Efficient Synchronisation of Large Repositories. Accuracy and maintenance of vast quantities of data are essential for any modern society. The economy, health institutes and industries, and our defence and legal systems rely on having data being distributed widely and securely, and on queries being answered accurately and quickly. Complete synchronisation of databases is often impossible due to the limitations of internet bandwidth. Better compression techniques have the potential to allow crit ....Efficient Synchronisation of Large Repositories. Accuracy and maintenance of vast quantities of data are essential for any modern society. The economy, health institutes and industries, and our defence and legal systems rely on having data being distributed widely and securely, and on queries being answered accurately and quickly. Complete synchronisation of databases is often impossible due to the limitations of internet bandwidth. Better compression techniques have the potential to allow critical data to be distributed much more efficiently; we anticipate in some applications that the size of a compressed file could be reduced tenfold or more compared to previous best methods, leading to dramatic savings.Read moreRead less
The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop si ....The Time-Varying Eigenvalue Problem with Application to Signal Processing and Control. Linear models are ubiquitous in representing physical processes. Decomposing a linear model into its fundamental components is known as the eigenvalue problem. In applications as wide ranging as astronomy, aircraft control systems, Internet search engines and communication systems, it is necessary to perform this decomposition of a pertinent time varying linear model on the fly. This project aims to develop significantly faster and more accurate algorithms for this time varying eigenvalue problem than currently exist. Very modern techniques will be employed to achieve this aim, and the potential benefits to Australian hi-tech industries are great.
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Fast, practical and effective algorithms for clustering with advice. To maintain a safe and healthy society, government and industry need high quality immunization and national security databases. Since we cannot afford to have duplicate, incomplete and conflicting records that refer to the same person, we unify them by identifying clusters of related records.
In the emerging field of functional genomics, diagnosis of certain diseases is enhanced by determining which genes act together. Diffe ....Fast, practical and effective algorithms for clustering with advice. To maintain a safe and healthy society, government and industry need high quality immunization and national security databases. Since we cannot afford to have duplicate, incomplete and conflicting records that refer to the same person, we unify them by identifying clusters of related records.
In the emerging field of functional genomics, diagnosis of certain diseases is enhanced by determining which genes act together. Different experimental runs might result in different clusterings of genes: we need one consensus clustering that summarizes the experimental outcomes.
Cleaning databases and combining clusterings by hand would require vast amounts of time. This project will result in faster and more accurate computational procedures.Read moreRead less
Approximate proximity for applications in data mining and visualization. Data Mining, pattern recognition and visualization of relational information are all important data analysis techniques in which it is essential to determine which data points are in the vicinity of others. The huge size of the data sets involved and the need for real-time interaction preclude the use of conventional methods for the precise computation of the proximity information required. This project will develop efficie ....Approximate proximity for applications in data mining and visualization. Data Mining, pattern recognition and visualization of relational information are all important data analysis techniques in which it is essential to determine which data points are in the vicinity of others. The huge size of the data sets involved and the need for real-time interaction preclude the use of conventional methods for the precise computation of the proximity information required. This project will develop efficient algorithms and data structures for gathering high-quality approximations of the full proximity information, and will use these innovations as the basis for new, practical tools for visualization, and clustering in data mining.Read moreRead less
Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require c ....Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require computational techniques that run extremely efficiently. The project expects to develop and improve approximate data structures that operate in tight resource bounds. Anticipated outcomes are improved event recognition and dramatic speedup in analysis of streams in areas such as finance, health, transport, and urban data.Read moreRead less
Secure and Efficient Cryptographic Hashing. This project will enhance information security, which is absolutely crucial for rapidly growing e-commerce, e-government services and for national security (Priority 4 -Safeguarding Australia - Protection against Terrorism and Crime). The project will strengthen international collaboration by reciprocal exchange of researchers and postgraduate students leading to more attractive and productive research environment. At the same time, the project will he ....Secure and Efficient Cryptographic Hashing. This project will enhance information security, which is absolutely crucial for rapidly growing e-commerce, e-government services and for national security (Priority 4 -Safeguarding Australia - Protection against Terrorism and Crime). The project will strengthen international collaboration by reciprocal exchange of researchers and postgraduate students leading to more attractive and productive research environment. At the same time, the project will help to maintain high research profile of Australian researchers, to increase the capacity for consultancy and contract work, and provide a cutting-edge information technology for the Australian telecommunications industry, business and government (Priority 3 - Frontier Technologies). Read moreRead less
Algorithmic engineering and complexity analysis of protocols for consensus. Opinions, rankings, observations, votes, gene sequences, sensor-networks in security systems or climate models. Massive datasets and the ability to share information at unprecedented speeds, makes finding the most central representative, the Consensus Problem, extremely complex. This research delivers new insights and new, efficient algorithms.
Next-generation techniques for analysing massive data sets. To process enormous amounts of data, leading computing companies are turning to modern computing frameworks, for which little theory of efficient computational techniques has been developed. This project will resolve key theoretical questions and provide fast techniques for poorly understood pattern recognition and bioinformatics problems.
Algorithmics for Interactive 2.5D Graph Drawing. Technological advances have provided a data deluge over the past few years, and consequently have led to many large and complex network models in many domains. This includes terrorrist networks and biological networks, software engineering structures, and webgraphs. Visualisation is an effective tool in helping humans to understand such networks. This project aims to provide a new direction in network visualisation, using 2.5 dimensions. The algor ....Algorithmics for Interactive 2.5D Graph Drawing. Technological advances have provided a data deluge over the past few years, and consequently have led to many large and complex network models in many domains. This includes terrorrist networks and biological networks, software engineering structures, and webgraphs. Visualisation is an effective tool in helping humans to understand such networks. This project aims to provide a new direction in network visualisation, using 2.5 dimensions. The algorithms developed in the project will help security analysts to detect abnormal behavious such as money laundering, help biologists understand protein-protein interaction networks, and help engineers to understand large software systems.Read moreRead less
Scalable Visual Analytics for Uncertain Dynamic Networks. Technological advances have provided a data deluge over the past few years, and have led to many large uncertain and dynamic network models. This includes terrorist networks, marketing networks, facebook networks, various biological networks, and software engineering structures. Human understanding of such networks is difficult. This project aims to provide new methods for visual analysis of large uncertain dynamic networks such as these. ....Scalable Visual Analytics for Uncertain Dynamic Networks. Technological advances have provided a data deluge over the past few years, and have led to many large uncertain and dynamic network models. This includes terrorist networks, marketing networks, facebook networks, various biological networks, and software engineering structures. Human understanding of such networks is difficult. This project aims to provide new methods for visual analysis of large uncertain dynamic networks such as these. The algorithms developed in the project will help security analysts to monitor illegal behaviour such as money laundering and terrorist activities, help biologists understand key biological systems, and help engineers to understand large software systems.Read moreRead less