Audit Security Models for Multiparty Internet Transactions. The aim of this project is to conduct the study for a secure, low overhead means of auditing secure transactions between two parties over the Internet, especially where some doubt surrounds the trustfulness of the other party.
A study will be conducted in this project by investigating security models for multiparty secure transactions in order to identify a number of likely applications for the technology, to develop a high level arch ....Audit Security Models for Multiparty Internet Transactions. The aim of this project is to conduct the study for a secure, low overhead means of auditing secure transactions between two parties over the Internet, especially where some doubt surrounds the trustfulness of the other party.
A study will be conducted in this project by investigating security models for multiparty secure transactions in order to identify a number of likely applications for the technology, to develop a high level architecture of the solution.Read moreRead less
QUA:Queensland digital Ultra-Atlas. This project aims to design and develop a digital ultra-atlas of Queensland which integrates the capabilities of GIS(geographical information system) with interactive 4D graphical modelling,knowledge extraction and context-based query and retrieval. This ultra-atlas would allow users to discover knowledge on natural resources,cultural characteristics and historical changes,as well as simulating different effects by providing advanced search capabilities and en ....QUA:Queensland digital Ultra-Atlas. This project aims to design and develop a digital ultra-atlas of Queensland which integrates the capabilities of GIS(geographical information system) with interactive 4D graphical modelling,knowledge extraction and context-based query and retrieval. This ultra-atlas would allow users to discover knowledge on natural resources,cultural characteristics and historical changes,as well as simulating different effects by providing advanced search capabilities and engaging display of spatial and thematically-linked data. Such an ultra-atlas would have enormous impact on facilitating strategic planning and performance in many applications(e.g fire control,environment and urban planning).Read moreRead less
Coarse Grained Parallel Algorithms. Various fields of research face barriers created by problems that are computationally hard and/or require processing of large amounts of data. For example, some computational biochemistry methods on protein or gene sequences can not be scaled up to data sets required for human health research because of performance problems. Parallel computing enables new research by increasing the size of solvable problems. In addition to fundamental parallel computing resear ....Coarse Grained Parallel Algorithms. Various fields of research face barriers created by problems that are computationally hard and/or require processing of large amounts of data. For example, some computational biochemistry methods on protein or gene sequences can not be scaled up to data sets required for human health research because of performance problems. Parallel computing enables new research by increasing the size of solvable problems. In addition to fundamental parallel computing research, this project studies parallel algorithms for structure-based drug design and protein-protein interaction prediction that will enable new biochemistry research, as well as parallel algorithms for data cubes that will help enable the next generation of very large data warehouses.Read moreRead less
Special Research Initiatives - Grant ID: SR0567393
Funder
Australian Research Council
Funding Amount
$100,000.00
Summary
Infrastructure for large-scale data resource sharing between research institutions – an environmental case study. The project creates a federated distributed data infrastructure for research, that encourages data creators to make their data available to other scientists, and encourages users to make use of data available from many sources. The vision is to establish an ICT infrastructure to facilitate a whole-of-environment approach to environmental research. The outcome is a proof-of-concept ....Infrastructure for large-scale data resource sharing between research institutions – an environmental case study. The project creates a federated distributed data infrastructure for research, that encourages data creators to make their data available to other scientists, and encourages users to make use of data available from many sources. The vision is to establish an ICT infrastructure to facilitate a whole-of-environment approach to environmental research. The outcome is a proof-of-concept application based upon a case study of Queensland Environmental Protection Agency’s databases, to gain an in-depth understanding of the complexity, scope and key technological barriers for establishing an ICT infrastructure, to identify where the latest technologies can be used and where the gaps are for these technologies to be used in environmental sciences.Read moreRead less
Efficient Pre-Processing of Hard Problems: New Approaches, Basic Theory and Applications. Computers store even larger amounts of data about all aspects of human and industrial activity. However, they have not become significantly better at solving common problems in optimization and search. Traditional complexity theory indicates many of these problems require algorithms that are very unlikely to exist. The Parameterized Complexity approach allows us to obtain very efficient algorithms for a lar ....Efficient Pre-Processing of Hard Problems: New Approaches, Basic Theory and Applications. Computers store even larger amounts of data about all aspects of human and industrial activity. However, they have not become significantly better at solving common problems in optimization and search. Traditional complexity theory indicates many of these problems require algorithms that are very unlikely to exist. The Parameterized Complexity approach allows us to obtain very efficient algorithms for a large variety of problems, but the machinery required was diverse and complicated. This research will organize the machinery into a new approach that systematically finds good algorithms by applying simplifications around a parameter of the domain of the problem. As a result, efficient algorithms are obtained for many diverse areas.Read moreRead less
Benchmarking Information Technology Impact in Organisations. Anecdotal evidence reveals dissatisfaction with the operational performance of large application software systems. Yet, Australian IT investments are seldom systematically evaluated post-implementation. Where post-implementation evaluation does occur, the process and measures are typically idiosyncratic and lacking credibility. The study will: yield a convenient, extensively-validated method for evaluating the impact of IT investments; ....Benchmarking Information Technology Impact in Organisations. Anecdotal evidence reveals dissatisfaction with the operational performance of large application software systems. Yet, Australian IT investments are seldom systematically evaluated post-implementation. Where post-implementation evaluation does occur, the process and measures are typically idiosyncratic and lacking credibility. The study will: yield a convenient, extensively-validated method for evaluating the impact of IT investments; establish comparable IT-Impact benchmarks across different sectors of interest to organisations and Government; and facilitate the education and research training of graduate research students well grounded in IT Evaluation methods, and well placed to advance industry expertise in this area.Read moreRead less
Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discove ....Unsupervised learning of finite mixture models in data mining applications. The extraction of useful information from massively large databases is known as data mining. Its broad but vague goal is to find "interesting structure" in the data, which typically leads to breaking the data into clusters. To this end, we consider the fast, efficient, and automatic learning of finite mixture models in hugh data sets without any prior knowledge of the structure. This probabilistic approach to the discovery and validation of group structure in data mining applications will considerably enhance knowledge management and decision support in science, industry, and government.
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