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
Probing the function of protein molecular motors on nano-fabricated structures. The function of protein linear molecular motors, which are natural dynamic bio-nano-devices with a ubiquitous importance in multicellular organisms, will be 'probed' with purposefully designed nano-structures fabricated via photo- or Scanning Probe Microscopy Lithography, that is, flat polymeric surfaces with combinatorial combinations of physico-chemistries; and micro/nano-channels and nano-wells with critical dimen ....Probing the function of protein molecular motors on nano-fabricated structures. The function of protein linear molecular motors, which are natural dynamic bio-nano-devices with a ubiquitous importance in multicellular organisms, will be 'probed' with purposefully designed nano-structures fabricated via photo- or Scanning Probe Microscopy Lithography, that is, flat polymeric surfaces with combinatorial combinations of physico-chemistries; and micro/nano-channels and nano-wells with critical dimensions similar to the scale of the probed biomolecules. The project turns 'up-side down' the challenge of invasive nano-probing of biomolecules using it in an engineered manner. The fundamental understanding of linear molecular motors will impact on biomedical science and on the assessment of hybrid natural-artificial dynamic nano-devices.Read moreRead less
Efficient and effective methods for classifying massive time series data. This project aims to transform the theory and practice of time series classification. The current state of the art cannot handle the massive numbers of time series that describe many critical problems facing humanity, such as disease transmission and climate change. This project seeks to develop methods that can analyse dynamic processes at global scale, delivering the most accurate classifiers feasible within a given comp ....Efficient and effective methods for classifying massive time series data. This project aims to transform the theory and practice of time series classification. The current state of the art cannot handle the massive numbers of time series that describe many critical problems facing humanity, such as disease transmission and climate change. This project seeks to develop methods that can analyse dynamic processes at global scale, delivering the most accurate classifiers feasible within a given computational budget. Expected outcomes of this project include efficient, effective and broadly applicable time series classification technologies. This should provide significant benefits to myriad sectors, transforming data science for time series problems and supporting innovation in industry, commerce and government.Read moreRead less
Fast effective clustering technologies for highly dynamic massive networks. Clustering is a fundamental data mining and analysis task. In an interconnected evolving world, friendships and information flows are modelled as large dynamic networks. Structural clustering and correlation clustering are important and well-studied approaches for static networks; for evolving networks, where links appear and disappear over time, we lack efficient techniques. Anticipated outcomes are new practical cluste ....Fast effective clustering technologies for highly dynamic massive networks. Clustering is a fundamental data mining and analysis task. In an interconnected evolving world, friendships and information flows are modelled as large dynamic networks. Structural clustering and correlation clustering are important and well-studied approaches for static networks; for evolving networks, where links appear and disappear over time, we lack efficient techniques. Anticipated outcomes are new practical clustering algorithms for dynamic networks – with performance guarantees of efficiency and clustering quality – and prototype software, guiding us to pick a good clustering. Expected benefits include better understanding of spread in evolving social networks, accelerating the software testing cycle, and improved topic detection.Read moreRead less
Exploring Aspects of Supramolecular Chemistry as a Paradigm for Advanced Functional Materials. This research proposal aims to provide an intellectual grounding in the use of molecular recognition for the assembly of complex arrays for new materials research. The development of molecular systems and supramolecular arrays that are capable of solar energy conversion (e.g. photovoltaics and artificial photosynthesis) or that have potential applications in catalysis will provide advances in the deve ....Exploring Aspects of Supramolecular Chemistry as a Paradigm for Advanced Functional Materials. This research proposal aims to provide an intellectual grounding in the use of molecular recognition for the assembly of complex arrays for new materials research. The development of molecular systems and supramolecular arrays that are capable of solar energy conversion (e.g. photovoltaics and artificial photosynthesis) or that have potential applications in catalysis will provide advances in the development of these industries within Australia. Such developments may also lead to breakthroughs in areas such as optoelectronics and cleaner energy production. Read moreRead less
Knowledge Graph-driven Software Vulnerability Risk Discovery and Assessment. This project aims to alleviate cyberattacks which are increasingly being crafted to attack software vulnerabilities and weaknesses by utilising advanced knowledge graphs and deep learning techniques. This project expects to construct an innovative software vulnerability knowledge graph and develop advanced graph-based algorithms and models. Expected outcomes of this project include the enhanced capacity to defend agains ....Knowledge Graph-driven Software Vulnerability Risk Discovery and Assessment. This project aims to alleviate cyberattacks which are increasingly being crafted to attack software vulnerabilities and weaknesses by utilising advanced knowledge graphs and deep learning techniques. This project expects to construct an innovative software vulnerability knowledge graph and develop advanced graph-based algorithms and models. Expected outcomes of this project include the enhanced capacity to defend against cyberattacks for both organisations and individuals in Australia and beyond, theory development in graph theory, refined graph neural network models and improved graph transfer learning algorithms.Read moreRead less
Fast Reconstruction and Real-time Rendering of Immersive Light Field Video. This project aims to develop new learning-based methods for reconstructing and rendering 3D immersive videos from multi-view 2D videos. The project expects to generate new knowledge in the areas of data mining, multimedia, pattern recognition and deep learning. Expected outcomes of this project include new deep neural networks to represent 3D videos, neural methods for high-fidelity video rendering and efficient 3D video ....Fast Reconstruction and Real-time Rendering of Immersive Light Field Video. This project aims to develop new learning-based methods for reconstructing and rendering 3D immersive videos from multi-view 2D videos. The project expects to generate new knowledge in the areas of data mining, multimedia, pattern recognition and deep learning. Expected outcomes of this project include new deep neural networks to represent 3D videos, neural methods for high-fidelity video rendering and efficient 3D video reconstruction and rendering algorithms. This should provide significant benefits to a diverse range of practical applications, such as autonomous driving, virtual reality, healthcare, advanced manufacturing, and many other 3D applications.Read moreRead less
Identifying and Tracking Influential Events in Large Social Networks. This project aims to invent a novel model and techniques for identifying and tracking influential events in large and dynamic social networks in real time. The proposed model would take into account the structure and content of social networks, and the influence of events. The project also plans to develop efficient strategies for identifying and tracking events in large and dynamic social network environments based on the mod ....Identifying and Tracking Influential Events in Large Social Networks. This project aims to invent a novel model and techniques for identifying and tracking influential events in large and dynamic social networks in real time. The proposed model would take into account the structure and content of social networks, and the influence of events. The project also plans to develop efficient strategies for identifying and tracking events in large and dynamic social network environments based on the model, In particular, the project plans to investigate flexible social network query methods to make users’ event search easy. Finally the project plans to build an evaluation system to demonstrate the efficiency of the algorithms and effectiveness of the model.Read moreRead less
Biclique discovery in Big Data. This project aims to design algorithms to capture Big Data. Biclique is a popular graph model that can capture important cohesive structures in many applications. However, traditional biclique discovery algorithms which only focus on simple, small-scale, static and deterministic data are inadequate in the era of Big Data where data has Variety (various formats), Volume (large quantity), Velocity (dynamic update) and Veracity (uncertainty). This project expects to ....Biclique discovery in Big Data. This project aims to design algorithms to capture Big Data. Biclique is a popular graph model that can capture important cohesive structures in many applications. However, traditional biclique discovery algorithms which only focus on simple, small-scale, static and deterministic data are inadequate in the era of Big Data where data has Variety (various formats), Volume (large quantity), Velocity (dynamic update) and Veracity (uncertainty). This project expects to benefit real applications in both public and private sectors and add value to Australian manufactured products.Read moreRead less
High specificity nanosensors for glycobiology . This project aims to develop high specificity glycosensors for identifying and characterising carbohydrates. These glycosensors are expected to generate detailed information on carbohydrate stereochemical structure and how this controls protein-carbohydrate binding and other interactions fundamental to biochemical processes. This innovative nanotechnology aims to deliver a new capability for understanding cellular recognition and antigen binding me ....High specificity nanosensors for glycobiology . This project aims to develop high specificity glycosensors for identifying and characterising carbohydrates. These glycosensors are expected to generate detailed information on carbohydrate stereochemical structure and how this controls protein-carbohydrate binding and other interactions fundamental to biochemical processes. This innovative nanotechnology aims to deliver a new capability for understanding cellular recognition and antigen binding mechanisms. The expected outcomes are new tools for glycobiology and research into carbohydrate structure-function relationships, strengthening Australia’s global reputation in nanosensors with an incisive analytical technology for biomedical sciences and the many industries utilising carbohydrates.Read moreRead less