Motion of objects in soils. This project aims to conduct a fundamental study of a challenging class of geotechnical problems in which an object moves inside a layer of soil, interacts with soil, and disturbs it, by developing advanced numerical and analytical methods. This project expects to determine the fundamental principles governing soil behaviour upon movement of embedded objects. The expected outcomes are robust solutions and computational procedures that will benefit government and engin ....Motion of objects in soils. This project aims to conduct a fundamental study of a challenging class of geotechnical problems in which an object moves inside a layer of soil, interacts with soil, and disturbs it, by developing advanced numerical and analytical methods. This project expects to determine the fundamental principles governing soil behaviour upon movement of embedded objects. The expected outcomes are robust solutions and computational procedures that will benefit government and engineers by providing safer and more cost-effective strategies for designing, constructing, and maintaining Australia's infrastructure. This should bring significant benefits to industries engaged in harvesting energy resources, such as wind farms, as well as oil and gas.Read moreRead less
Rethinking the Data-driven Discovery of Rare Phenomena. This project will investigate novel technologies for the data-driven discovery of rare phenomena. Scientific disciplines are increasingly able to generate large amounts of data relevant to key discoveries such as novel photovoltaic materials or explanations of brain seizures. However, these discoveries typically correspond to extremely rare phenomena in high dimensional spaces, which current data science methods are unable to detect. The pr ....Rethinking the Data-driven Discovery of Rare Phenomena. This project will investigate novel technologies for the data-driven discovery of rare phenomena. Scientific disciplines are increasingly able to generate large amounts of data relevant to key discoveries such as novel photovoltaic materials or explanations of brain seizures. However, these discoveries typically correspond to extremely rare phenomena in high dimensional spaces, which current data science methods are unable to detect. The project will fill this void and yield novel methods, publications, and open source software for the data-driven discovery or rare phenomena. Thus, it will expand the capabilities of data science, providing better use of the massive data collections accumulating across science, government, and industry.Read moreRead less
Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolut ....Differential Evolution Framework for Intelligent Charging Scheduling. Smart charging scheduling is a vital challenge as dynamic environment with traffic networks and various unexpected issues. This project aims to develop a differential evolution framework for intelligent charging scheduling. The framework consists of a comprehensive charging scheduling model with various road networks and factors. The project outcomes include a distributed evolutionary computation framework, differential evolution algorithms, and cooperative co-evolutionary strategies. The outcome results will be demonstrated by practical evaluations over public datasets and comparisons to related works. The project is beneficial to the nation in both theory of artificial intelligence techniques and applications of real transport systems.Read moreRead less
Scalable Stream Processing in Hybrid Edge-Cloud Infrastructures. This project aims to develop a new computational paradigm to ensure low-latency services for streaming applications across heterogeneous Edge devices while satisfying high-throughput and scalability requirements. This project is of high significance for generating new knowledge in the area of real-time streaming using innovative algorithms that overcome the limitations of remote Cloud and distributed Edge computing. Expected outcom ....Scalable Stream Processing in Hybrid Edge-Cloud Infrastructures. This project aims to develop a new computational paradigm to ensure low-latency services for streaming applications across heterogeneous Edge devices while satisfying high-throughput and scalability requirements. This project is of high significance for generating new knowledge in the area of real-time streaming using innovative algorithms that overcome the limitations of remote Cloud and distributed Edge computing. Expected outcomes include novel programming abstractions, performance models, and control mechanisms to address complex problems for incremental and iterative computations in hybrid Edge-Cloud infrastructures. This should provide significant benefits, one of which is the optimised utilisation of limited computing resources.Read moreRead less
Adaptive and Ubiquitous Trust Framework for Internet of Things interactions. The aim of the project is to address the Trust challenges in Internet of Things (IoT) environments, thus enabling the wide deployment of potentially billions of IoT devices. This project will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include the development of a ubiquitous and adaptive mu ....Adaptive and Ubiquitous Trust Framework for Internet of Things interactions. The aim of the project is to address the Trust challenges in Internet of Things (IoT) environments, thus enabling the wide deployment of potentially billions of IoT devices. This project will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include the development of a ubiquitous and adaptive multi-component trust framework reflecting trust perspectives. The developed solutions will allow the establishment of trusted interactions among crowdsourced IoT devices and wider deployment of convenient and just-in-time services, thus enabling the development of novel applications, such as the crowdsourcing of green energy.Read moreRead less
Security and Privacy of Individual Data Used to Extract Public Information. The project aims to contribute to the development of techniques to allow the harvesting of useful information without compromising personal privacy. Intelligent analysis of personal data can reveal valuable knowledge about a population but at a risk of invading an individual's privacy. This project aims to provide at least partial solutions to some of the problems associated with the protection of private data. In partic ....Security and Privacy of Individual Data Used to Extract Public Information. The project aims to contribute to the development of techniques to allow the harvesting of useful information without compromising personal privacy. Intelligent analysis of personal data can reveal valuable knowledge about a population but at a risk of invading an individual's privacy. This project aims to provide at least partial solutions to some of the problems associated with the protection of private data. In particular, it plans to work on the problem of security of statistical databases and privacy of streaming data. This would be underpinned by a study of anonymisation and homomorphic encryption. The expected outcomes are new theoretical results, new algorithms and protocols applicable to at least some of the current significant problems in information security.Read moreRead less
Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, i ....Decomposition and Duality: New Approaches to Integer and Stochastic Integer Programming. Because of their rich modelling capabilities, integer programs are widely used in industry for decision making and planning. However their solution algorithms do not have the maturity of their cousins in convex optimisation, where the theory of strong duality is ubiquitous. Efficient methods for convex optimisation under uncertainty do not apply to the integer case, which is highly non-convex. Furthermore, integer models usually assume the data is known with certainty, which is often not the case in the real world. This project will develop new theory and algorithms to enhance the analysis of integer models, including those that incorporating uncertainty, while also enabling the use of parallel computing paradigms. Read moreRead less
Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, ....Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, social group, and urban level, and at multiple locations and time scales. This should provide users with timely notifications and recommendations to resume their activities and routines. The expected benefits will be far-ranging and adaptable to many domains, from personal smart assistants to trip planning and emergency services.Read moreRead less
Adaptive context caching for fast concurrent access in Internet of Things. Context-awareness in Internet of Things (IoT) applications has profound impact on smartness, relevance, adaptability, dependability, performance and flexibility of such applications. This project will address the significant knowledge gap by investigating, proposing and validating a novel adaptive context caching scheme for fast near real-time access in multiple concurrent context queries coming from multiple and diverse ....Adaptive context caching for fast concurrent access in Internet of Things. Context-awareness in Internet of Things (IoT) applications has profound impact on smartness, relevance, adaptability, dependability, performance and flexibility of such applications. This project will address the significant knowledge gap by investigating, proposing and validating a novel adaptive context caching scheme for fast near real-time access in multiple concurrent context queries coming from multiple and diverse IoT applications. The outcome will be a critical component of the IoT context management platform called Context-as-a-Service which is currently under development. The expected benefits will be far ranging and applicable to many domains including intelligent transportation, industrial internet and smart cities..Read moreRead less
More information for better utility; less information for better privacy. More information for better utility; less information for better privacy. The contradiction is everywhere in contemporary IT: doctors need accurate information for diagnosis, but insurance companies' access should be limited; on-line retailers use your postcode to present interesting products, but they also deduce from it how much you will pay. One way to manage this contradiction is to tolerate "small" information flows p ....More information for better utility; less information for better privacy. More information for better utility; less information for better privacy. The contradiction is everywhere in contemporary IT: doctors need accurate information for diagnosis, but insurance companies' access should be limited; on-line retailers use your postcode to present interesting products, but they also deduce from it how much you will pay. One way to manage this contradiction is to tolerate "small" information flows providing the risks involved can be accurately gauged. This project will build on recent advances in information measuring to develop new techniques for measuring the extent to which computer systems can defend against threats to privacy. Success in this project will lead to completely novel methods for security analysis of on-line applications where privacy is a critical issue.Read moreRead less