Secure Management of Internet of Things Data for Critical Surveillance. This project aims to develop innovative models/algorithms to manage Internet of Things (IoT) data safely and reliably. This project expects to generate new knowledge in the area of classified information governance using innovative data collection, transmission and analysis techniques that overcome the security concerns in large-scale collaborative sensing. Expected outcomes include novel abstract interfaces for IoT, adaptiv ....Secure Management of Internet of Things Data for Critical Surveillance. This project aims to develop innovative models/algorithms to manage Internet of Things (IoT) data safely and reliably. This project expects to generate new knowledge in the area of classified information governance using innovative data collection, transmission and analysis techniques that overcome the security concerns in large-scale collaborative sensing. Expected outcomes include novel abstract interfaces for IoT, adaptive trust and integrity preserving methods, and reliable distributed data processing mechanisms to mitigate vulnerabilities in real-time IoT-enabled critical surveillance. This should provide significant benefits to Australia's economy, one of which is the enhanced consumer-centric adoption of IoT for sensitive operations.Read moreRead less
Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop ....Personalised Privacy-Preserving Network Data Publishing System . Data sharing has become a driving force for many businesses in industrial sectors. This project aims to develop a privacy preserving network data publishing system that can preserve user privacy in a personalised way while maintaining maximal utility of the published data. To make accurate privacy preservation, this project will design novel learning models to derive accurate users’ correlation and their privacy intention, develop efficient privacy preserving algorithms to deal with static and dynamic network data sharing. The success of this project will benefit many industries and government agencies to reduce users’ privacy breaches, avoid illegal consequences of sharing data, and enhance these service providers’ service quality.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Personalised Online Learning Analytics by Exploring Multilayer Graph Data . Learning analytics is becoming a significant factor in reducing the drop-out rate of students in online learning. The aim of this project is to develop a reliable, robust, real-time analysis system that automatically reveals multilayered relationships, evaluates students' learning performance, and generates a personal study plan through discovery. This project includes the design of novel algorithms for multilayer graph ....Personalised Online Learning Analytics by Exploring Multilayer Graph Data . Learning analytics is becoming a significant factor in reducing the drop-out rate of students in online learning. The aim of this project is to develop a reliable, robust, real-time analysis system that automatically reveals multilayered relationships, evaluates students' learning performance, and generates a personal study plan through discovery. This project includes the design of novel algorithms for multilayer graph processing, pattern recognition in learning activities, learning performance assessment, and personalised study plan recommendations. The success of this project will significantly enhance the success of online education both in Australia and worldwide and; hence, will save time, money and resources for end users.Read moreRead less
Robust and scalable change detection in geo-spatial data. A flood of data in the form of text, images and video emanate from a proliferation of sensors. These data are collected but rarely analysed, rendering it meaningless. This project aims to develop new software and techniques to detect changes over time in large scale geographically referenced data (for example photomaps) for use across numerous domains.
Infill Developments: Project HOME (Housing Outcomes Metrics and Evaluation). The project plans to improve housing outcomes by evaluating housing design in the rapidly growing infill multi-residential sector, which often experiences design quality problems. Set across four global cities, the project aims to use a unique combination of design and social science methods to analyse good design and how this is produced and experienced. It is expected that this will deliver greater definition of and e ....Infill Developments: Project HOME (Housing Outcomes Metrics and Evaluation). The project plans to improve housing outcomes by evaluating housing design in the rapidly growing infill multi-residential sector, which often experiences design quality problems. Set across four global cities, the project aims to use a unique combination of design and social science methods to analyse good design and how this is produced and experienced. It is expected that this will deliver greater definition of and evidence for ‘good’ design as experienced through the real lives of Australian households. Outcomes should include robust design evaluation methods and transition strategies for cities, allowing city decision-makers to improve housing design for many people in Australian cities.Read moreRead less
Modelling stock market liquidity in Australia and the Asia Pacific Region. This project will develop new methods of assessing stock market liquidity in Australia and the Asia-Pacific region. These methods will use high frequency transactions-based data provided by the industry partner, SIRCA. The data will be the basis of smart information real time algorithms for measuring market liquidity. They will incorporate generalizations and extensions of recent developments in time series econometrics, ....Modelling stock market liquidity in Australia and the Asia Pacific Region. This project will develop new methods of assessing stock market liquidity in Australia and the Asia-Pacific region. These methods will use high frequency transactions-based data provided by the industry partner, SIRCA. The data will be the basis of smart information real time algorithms for measuring market liquidity. They will incorporate generalizations and extensions of recent developments in time series econometrics, and will be calibrated and evaluated statistically. The novel methods will be crucial to market participants and to regulators, who will be able to apply them to assess market depth and liquidity, and reduce trading costs substantially.Read moreRead less
Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through dee ....Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through deep learning with structural conditions and load-carrying capacities obtained from vibration tests and finite element model analysis for efficient structural damage detection and quantification. The project will lead to effective structural health monitoring and enhance structural safety and reduce maintenance costs. Read moreRead less
An Advanced Numerical Technique for Stability Analysis of Mining Excavations in Jointed/Faulted Rock Masses under High Stresses. The aim of this project is to develop a sophisticated mathematical model and computational technique for the stability analysis of mining excavations in jointed/faulted rock masses. The development involves a novel solution method based on current work in finite element method, boundary element method and large-scale optimisation with partial differential equation cons ....An Advanced Numerical Technique for Stability Analysis of Mining Excavations in Jointed/Faulted Rock Masses under High Stresses. The aim of this project is to develop a sophisticated mathematical model and computational technique for the stability analysis of mining excavations in jointed/faulted rock masses. The development involves a novel solution method based on current work in finite element method, boundary element method and large-scale optimisation with partial differential equation constraints. The work is extremely important to the mining industry in Australia, as the outcomes of the project will provide engineers with an innovative simulation technique to optimise mine design and to predict and control rock failure so as to reduce personnel injuries and death toll in mine sites.Read moreRead less
Computational methods in atomic collision theory. We will develop computational methods for solving interactions between particles on the atomic scale. Computational problems, of particular interest to the industry partner, are the treatment of large-scale ill-conditioned linear systems, and the extension of the Gaussian molecular structure package to collision physics. We have been world-leaders in the field of atomic collision theory for almost a decade, and now, utilising the latest software ....Computational methods in atomic collision theory. We will develop computational methods for solving interactions between particles on the atomic scale. Computational problems, of particular interest to the industry partner, are the treatment of large-scale ill-conditioned linear systems, and the extension of the Gaussian molecular structure package to collision physics. We have been world-leaders in the field of atomic collision theory for almost a decade, and now, utilising the latest software and hardware, will have the capacity to extend the numerical techniques to a vast range of collision systems of interest to science and industry, where visualisation and sheer computer power will play a major role in both
code development and production runs.Read moreRead less