ARC Centre for Perceptive & Intelligent Machines in Complex Environments. The Centre for Perceptive and Intelligent Machines in Complex Environments will perform fundamental research into and construct reliable large-scale systems of networked sensors, computational intelligence, mobile robots, and knowledge sources to support a large variety of critical human tasks, including surveillance/ security (eg. borders/airports/homes), health care support (eg. smart houses/ health condition monitoring, ....ARC Centre for Perceptive & Intelligent Machines in Complex Environments. The Centre for Perceptive and Intelligent Machines in Complex Environments will perform fundamental research into and construct reliable large-scale systems of networked sensors, computational intelligence, mobile robots, and knowledge sources to support a large variety of critical human tasks, including surveillance/ security (eg. borders/airports/homes), health care support (eg. smart houses/ health condition monitoring, semi autonomous wheelchairs), and civil disaster support (eg. fighting bushfires, looking for people in rubble) always keeping people in the loop so that strong human/ machine cooperative ventures can achieve what neither human or machines could accomplish independently.Read moreRead less
ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environme ....ARC Research Network in Enterprise Information Infrastructure. EII targets consolidated research towards the comprehensive development & establishment of advanced information infrastructures. Its prime purpose is to provide a forum for intellectual exchange by diverse yet complementary research groups, to address the fundamental research problems faced by scientific & business communities when dealing with deployment of information technology to globally distributed, and data intensive environments. EII will address 3 tightly coupled research themes: Ability to interoperate across existing heterogenous platforms & applications; Efficient processing of very large data sets; Technology adoption & impact. Generic results will be applicable to e-science and large business information systems installations.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100431
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Optimising the use of geophysical data for modelling the Australian crust. This project aims to determine the optimal use of geophysical methods to model the Australian crust in four dimensions. These models provide an understanding of the tectonic history of a region and thus its mineral potential. Mineral resources are mostly being found undercover, requiring geophysical data to locate them. This project will combine recent developments in modelling geological uncertainty with data acquired fo ....Optimising the use of geophysical data for modelling the Australian crust. This project aims to determine the optimal use of geophysical methods to model the Australian crust in four dimensions. These models provide an understanding of the tectonic history of a region and thus its mineral potential. Mineral resources are mostly being found undercover, requiring geophysical data to locate them. This project will combine recent developments in modelling geological uncertainty with data acquired for locating zones of mineralisation. The outcomes will help guide Australian government policy to draw on publicly-available datasets that provide a basis for mineral exploration performed by companies, and supported by research institutions.Read moreRead less
Next generation Customer Relationship Management (CRM) framework through intelligence and relationships from multiple information sources. In the current competitive times, organisations need to improve their service delivery and customer care processes and provide customised service to customers. This project develops a Customer Relationship Management (CRM) framework that can extract intelligence and relationships from multiple data sources to improve customer management and satisfaction in pu ....Next generation Customer Relationship Management (CRM) framework through intelligence and relationships from multiple information sources. In the current competitive times, organisations need to improve their service delivery and customer care processes and provide customised service to customers. This project develops a Customer Relationship Management (CRM) framework that can extract intelligence and relationships from multiple data sources to improve customer management and satisfaction in public and private organisations.Read moreRead less
Modelling human decision making in complex environments. The project aims to extend quantitative psychological models of simple choice tasks to decision-making with complex stimuli in complex environments. The new formal models are designed to provide a comprehensive account of behaviour, including the choices that are made, how long it takes to make them, and how choices and choice times vary within and between decision-makers. The models would explain how people adapt to changes in task demand ....Modelling human decision making in complex environments. The project aims to extend quantitative psychological models of simple choice tasks to decision-making with complex stimuli in complex environments. The new formal models are designed to provide a comprehensive account of behaviour, including the choices that are made, how long it takes to make them, and how choices and choice times vary within and between decision-makers. The models would explain how people adapt to changes in task demands when dealing with multiple stimuli or performing multiple tasks concurrently under time pressure. The project aims to provide the basic research that is needed to extend psychological models of choice to complex ‘real-world’ tasks, such air traffic control and maritime surveillance.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
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
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.
Discovery Early Career Researcher Award - Grant ID: DE170101081
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis t ....Adaptive value-flow analysis to improve code reliability and security. This project aims to develop client-driven adaptive value-flow analysis to detect software bugs in system software written in the C/C++ programme language. Static analysis tools for automated code inspections can benefit software developers, but are imprecise, inefficient and not user-friendly for analysing real-world industrial-sized software. The project will investigate static, dynamic and user-guided value-flow analysis to efficiently and precisely analyse large-scale programs according to clients’ needs, thereby allowing compilers to generate safe, reliable and secure code. This project is expected to advance value-flow analysis for industrial-sized software, improve software reliability and security, and benefit Australian software systems and industries.Read moreRead less
Developing smart embedded host-based intrusion detection systems. Computer intrusion is a major concern in many places. It is estimated that cybercrime cost firms US$1 trillion globally in 2008. Many serious cyber attacks, including cyber espionage, do not generate significant network traffic and can easily penetrate network-based intrusion detection systems (NIDS). Such attacks often attempt to compromise individual hosts and hence they are best detected at the host level. We aim to design i ....Developing smart embedded host-based intrusion detection systems. Computer intrusion is a major concern in many places. It is estimated that cybercrime cost firms US$1 trillion globally in 2008. Many serious cyber attacks, including cyber espionage, do not generate significant network traffic and can easily penetrate network-based intrusion detection systems (NIDS). Such attacks often attempt to compromise individual hosts and hence they are best detected at the host level. We aim to design innovative host-based IDS, as a complement to the NIDS, to address this issue. The outcomes of this project will strengthen the national capability to resist attacks by criminals and terrorists on Australian networked critical infrastructures and also enhance the global competitiveness of Australia’s information technology industry.Read moreRead less