Integrated Financial Fraud Detection in Enterprise Applications. Fraud costs the Australian economy at least $3 billion per year. The incidence of fraud within the Australian economy is increasing. Australian entities are ill-prepared to detect and prevent fraud against their businesses with very few developing or implementing any form of fraud control strategy (AS 8001-2003). The growing use of the Internet by organisations for electronic commerce increases their exposure to fraudulent activiti ....Integrated Financial Fraud Detection in Enterprise Applications. Fraud costs the Australian economy at least $3 billion per year. The incidence of fraud within the Australian economy is increasing. Australian entities are ill-prepared to detect and prevent fraud against their businesses with very few developing or implementing any form of fraud control strategy (AS 8001-2003). The growing use of the Internet by organisations for electronic commerce increases their exposure to fraudulent activities. Inevitably much of the cost of fraud is passed on to the customers and the community at large. By providing large organisations with an approach to assist in detecting fraudulent behaviour in accounting systems, it is envisaged that this research will assist in reducing the impact of fraud on society.Read moreRead less
Finding new economic drivers for Sea Change (coastal) and similar rapidly growing communities. This project is of major benefit to developing more environmentally sensitive but diverse economies for coastal communities. Coastal communities are commuter or tourism dominated, each of these issues generate both current and future liabilities for the communities and the nation.
Efficient Prediction of Application Metrics for E-Services. Application Service Providers (ASPs) are one of the fastest growing classes of e-services and operate on the principle of renting software applications. This project aims to develop prediction techniques to estimate quality of service metrics for ASPs. The efficient prediction of the service levels that can be ensured is challenging given the dynamic nature of the Internet and the semantics of application metrics not being formally defi ....Efficient Prediction of Application Metrics for E-Services. Application Service Providers (ASPs) are one of the fastest growing classes of e-services and operate on the principle of renting software applications. This project aims to develop prediction techniques to estimate quality of service metrics for ASPs. The efficient prediction of the service levels that can be ensured is challenging given the dynamic nature of the Internet and the semantics of application metrics not being formally defined. The project will result in the development of a prototype system to support prediction of service levels. This system will be accessible to the Australian e-services industry via a web interface.Read moreRead less
Adaptive data stream processing in heterogeneous distributed computing environments using real-time context. This project falls within the ARC research priority goal, Smart Information Use. The innovative contributions of this project through the development of adaptive data stream mining algorithms for heterogeneous devices will have an impact on a range of emerging application areas such as:
1. Meeting time-critical, intelligent information needs of the mobile workforce (e.g. mobile healthca ....Adaptive data stream processing in heterogeneous distributed computing environments using real-time context. This project falls within the ARC research priority goal, Smart Information Use. The innovative contributions of this project through the development of adaptive data stream mining algorithms for heterogeneous devices will have an impact on a range of emerging application areas such as:
1. Meeting time-critical, intelligent information needs of the mobile workforce (e.g. mobile healthcare professionals, stockbrokers). 2. Improving Intelligent Transportation Systems via in-vehicle analysis and crash prevention. 3. Facilitating 'on-board' analysis in sensors that monitor the environment and patients. The project will enhance Australia's leading international role in the area of data stream processing in distributed computing environments.Read moreRead less
Effective Fuzzy Systems for Complex Structured Data Using Fuzzy Signatures. We are developing systematic, heuristic and mathematical techniques to produce effective fuzzy systems for complex structured data. Many or most real world problems have data which has interdependent sub-components depending on the context (eg only female patients need be tested for pregnancy), and often has missing components. Our techniques use fuzzy signatures to extend simple fuzzy systems to deal with data with such ....Effective Fuzzy Systems for Complex Structured Data Using Fuzzy Signatures. We are developing systematic, heuristic and mathematical techniques to produce effective fuzzy systems for complex structured data. Many or most real world problems have data which has interdependent sub-components depending on the context (eg only female patients need be tested for pregnancy), and often has missing components. Our techniques use fuzzy signatures to extend simple fuzzy systems to deal with data with such complex (sub-)structure. This produces effective fuzzy systems with wide applicability to real problems, in telecommunications, and petroleum reservoir data.Read moreRead less
Developing Minimum Message Length and Support Vector Machine methods to predict user behaviour. Predicting and modelling customer behaviour enables considerable savings in the telecommunications industry and elsewhere. The resulting predictive models facilitate identifying novice users, identifying fraud, responding to users' needs, guiding and advising users, and forwarding useful information.
We consider two cutting-edge data mining approaches, Minimum Message Length (developed and led by ....Developing Minimum Message Length and Support Vector Machine methods to predict user behaviour. Predicting and modelling customer behaviour enables considerable savings in the telecommunications industry and elsewhere. The resulting predictive models facilitate identifying novice users, identifying fraud, responding to users' needs, guiding and advising users, and forwarding useful information.
We consider two cutting-edge data mining approaches, Minimum Message Length (developed and led by Monash) and Support Vector Machines, in order to create efficient tailor-made software.
Our software will respond to specific groups of users, and their changes over time, rather than just the average user. Moreover, it will integrate the functionalities of existing individual data mining software.Read moreRead less
Coherent Transport of Spin Qubits in an Engineered-Atom Silicon Quantum Computer: Demonstrating the Critical Spintronics. The project will enhance Australia's scientific credentials in the nanotechnology national priority area and research capacity to play a role in the next-generation computer industry based on quantum technologies. Through its involvement of young postgraduate students and postdoctoral researchers in advanced science and technology, and strong international positioning, it wil ....Coherent Transport of Spin Qubits in an Engineered-Atom Silicon Quantum Computer: Demonstrating the Critical Spintronics. The project will enhance Australia's scientific credentials in the nanotechnology national priority area and research capacity to play a role in the next-generation computer industry based on quantum technologies. Through its involvement of young postgraduate students and postdoctoral researchers in advanced science and technology, and strong international positioning, it will strengthen Australia's intellectual capital and increase the prestige of Australian science. Quantum technology has the potential to impact the economy of nations and has important implications for national security. The project, through its focus on critical spintronic technology, will reinforce the investment in the Centre for Quantum Computer Technology.Read moreRead less
Resource-bounded adaptive inference of accurate conditional probability estimates from data. This project will develop machine learning techniques with a valuable new capability: the ability to produce estimates of complex conditional probabilities to varying levels of expected accuracy depending upon the constraints of available computational resources. This will provide significant competitive advantage to developers of many types of online application by allowing them to maximise utilisation ....Resource-bounded adaptive inference of accurate conditional probability estimates from data. This project will develop machine learning techniques with a valuable new capability: the ability to produce estimates of complex conditional probabilities to varying levels of expected accuracy depending upon the constraints of available computational resources. This will provide significant competitive advantage to developers of many types of online application by allowing them to maximise utilisation of available computational resources when making inferences from data, together with the flexibility to trade-off accuracy and computing resources during system design. Australia will also benefit by strengthening its machine learning expertise, which is central to many complex and intelligent systems and the booming data mining industry.Read moreRead less
Parametric Brain Imaging via Modeling and Analysis of Electroencephalographic Signals. Parameters of brain function and physiology will be spatially imaged with high time resolution via their effects on electroencephalographic (EEG) signals, a form of imaging that is impossible with existing methods. This will be achieved by improving existing physiologically-based models of the generation of EEGs and developing analysis tools based on fitting of model predictions to multielectrode EEG data. T ....Parametric Brain Imaging via Modeling and Analysis of Electroencephalographic Signals. Parameters of brain function and physiology will be spatially imaged with high time resolution via their effects on electroencephalographic (EEG) signals, a form of imaging that is impossible with existing methods. This will be achieved by improving existing physiologically-based models of the generation of EEGs and developing analysis tools based on fitting of model predictions to multielectrode EEG data. The results will be used to probe spatiotemporal features of EEGs in normal subjects to explore the underlying fundamental mechanisms and to infer novel parameter variations of practical relevance.Read moreRead less
Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering ap ....Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.Read moreRead less