Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results ....Design of dynamic visual signals. Models of the design of visual signals depend heavily upon analyses of static ornaments. Nothing is known about dynamic visual signals. We will use an array of new techniques to tackle this problem for the first time. Motion analyses will define the task faced by the visual system. Sensory limitations will be measured to identify constraints on signal evolution. Digital video playback studies will assess recognition and explain aspects of signal design. Results will test the generality of principles that have been developed in studies of female mate choice and extend these ideas to address intra-sexual selection operating through opponent assessment.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
Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learnin ....Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax and semantics of individual gestures and actions, nor the multi-gesture information fusion required for understanding, which could significantly enhance efficiency, for example, in sorting through named entities in an investigation. All of this is done naturally by most human beings, using biological neural networks.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
Development of methods and algorithms to support multidisciplinary optimisation. This project will aim to develop a number of novel and computationally efficient schemes to deal with the key challenges facing multidisciplinary optimisation. These advancements will allow us to solve a number of challenging and intractable problems in science and engineering.
Haemodynamic investigation of flow diverter stents for the treatment of intracranial aneurysms. This project will explore the engineering of a flow diverter, an endovascular device for the treatment of brain aneurysms. The project will determine the optimal design of new types of flow diverters, which in turn could improve the effectiveness of treatments, thus reducing the associated costs of cerebral haemorrhage and stroke.
Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected ....Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected outcomes include the
development of software that allows the solution of hitherto unsolved machine
learning problems, and the ability to solve problems larger than those solvable
by the current generation of machine learning tools.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE170100118
Funder
Australian Research Council
Funding Amount
$1,800,000.00
Summary
UltraTEM: Resolving the structure of matter in space, energy and time. This project aims to establish a transmission electron microscope facility to analyse materials structure at the atomic level. A small number of atoms in critical locations governs the properties of materials from solar cells and catalysts to aerospace alloys, bio-sensors and quantum computers. To understand and engineer matter at this atomic level, tools are needed to characterise these critical atoms. This open access, nati ....UltraTEM: Resolving the structure of matter in space, energy and time. This project aims to establish a transmission electron microscope facility to analyse materials structure at the atomic level. A small number of atoms in critical locations governs the properties of materials from solar cells and catalysts to aerospace alloys, bio-sensors and quantum computers. To understand and engineer matter at this atomic level, tools are needed to characterise these critical atoms. This open access, national facility will be able to characterise matter at the atomic-level. Expected outcomes include better understanding of the natural world and advanced materials to solve problems in energy, technology, health, environment, communications, advanced manufacturing, transport and security.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE200100132
Funder
Australian Research Council
Funding Amount
$1,486,000.00
Summary
A triple beam microscope: new frontiers in materials nanocharacterisation. This project aims to establish a triple beam ion and electron microscope facility for the modification, preparation and characterisation of materials that have hitherto been too sensitive for high resolution analysis with charged particle beams. It is expected that materials will be studied artefact-free and at the nanoscale with twin ion beams and new detectors that allow novel imaging modes and extreme chemical sensitiv ....A triple beam microscope: new frontiers in materials nanocharacterisation. This project aims to establish a triple beam ion and electron microscope facility for the modification, preparation and characterisation of materials that have hitherto been too sensitive for high resolution analysis with charged particle beams. It is expected that materials will be studied artefact-free and at the nanoscale with twin ion beams and new detectors that allow novel imaging modes and extreme chemical sensitivity plus controlled atmosphere transfer to other instruments for correlative measurements. This unique facility should benefit research in many disciplines such as physics, chemistry, geology, pharmacy, materials, civil and chemical engineering by allowing first-ever observations of vital phenomena in diverse materials.Read moreRead less
X-ray imaging and magnetic resonance approach for enhanced oil recovery. This project aims to develop an efficient multi-scale modelling capability to quantify the effect of two-phase fluid flow within porous material by modelling rock wettability heterogeneity and alteration on two-phase flow performance for heterogeneous rock. Super-resolution methods combined with a deep learning approach will be used to determine a digital representation of reservoir rock, achieving an unprecedented combinat ....X-ray imaging and magnetic resonance approach for enhanced oil recovery. This project aims to develop an efficient multi-scale modelling capability to quantify the effect of two-phase fluid flow within porous material by modelling rock wettability heterogeneity and alteration on two-phase flow performance for heterogeneous rock. Super-resolution methods combined with a deep learning approach will be used to determine a digital representation of reservoir rock, achieving an unprecedented combination of resolution necessary to resolve small-scale fluid connectivity and field of view required to capture heterogeneity. The project expects to develop a workflow to populate a high-resolution model with wettability parameters by combining micro-CT imaging with nuclear magnetic resonance measurements. This improved understanding should provide significant benefits by enhancing our capability to optimise enhanced oil and gas recovery programs.Read moreRead less