Distributional Consequences of Mass-Market Higher Education in Business. Increased access to tertiary education has not been evaluated for its effects on the full spectrum of individuals served by the tertiary sector. Using longitudinal data on entire student populations at university business faculties, this project will provide the first Australian evidence on the trade-offs amongst the educational success of students with different levels of preparation that occur when those with poorer prep ....Distributional Consequences of Mass-Market Higher Education in Business. Increased access to tertiary education has not been evaluated for its effects on the full spectrum of individuals served by the tertiary sector. Using longitudinal data on entire student populations at university business faculties, this project will provide the first Australian evidence on the trade-offs amongst the educational success of students with different levels of preparation that occur when those with poorer preparation are added to classrooms. Short-term performance and medium-term attrition, a recent educational policy focus, will be evaluated. Theoretically grounded recommendations will result for undergraduate program design to suit a student population with varying levels of university preparation.Read moreRead less
Nonlinear spatial and spatiotemporal econometrics: theory with applications. Modern societies like Australia have major challenges in the forecasting, measuring and managing of risks associated with global economic and environmental/climate changes. These tasks require advanced econometric techniques in modelling and forecasting of complex nonlinear spatiotemporal variability in economic and social systems. This project will develop frontier econometric technologies that enable more accurate eco ....Nonlinear spatial and spatiotemporal econometrics: theory with applications. Modern societies like Australia have major challenges in the forecasting, measuring and managing of risks associated with global economic and environmental/climate changes. These tasks require advanced econometric techniques in modelling and forecasting of complex nonlinear spatiotemporal variability in economic and social systems. This project will develop frontier econometric technologies that enable more accurate economic and climate forecasts. The tools produced will provide Australia's scientists and policy-makers with a greater capacity to manage the risks associated with these challenges. A side-benefit of the research will be high-quality publications that enhance the nation's reputation in this cutting edge research.Read moreRead less
Build competency aware and assuring machine learning systems. Recent development in machine learning (ML) has seen ML models with extremely high prediction accuracy. However, to support human-machine partnership in decision-making in complex environments, beyond accuracy, it is essential for ML systems to be competency aware and reliable, and at the same time be exploratory. This project aims to develop novel techniques to equip a ML system with the ability to identify own competency, to justify ....Build competency aware and assuring machine learning systems. Recent development in machine learning (ML) has seen ML models with extremely high prediction accuracy. However, to support human-machine partnership in decision-making in complex environments, beyond accuracy, it is essential for ML systems to be competency aware and reliable, and at the same time be exploratory. This project aims to develop novel techniques to equip a ML system with the ability to identify own competency, to justify its competency and decisions, to explore unknown situations and fully utilise existing expertise to deal with unknowns. The expected outcomes of the project will enable ML systems to become truely intelligent and reliable machine partners for human decision makers in a wide range of applications.Read moreRead less
Towards knowledge discovery from imperfect and evolving data. Information extraction from data is critical, both to analyse and protect consumer data. However, many learning techniques are developed using perfect, static datasets, quite different to messy, ever-changing real-world data. This project aims to develop data analytics techniques that can extract accurate information in complex structures from imperfect/incomplete data that changes over time. Expected outcomes are a prototype tool, te ....Towards knowledge discovery from imperfect and evolving data. Information extraction from data is critical, both to analyse and protect consumer data. However, many learning techniques are developed using perfect, static datasets, quite different to messy, ever-changing real-world data. This project aims to develop data analytics techniques that can extract accurate information in complex structures from imperfect/incomplete data that changes over time. Expected outcomes are a prototype tool, tested on real datasets, that combines new techniques in data modelling, algorithm development, and system design. Likely benefits are enhanced Australia's competence in data science through student training and new, robust data tools relevant to critical sectors such as cybersecurity, healthcare, and defence.Read moreRead less
Challenging econometric issues in nonlinear high-dimensional spatio-temporal prediction: theory and applications. This project will develop cutting-edge methodologies to break through challenging issues in nonlinear spatio-temporal econometric prediction. It will yield a new generation of prediction tools that enpower practitioners in Australia to produce more accurate forecasts, with more informed countermeasures to viarious economic and enviromental risks.
Modelling mean and dispersion using fixed and random effects. The aims of the project are to develop methods for joint mean and dispersion modelling using fixed and random effects, in the generalized linear models context and for Gaussian longitudinal data. The significance is the more efficient, precise and appropriate analysis of data arising from many areas of application. The expected outcomes are therefore better methods of analysis, software to carry the analyses out, and potentially impor ....Modelling mean and dispersion using fixed and random effects. The aims of the project are to develop methods for joint mean and dispersion modelling using fixed and random effects, in the generalized linear models context and for Gaussian longitudinal data. The significance is the more efficient, precise and appropriate analysis of data arising from many areas of application. The expected outcomes are therefore better methods of analysis, software to carry the analyses out, and potentially important results in applications.Read moreRead less
XML Views of Relational Databases: Semantics and Update Problems. XML is the standard for representing, publishing and exchanging data over the Internet and relational database is the dominant technology for data management. Updating XML views over relational data is fundamental to bring these two technologies together to serve Internet-based applications. Australia has been a leading country in both developing and applying internet technologies. The theoretic outcomes of this project will contr ....XML Views of Relational Databases: Semantics and Update Problems. XML is the standard for representing, publishing and exchanging data over the Internet and relational database is the dominant technology for data management. Updating XML views over relational data is fundamental to bring these two technologies together to serve Internet-based applications. Australia has been a leading country in both developing and applying internet technologies. The theoretic outcomes of this project will contribute to the advance in database and web research communities and establish us as an internationally leading group in this research area. The technological outcomes will help organisations in Australia effectively and efficiently conduct e-Business on the Internet. Read moreRead less
Constraints in XML Schema Integration. This project will produce worldwide leading technologies for designing XML data integration system. With the technologies, the well designed integration systems will be able store data with rich semantics and thus provide accurate and understandable information to users. In this way, Australia and communities will be benefited both financially and informatively. The research of this project will also add to the research reputation of Australia in data integ ....Constraints in XML Schema Integration. This project will produce worldwide leading technologies for designing XML data integration system. With the technologies, the well designed integration systems will be able store data with rich semantics and thus provide accurate and understandable information to users. In this way, Australia and communities will be benefited both financially and informatively. The research of this project will also add to the research reputation of Australia in data integration areas. At the same time, the knowledge capacity of Australia on data integration will be enlarged which further improves frontier research activities in the area. Through the research of the project, PhD students will be trained.Read moreRead less
Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the mat ....Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the matching of the clusters across the entities in the class. The project will use a statistical approach to automatically match the clusters, since the overall mixture model provides a template for the class. It will provide a basis for discriminating between different classes in addition to the identification of atypical data points within a sample and of anomalous samples within a class. Key applications include biological image analysis and the analysis of data in flow cytometry which is one of the fundamental research tools for the life scientist.Read moreRead less
New strategies to transmit data: Coping with exponential growth in demand. The aim of this project is to provide new technologies to facilitate the exponential growth in demand for streaming of digital data. Based on novel techniques combining graph theory, information theory, and coding, this project aims to change the way we encode data, offering significant improvements to the efficiency of communication networks and providing a 10-100 fold increase in transmission speed. If successful this p ....New strategies to transmit data: Coping with exponential growth in demand. The aim of this project is to provide new technologies to facilitate the exponential growth in demand for streaming of digital data. Based on novel techniques combining graph theory, information theory, and coding, this project aims to change the way we encode data, offering significant improvements to the efficiency of communication networks and providing a 10-100 fold increase in transmission speed. If successful this project expects to bring digital transmission improvements which could impact on almost every sector of the economy from education to advanced healthcare. Possible applications include cloud storage for big data, high-definition video streaming, and wide-coverage high-speed mobile broadband.Read moreRead less