Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Scalable Robust Video Surveillance over Constrained Networks. Real-time monitoring of large numbers of people is becoming increasingly important for applications such as efficient service delivery and security against both common crime and terrorism. The use of human operators for such tasks is infeasible due to the large amount of data collected. Existing autonomous video surveillance systems are prone to high numbers of false alarms and often require expensive hardware. This proposal seeks ....Scalable Robust Video Surveillance over Constrained Networks. Real-time monitoring of large numbers of people is becoming increasingly important for applications such as efficient service delivery and security against both common crime and terrorism. The use of human operators for such tasks is infeasible due to the large amount of data collected. Existing autonomous video surveillance systems are prone to high numbers of false alarms and often require expensive hardware. This proposal seeks to address both difficulties by using rigorous statistical signal processing methods to optimally fuse information from a network of low-cost cameras.Read moreRead less
Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including comm ....Space-based space surveillance with robust computer vision algorithms. Space-based space surveillance with robust computer vision algorithms. This project aims to develop computer vision algorithms to detect man-made objects in space. These algorithms function on nanosatellite platforms, enabling space-based space surveillance. This technology is expected to provide always-on monitoring of the Earth's orbit to enhance existing defence infrastructure and protect vital space assets, including communications and navigational satellites, in Earth’s orbit from collisions and covert sabotage. Increased space use by government and civilian agencies opens up opportunities for the space industry. This project is expected to develop Australia’s space surveillance capabilities, protect space assets and capture a growing market.Read moreRead less
Robust and scalable change detection in geo-spatial data. A flood of data in the form of text, images and video emanate from a proliferation of sensors. These data are collected but rarely analysed, rendering it meaningless. This project aims to develop new software and techniques to detect changes over time in large scale geographically referenced data (for example photomaps) for use across numerous domains.
Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emer ....Design of adaptive learning visual sensor networks for crowd modelling in high-density and occluded scenarios. Partnering University of Melbourne researchers, with video surveillance experts SenSen, engineering consultants ARUP and the Melbourne Cricket Club, the project addresses research enabling a system-integrating, existing surveillance, infrastructure to model crowd behaviour and exit strategies, providing real-time analysis, prediction and response capabilities for venue managers and emergency services. This new capability enhances utilisation of security resources to prevent injury and fatalities in evacuation scenarios, applicable to existing venues and influencing the development of new facilities around the country. The project delivers researcher training, global clientele for local technology and a platform for local industry growth.Read moreRead less
Characterisation and Mitigation of Caustic Cracking: A Safety and Maintenance Concern in Alumina and Pulp-and-Paper Processing. Extraction of alumina from mineral bauxite (Bayer process) and pulp-and-paper processing (Kraft process) are major industries in Australia. Cracking of reaction vessels, digesters, cleaning tanks and pipework are major concern for plant integrity, occupational health, safety and environment. Caustic cracking is often the first suspect when a failure occurs. The propose ....Characterisation and Mitigation of Caustic Cracking: A Safety and Maintenance Concern in Alumina and Pulp-and-Paper Processing. Extraction of alumina from mineral bauxite (Bayer process) and pulp-and-paper processing (Kraft process) are major industries in Australia. Cracking of reaction vessels, digesters, cleaning tanks and pipework are major concern for plant integrity, occupational health, safety and environment. Caustic cracking is often the first suspect when a failure occurs. The proposed program will investigate the role of critical impurities and additives, temperature and stress fluctuations in caustic cracking of mild steel and their weldments (known to be most susceptible). This project will also develop an intellectual and infrastructural base that will also be a vital resource for several Australian industries where such cracking is a major concern.Read moreRead less
Experimental and numerical studies of the packing of alumina powders. This project is to investigate the packing of alumina powders at both microscopic and macroscopic levels by means of physical and numerical experiments, aiming to develop a comprehensive understanding of the underlying physics and computer models for predicting the packing properties under conditions corresponding to different operations in alumina refining and smelting processes. It will generate an effective method to solve ....Experimental and numerical studies of the packing of alumina powders. This project is to investigate the packing of alumina powders at both microscopic and macroscopic levels by means of physical and numerical experiments, aiming to develop a comprehensive understanding of the underlying physics and computer models for predicting the packing properties under conditions corresponding to different operations in alumina refining and smelting processes. It will generate an effective method to solve the complex packing problems for process and/or property control in alumina/aluminium industry.Read moreRead less
Analysis of effective offshoring processes for Australian organisations. The offshore outsourcing of business processes is a new, largely unexplored and under-theorised area that is placing great pressure on Australian organisations. This research aims to develop models of best practice for offshoring by Australian organisations through a series of cases studies commencing with the industry partner, Repcol Limited. The research will identify what business processes are core, what processes can b ....Analysis of effective offshoring processes for Australian organisations. The offshore outsourcing of business processes is a new, largely unexplored and under-theorised area that is placing great pressure on Australian organisations. This research aims to develop models of best practice for offshoring by Australian organisations through a series of cases studies commencing with the industry partner, Repcol Limited. The research will identify what business processes are core, what processes can be offshored, whether to use third parties or have captive operations, and what factors need to be addressed in order to utilise offshoring to strengthen Australian organisations and enable them to take advantage of global strategic opportunities for growth.Read moreRead less
Evolutionary Design for Ore Processing Plants. This project will investigate the use of evolutionary algorithms (EAs) in the design of ore processing plants. Ore processing is a major activity in the Australian mining industry, and a significant source of export dollars. Prior work has demonstrated that EAs can out-perform previous manual and automated design techniques for individual processing units. This project will apply EAs to the design of whole flowsheets containing arbitrary combination ....Evolutionary Design for Ore Processing Plants. This project will investigate the use of evolutionary algorithms (EAs) in the design of ore processing plants. Ore processing is a major activity in the Australian mining industry, and a significant source of export dollars. Prior work has demonstrated that EAs can out-perform previous manual and automated design techniques for individual processing units. This project will apply EAs to the design of whole flowsheets containing arbitrary combinations of different types of units. The complexity of typical flowsheet layouts will require new algorithms to discover improved designs in practical time, so parallel hardware, and new parallel EAs, will be utilised.
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A theoretical framework for practical partial fingerprint identification. Fingerprints captured from a crime scene are often partial and poor quality which makes it difficult to identify the criminal suspects from large databases. This project will find mathematical models which can estimate the missing information located in the blank areas of a partial fingerprint and effectively identify it.