A high throughput Grid based environment for real time bio-medical imaging. Together with Leica, we will build a virtual microscope facility that will provide substantial functionality not currently available in Australia. This facility will have major national and international impact on bio-medical imaging. The software solutions and infrastructure, developed as part of this program will have considerable commercial and strategic value in their own right. One guaranteed avenue for exploitation ....A high throughput Grid based environment for real time bio-medical imaging. Together with Leica, we will build a virtual microscope facility that will provide substantial functionality not currently available in Australia. This facility will have major national and international impact on bio-medical imaging. The software solutions and infrastructure, developed as part of this program will have considerable commercial and strategic value in their own right. One guaranteed avenue for exploitation of the software will clearly be through our industry partner, Leica. Importantly, our proposal consolidates a critical mass of expertise connecting biomedical with computer science, thereby addressing a well-recognised constraint that to date has limited their national and international impact.Read moreRead less
Innovative visualization of next-generation biomedical images. This project addresses the difficult problems associated with managing the vast amounts of data that are currently available with advanced imaging devices and displaying these data so that the maximum amount of information can be extracted. Developing visualization capabilities for such data is not a trivial undertaking but the outcome of this research will produce enabling visualization technologies that will significantly impact th ....Innovative visualization of next-generation biomedical images. This project addresses the difficult problems associated with managing the vast amounts of data that are currently available with advanced imaging devices and displaying these data so that the maximum amount of information can be extracted. Developing visualization capabilities for such data is not a trivial undertaking but the outcome of this research will produce enabling visualization technologies that will significantly impact the life science, biomedical research and the way clinicians view and use these data for patient management. These technologies will have broad applications across biology and molecular science and will enhance Australia's leading position in the development of frontier technologies.Read moreRead less
Detection and Quantification of General Fetal Movements from Accelerometer Measurements using Nonstationary Signal Processing Techniques. There are approximately 1,750 fetal deaths per year in Australian with about one-third occurring late in gestation and without an apparent cause. The development of an automated system capable of long-term monitoring of fetal health will result in accurate diagnoses and prediction of future outcome. This will, in turn, allow early intervention by the clinicia ....Detection and Quantification of General Fetal Movements from Accelerometer Measurements using Nonstationary Signal Processing Techniques. There are approximately 1,750 fetal deaths per year in Australian with about one-third occurring late in gestation and without an apparent cause. The development of an automated system capable of long-term monitoring of fetal health will result in accurate diagnoses and prediction of future outcome. This will, in turn, allow early intervention by the clinician to reduce fetal deaths and enhance the chances of good outcomes with resultant savings in social and financial costs to the community. The development of such equipment would spawn future research into intervention treatments and contribute to Australia's position as a world leader in computerised health monitoring systems.Read moreRead less
Multi-Channel Time-Frequency Analysis for EEG Neonatal Seizure Characterization. This project researches new signal processing methodologies for a multi-channel characterization of seizures for use in diagnosing newborn brain dysfunctions. The outcomes will result in important immediate clinical benefits for sick newborn babies and will fundamentally facilitate research progress in the development of neuroprotectants and anticonvulsants. The success of this project will contribute in minimizing ....Multi-Channel Time-Frequency Analysis for EEG Neonatal Seizure Characterization. This project researches new signal processing methodologies for a multi-channel characterization of seizures for use in diagnosing newborn brain dysfunctions. The outcomes will result in important immediate clinical benefits for sick newborn babies and will fundamentally facilitate research progress in the development of neuroprotectants and anticonvulsants. The success of this project will contribute in minimizing the social financial costs by diagnosing brain disorders in the initial stage of life and preventing further damage. This has the potential to result in a standard diagnostic equipment in neonatal intensive care units and medical research centres.Read moreRead less
Design of Neonatal Seizure Diagnosis Methods Using Time-Frequency Signal Processing Techniques. Seizures occur in approximately 0.5% of all newborns. They are often the only indicator of an early dysfunction in central nervous system (CNS). Their occurrence raises concerns about the underlying cause, its effect on the brain, and the appropriate treatment. Newborn seizures are mostly sub-clinical and only detected through the Electroencephalogram. For an efficient diagnosis, seizure classificatio ....Design of Neonatal Seizure Diagnosis Methods Using Time-Frequency Signal Processing Techniques. Seizures occur in approximately 0.5% of all newborns. They are often the only indicator of an early dysfunction in central nervous system (CNS). Their occurrence raises concerns about the underlying cause, its effect on the brain, and the appropriate treatment. Newborn seizures are mostly sub-clinical and only detected through the Electroencephalogram. For an efficient diagnosis, seizure classification systems were proposed based on visual observations. This project proposes developing a novel approach to automate the classification process using time-frequency (TF) signal processing techniques based on the multi-channel characteristics of the seizure; namely: A) TF signature B) origin, and C) propagation behaviour.Read moreRead less
Computing with nearly-consistent data. This project will help programmers correctly use data that originates at various times and places, and spreads unevenly through a system. Computation will combine data that comes from different situations, and is not exactly consistent. Capability to develop high quality software on platforms with this feature will enhance the value of the Australian IT industry. As well, the industries which use the software benefit from correctly working with their data. ....Computing with nearly-consistent data. This project will help programmers correctly use data that originates at various times and places, and spreads unevenly through a system. Computation will combine data that comes from different situations, and is not exactly consistent. Capability to develop high quality software on platforms with this feature will enhance the value of the Australian IT industry. As well, the industries which use the software benefit from correctly working with their data. Sensor networks have data like this, and they play a vital role in environmental monitoring. Cloud computing platforms also have this type of data, and these allow smaller enterprises to grow smoothly, without needing large up-front investments in computing infrastructure.Read moreRead less
Enhanced Automation of Close-Range Photogrammetry for Defence and National Security Applications. The project, which falls under the National Research Priority of safeguarding Australia, will be of significant national and community benefit. The research outcomes will advance close-range photogrammetry (CRP) technology, especially in the critical areas of defence and national security. It will lower the cost base of CRP and expand its commercial potential in new application domains, thus promoti ....Enhanced Automation of Close-Range Photogrammetry for Defence and National Security Applications. The project, which falls under the National Research Priority of safeguarding Australia, will be of significant national and community benefit. The research outcomes will advance close-range photogrammetry (CRP) technology, especially in the critical areas of defence and national security. It will lower the cost base of CRP and expand its commercial potential in new application domains, thus promoting business activity in the broader Australian spatial information industry. Also, community oriented benefits will be seen through the improved prospects for new public-good applications of CRP, ranging for example from cultural heritage recording through to homeland security and forensic measurement for crime scene analysis.Read moreRead less
Development of methods to address internet crime. If this research accomplishes successfully, it will be a big step forward in terms of traceback scope, accuracy, usability and deployment. This will empower authorities to control and punish Internet crimes more effectively and efficiently. It will also limit the damage caused by Internet crimes quickly. For example, if we can quickly identify the origins of a fast spreading virus, we will be able to prevent its propagation as fast as possible. I ....Development of methods to address internet crime. If this research accomplishes successfully, it will be a big step forward in terms of traceback scope, accuracy, usability and deployment. This will empower authorities to control and punish Internet crimes more effectively and efficiently. It will also limit the damage caused by Internet crimes quickly. For example, if we can quickly identify the origins of a fast spreading virus, we will be able to prevent its propagation as fast as possible. If we can quickly identify and block a harmful phishing site, then less innocent people will be deceived into disclosing their credit card numbers, bank account information, passwords or other sensitive information.Read moreRead less
Extending a family of garbage collectors. Garbage collection is a key component in the automatic management of storage in computer systems. It is an essential property of modern programming systems that frees the programmer from a significant error-prone task. Our interest is in garbage collection in distributed systems involving a number of networked computers. Using our novel construction methodology, we have jointly produced a family of collection algorithms that are significantly simpler and ....Extending a family of garbage collectors. Garbage collection is a key component in the automatic management of storage in computer systems. It is an essential property of modern programming systems that frees the programmer from a significant error-prone task. Our interest is in garbage collection in distributed systems involving a number of networked computers. Using our novel construction methodology, we have jointly produced a family of collection algorithms that are significantly simpler and more efficient than previous work. Here we wish to extend this family to operate effectively in a specific architecture increasingly favoured by many modern distributed high-performance computing systems.Read moreRead less
Asymptotic Geometric Analysis and Machine Learning. Phenomena in large dimensions appear in a number of domains of Mathematics and adjacent domains of science (e.g. Computer Science), dealing with functions of infinitely growing number of parameters. Here, we focus on several questions naturally linked to Asymptotic Geometric Analysis which have natural applications to Statistical Learning Theory. We intend to use geometric, probabilistic and combinatorial methods to investigate these problems, ....Asymptotic Geometric Analysis and Machine Learning. Phenomena in large dimensions appear in a number of domains of Mathematics and adjacent domains of science (e.g. Computer Science), dealing with functions of infinitely growing number of parameters. Here, we focus on several questions naturally linked to Asymptotic Geometric Analysis which have natural applications to Statistical Learning Theory. We intend to use geometric, probabilistic and combinatorial methods to investigate these problems, with an emphasis on modern tools in Empirical Processes Theory and the theory of Random Matrices.Read moreRead less