Secure and Resistant Blockchain for Financial and Business Applications. The aim of this project is to develop a practical secure blockchain technology for the booming applications in finance and business. This project expects to address the leading security threats to the current blockchain applications. The expected outcome is an executable secure and resistant blockchain prototype through the integration of the latest developed and customized techniques. The success of the project will dramat ....Secure and Resistant Blockchain for Financial and Business Applications. The aim of this project is to develop a practical secure blockchain technology for the booming applications in finance and business. This project expects to address the leading security threats to the current blockchain applications. The expected outcome is an executable secure and resistant blockchain prototype through the integration of the latest developed and customized techniques. The success of the project will dramatically benefit Australian people and government, especially for the Australian ICT industry for commercializing the research outputs. Read moreRead less
Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. Th ....Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. The success of this project will further enhance the international competitiveness of Australian research in this important field and will benefit any Australian industry and business where software systems are deeply-rooted, such as transportation, smart homes, medical devices, defence and finance.Read moreRead less
Thermo-mechanical interactive atlas of basin evolution. We propose to create a thermo-mechanical interactive atlas of basin evolution as a desktop geodynamic modelling resource for exploration geologists. The atlas will allow the user to iteratively run our 2D/3D basin modelling software ELLIPSIS to alter model parameters until they match observed basin geometries or thermal history. Model iteration will be based on interactive user evaluation of model outputs and genetic algorithms, which pr ....Thermo-mechanical interactive atlas of basin evolution. We propose to create a thermo-mechanical interactive atlas of basin evolution as a desktop geodynamic modelling resource for exploration geologists. The atlas will allow the user to iteratively run our 2D/3D basin modelling software ELLIPSIS to alter model parameters until they match observed basin geometries or thermal history. Model iteration will be based on interactive user evaluation of model outputs and genetic algorithms, which progressively modify the solution set by mimicking the evolutionary behavior of biological systems (selection, cross-over and mutation), until an acceptable result is achieved. The interactive atlas will be applied to Australian and international case studies.Read moreRead less
Feedback Processes in Galaxy Formation. We have an opportunity to combine the best Australian theory with the best local and international telescopes, to probe the murky story of how galaxies form and why they look they way they do today. By looking back to a time when the Universe was only 1 billion years old, and comparing what we see with cutting edge supercomputer simulations plus pure theory, we will gain insight into the birth of entire galaxies. The results will form part of the study o ....Feedback Processes in Galaxy Formation. We have an opportunity to combine the best Australian theory with the best local and international telescopes, to probe the murky story of how galaxies form and why they look they way they do today. By looking back to a time when the Universe was only 1 billion years old, and comparing what we see with cutting edge supercomputer simulations plus pure theory, we will gain insight into the birth of entire galaxies. The results will form part of the study of how the universe works - that is driving astrophysics today, and represents pure research for the sake of advancing knowledge and showing us where we fit into the Universe. In doing so we will also advance Australia's base of theoretical and computational expertise.Read moreRead less
User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating conc ....User-task co-adaptation for effective interactive simulation environments. This project aims to deliver smart interactive simulation environments in which users and simulation tasks work together. This project aims to create novel adaptive algorithms to automatically discover those user and task features that vary together to smartly adapt users and simulation tasks to work together harmoniously, seamlessly and effectively. Interactive simulation environments are the backbone for evaluating concepts, designs, products and advanced training systems in industry and government organisations. By bringing the user naturally inside the simulation as a task's component, users can improve their experience while task performance is simultaneously optimised. Intended outcomes include novel dynamic user-task profiling algorithms and new adaptive algorithms for user-task co-adaptation. Practical outcomes may include robust and highly effective simulation environments.Read moreRead less
Special Research Initiatives - Grant ID: SR0566892
Funder
Australian Research Council
Funding Amount
$220,000.00
Summary
The EarthByte software and database system. Earth processes over geological timescales cannot be understood outside of a plate tectonic context. However, no standard tool exists to explore the causes and effects of lithosphere-mantle interaction in accordance with past plate configurations. Our aim is to develop a Palaeo-Geographic Information System called EarthByte that will connect the open source and architecture-independent GPlates and GMT software, and implement XML-based service interfac ....The EarthByte software and database system. Earth processes over geological timescales cannot be understood outside of a plate tectonic context. However, no standard tool exists to explore the causes and effects of lithosphere-mantle interaction in accordance with past plate configurations. Our aim is to develop a Palaeo-Geographic Information System called EarthByte that will connect the open source and architecture-independent GPlates and GMT software, and implement XML-based service interfaces and databases. EarthByte will create the foundation for an e-geoscience framework for grid-based data access and Earth process modelling by linking geological and geophysical observations to palaeogeographic models for constraining mantle convection and lithospheric deformation.Read moreRead less
Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algori ....Analysing Iterative Machine Learning Algorithms with Information Geometric Methods. Online machine learning problems arise from situations where data is provided a point at a time. There are many classical algorithms for solving such problems based on the principle of stochastic gradient descent. Recent research by the CIs and others have thrown up interesting but diverse geometric connections that offer new insights. The proposed research aims to integrate the understanding of these algorithms with the aim of designing algorithms better able to exploit prior knowledge, and to extend existing algorithms to new problem domains thus offering well principled and well understood algorithms for solving a variety of novel online problems.Read moreRead less
Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical application ....Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical applications such as better wellness tracking and lifestyle-related illness prevention, which will be particularly critical to Australia's aging population. This project will also serve as a vehicle to educate and train Australia’s young scholars and engineers.Read moreRead less
Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human expl ....Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human explicit and implicit interest domains. The expected results of this application will not only maintain Australia's leadership in this frontier research area, but also support many important applications that safeguard Australian people and economy such as cyber security, healthcare, and e-Commerce.Read moreRead less
Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance witho ....Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance without accessing expensive test labels and improvements to system generalisation. This should provide significant benefits for computer vision applications that currently require expensive labelling, and commercial and economic benefits across sectors such as transportation, security and manufacturing.Read moreRead less