us as an internationally leading research group but also bring significant economic and social benefits to Australia. Many Australia organizations specializing in media communication, entertainment, management and services will be benefited by saving enormous cost, improving service quality, protecting their intelligence properties, etc. It will also advance Australia's intellectual leadership in copyright compliance, benefit commercialization of research results, form strong international collaborations and networks, and underpin the National Research Priority.
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Real-time and self-adaptive stream data analyser for intensive care management. The clinical benefit of this project will be in improved success rates and reduced mortality and risk in surgery and intensive care units. The Information and communication technology (ICT) benefit of this project is associated with the novel online algorithms and models aligned with the stream data research, and will be enhanced by our stream compression techniques. The stream data analyser developed in this projec ....Real-time and self-adaptive stream data analyser for intensive care management. The clinical benefit of this project will be in improved success rates and reduced mortality and risk in surgery and intensive care units. The Information and communication technology (ICT) benefit of this project is associated with the novel online algorithms and models aligned with the stream data research, and will be enhanced by our stream compression techniques. The stream data analyser developed in this project will be suitable for more than medical surveillance data; it will also improve the processing of other kinds of massive stream data (for example data from remote sensors, communication networks and other dynamic environments). The project involves a scientifically rich collaboration that will enhance the skills of PhD students and staff and drive the field forward.Read moreRead less
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
Managing data with high redundancy and low value density. This project aims to develop a database for data storage, cleaning, compression, hierarchal summarisation, indexing and query processing for machination data.Database management systems are needed to support stream query processing and manage historical data to support complex data analytics, data mining and data-driven decision making. Machination data, often found in sensor networks, GPS and RFID applications, vehicle on-board devices a ....Managing data with high redundancy and low value density. This project aims to develop a database for data storage, cleaning, compression, hierarchal summarisation, indexing and query processing for machination data.Database management systems are needed to support stream query processing and manage historical data to support complex data analytics, data mining and data-driven decision making. Machination data, often found in sensor networks, GPS and RFID applications, vehicle on-board devices and medical monitoring devices are difficult to manage and process because of large volumes and streaming, high redundancy and low value density. This project is expected to stream machination data management to support scalable query processing and data analytics.Read moreRead less