Advanced Monte Carlo Methods for Spatial Processes. The modeling and analysis of spatial data relies more and more on sophisticated Monte Carlo simulation methods. However, with the growing complexity of today's spatial data, traditional Monte Carlo methods increasingly face difficulties in terms of speed and accuracy. The aim of this project is to develop new theory and applications at the interface of Monte Carlo methods and spatial statistics, building upon exciting theoretical and computatio ....Advanced Monte Carlo Methods for Spatial Processes. The modeling and analysis of spatial data relies more and more on sophisticated Monte Carlo simulation methods. However, with the growing complexity of today's spatial data, traditional Monte Carlo methods increasingly face difficulties in terms of speed and accuracy. The aim of this project is to develop new theory and applications at the interface of Monte Carlo methods and spatial statistics, building upon exciting theoretical and computational advances in both areas in recent years. The research will stimulate the design of microscopic and macroscopic complex spatial structures with superior properties, such as composite materials, solar cells, telecommunication networks, mining operations, and road systems.Read moreRead less
Cross-Entropy Methods in Complex Biological Systems. The Cross-Entropy method provides a powerful new way to find superior solutions to complicated optimisation problems in biology, ranging from better design and implementation of medical treatments to an increased understanding of complex ecosystems.
Biotransformation and biodegradation of organic nitrogen compounds from wastewater in bio-electrochemical systems. The rapid emergence of water recycling in Australia requires more vigilant control of pollutants that are discharged to sewers. This project will develop a novel, cost-effective process to remove organic nitrogen compounds (and likely other organics) present in many industrial wastewaters. It could provide an excellent solution for the pre-treatment of such industrial wastewaters at ....Biotransformation and biodegradation of organic nitrogen compounds from wastewater in bio-electrochemical systems. The rapid emergence of water recycling in Australia requires more vigilant control of pollutants that are discharged to sewers. This project will develop a novel, cost-effective process to remove organic nitrogen compounds (and likely other organics) present in many industrial wastewaters. It could provide an excellent solution for the pre-treatment of such industrial wastewaters at the source without any chemical addition, hence reducing the challenge and risks facing the water recycling plants. This innovative technology will further expand the growing research capacity and know-how in water recycling in Australia.Read moreRead less
Enhanced Multilingual Speaker Recognition through the Incorporation of High-Level Features, Late Fusion and Discriminative Classification Methods. The development of robust multilingual speaker recognition systems will benefit the community through the elimination of fraud incurred by financial institutions and customers by enabling several person authentication applications such as: voice based signatures and document issuance; credit card verification by voice and secure over-the-phone financi ....Enhanced Multilingual Speaker Recognition through the Incorporation of High-Level Features, Late Fusion and Discriminative Classification Methods. The development of robust multilingual speaker recognition systems will benefit the community through the elimination of fraud incurred by financial institutions and customers by enabling several person authentication applications such as: voice based signatures and document issuance; credit card verification by voice and secure over-the-phone financial transactions. The technology will also assist in the protection of the community and safeguard Australia by enabling the implementation of the following: suspect identification using voice print; national security measures for combating terrorism by using voice to locate and track terrorists; preemptive criminal activity counter-measures; surveillance and secure building access by voice.Read moreRead less
Robust speaker recognition with reduced utterance duration and intersession variability. The development of robust and accurate speaker recognition systems will enable secure person authentication in over-the-phone financial transactions and benefit the community through the elimination of identity fraud incurred by customers and financial institutions. The technology will also assist in safeguarding Australia by enabling the implementation of suspect identification using voice and security meas ....Robust speaker recognition with reduced utterance duration and intersession variability. The development of robust and accurate speaker recognition systems will enable secure person authentication in over-the-phone financial transactions and benefit the community through the elimination of identity fraud incurred by customers and financial institutions. The technology will also assist in safeguarding Australia by enabling the implementation of suspect identification using voice and security measures for combating terrorism by using voice to locate and track terrorists. Our research at QUT Speech Research Lab is at the forefront of development in this field and will provide Australia with a technological advantage in the rapidly evolving global market for speaker recognition technology for person authentication applications.Read moreRead less
Techniques to use stereo vision for improving person identification systems based on face recognition. The broad aim of this project is to use three-dimensional information available by processing images from stereo cameras in order to bridge the gap between constrained face recognition systems and viable systems that work well under varying illumination, changes in pose and variations in spectacles, facial hair and attire. Such a system will be useful in passenger verification at airports and a ....Techniques to use stereo vision for improving person identification systems based on face recognition. The broad aim of this project is to use three-dimensional information available by processing images from stereo cameras in order to bridge the gap between constrained face recognition systems and viable systems that work well under varying illumination, changes in pose and variations in spectacles, facial hair and attire. Such a system will be useful in passenger verification at airports and as a component of personal identification systems to counter terrorism. The key to successful face location and recognition is an effective combination of all data - range, luminance and colour - and techniques for this will be the discovered outcomes.Read moreRead less
Optimisation of piezoelectric metamaterials: Towards robotic stress sensors. This project aims to design new piezoelectric material microstructures that can enhance the measurement of complex local stress states within robotic limbs. The project expects to generate new knowledge of the achievable properties of multi-poled piezoelectric materials and develop computational tools for the analysis and structural optimisation of such materials. The designed microstructures may revolutionise piezoelec ....Optimisation of piezoelectric metamaterials: Towards robotic stress sensors. This project aims to design new piezoelectric material microstructures that can enhance the measurement of complex local stress states within robotic limbs. The project expects to generate new knowledge of the achievable properties of multi-poled piezoelectric materials and develop computational tools for the analysis and structural optimisation of such materials. The designed microstructures may revolutionise piezoelectric sensor technology. Expected outcomes include manufactured proof-of-concept sensors that enable measurement of local stress fields. This should provide significant benefits, such as improved future robot capability and reliability, and research training for next-generation Australian computational mathematicians. Read moreRead less
Automatic Ontology Learning and Data Reasoning in Web Mining. This research has an impact on both research and practical applications. In research, it provides opportunities for research students to carry out research using both data mining and data reasoning to solving Web based application problems. In practical, it can help IT industry to design the new generation of Web mining systems in order to provide invaluable service to users. This research also develops new techniques for data automa ....Automatic Ontology Learning and Data Reasoning in Web Mining. This research has an impact on both research and practical applications. In research, it provides opportunities for research students to carry out research using both data mining and data reasoning to solving Web based application problems. In practical, it can help IT industry to design the new generation of Web mining systems in order to provide invaluable service to users. This research also develops new techniques for data automatic processing within areas of smart information use in Australia. In particular it further develops data mining techniques by introducing data reasoning models for using discovered knowledge. It must be useful to improve the efficiency of the existing data mining systems. Read moreRead less
Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inf ....Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inferential quantities in an incremental manner. The proposed stochastic algorithms encompass and extend upon a wide variety of current algorithmic frameworks for fitting statistical and machine learning models, and can be used to produce feasible and practical algorithms for complex models, both current and future.
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Efficient multi-context systems for heterogeneous information reasoning and sharing. This project aims to investigate formal models and efficient methods for processing information from heterogeneous sources such as the World Wide Web. When the project is successfully completed, new theories, technologies and systems for reasoning about heterogeneous knowledge bases will be developed.