Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predi ....Low-cost Sensing Methods and Hybrid Learning Models. This project aims to revolutionise the theory and practice of sensing and monitoring by developing novel Artificial Intelligence and Internet of Things technologies. This project expects to generate new knowledge in the area of Artificial Intelligence of Things by combining sensing, machine learning, and big data analytics. Expected outcomes of this project include novel low-cost sensing methods and new hybrid machine learning models for predictive sensory data analytics. This should provide significant benefits, such as substantially reduced operating and service costs and improved accuracy for real-time monitoring in the fields where cheap-to-implement and easy-to-service monitoring systems over large geographical areas are imperative.Read moreRead less
Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while pres ....Privacy-preserving data processing on the cloud. This project aims to address the current lack of privacy of user data processed by common cloud computing web servers, including email, business data, and confidential files. This project aims to develop new techniques in cryptography. The anticipated outcome is a suite of practical tools enabling common cloud computing processing operations such as search, statistical analysis, and multi-user access control, to be performed efficiently while preserving the data privacy. These tools should provide significant benefits to the privacy of cloud users, as well as financial and reputation benefits to the IT industry, by significantly reducing the likelihood of massive user data privacy breaches in the event of a cyber-hacking attack on the cloud server.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
Taming the uncertainty in trajectory data. This project aims to develop effective and efficient methods to manage large scale uncertain trajectory data. It provides individuals, business, government and social groups the ability to explore significant uncertain trajectories and their patterns, for important usages in location based services, logistic, transportation and tourism.
Indexing Large Video Databases to Support Efficient Query Processing. This project aims to develop breakthrough database technology that leverages the advances in video data capturing, computer vision based object recognition, multimedia tagging, large scale database systems and parallel processing, to provide the capability of managing massive video data with enriched semantic information and enabling database-like flexible and efficient video information search. It is expected to establish a n ....Indexing Large Video Databases to Support Efficient Query Processing. This project aims to develop breakthrough database technology that leverages the advances in video data capturing, computer vision based object recognition, multimedia tagging, large scale database systems and parallel processing, to provide the capability of managing massive video data with enriched semantic information and enabling database-like flexible and efficient video information search. It is expected to establish a new data management and processing foundation for big video data analytics.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.
Market segmentation methodology: attacking the 'Too Hard' basket. Businesses embrace market segmentation to identify and target clients. However, poor segmentation analysis leads to poor segment choice. This project will develop tools to improve segmentation analysis and will test the resulting tools in tourism, foster care and climate change mitigating behaviours, and produce usable, transferable recommendations.
Bio-Acoustic Observatory: Engaging Birdwatchers to Monitor Biodiversity by Collaboratively Collecting and Analysing Big Audio Data. This project will research how to crowd-source the collection and analysis of environmental animal sounds (for example, birds, frogs). This will enable a bio-acoustic observatory which provides a scalable, objective and permanent record of the environment, something hitherto impossible. The project will investigate how to engage the community of birdwatchers to exte ....Bio-Acoustic Observatory: Engaging Birdwatchers to Monitor Biodiversity by Collaboratively Collecting and Analysing Big Audio Data. This project will research how to crowd-source the collection and analysis of environmental animal sounds (for example, birds, frogs). This will enable a bio-acoustic observatory which provides a scalable, objective and permanent record of the environment, something hitherto impossible. The project will investigate how to engage the community of birdwatchers to extend their pastime online with new kinds of interactive tools to enable collaborative analysis of big audio data, and new kinds of birding experiences. Outcomes will be: new approaches to physical/virtual engagement in human-computer interaction; new approaches to analysing big data; a new validated ecological monitoring technique and concepts for sustainable knowledge generation communities.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.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