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
Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources. This project aims to investigate and develop techniques to improve customer relationship management (CRM) for public and private organisations. It aims to develop an intelligent framework to assist in adaptive marketing and management of customers. The framework is designed to manage multiple information resources for information sharing, and to synthesise knowledge through visualisation. Intended outcomes are standardised XM ....Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources. This project aims to investigate and develop techniques to improve customer relationship management (CRM) for public and private organisations. It aims to develop an intelligent framework to assist in adaptive marketing and management of customers. The framework is designed to manage multiple information resources for information sharing, and to synthesise knowledge through visualisation. Intended outcomes are standardised XML profiles for the different data sets and business processes, novel techniques for conjoint mining of structured and semi-structured data, and adaptive business intelligence techniques. The results will be validated using large real-world data sets provided by the partner organisation.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.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
A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extrac ....A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extractor for automatically extracting features, an optimiser for finding optimal parameters and non-iterative ensemble learning technique for classification of features into classes. The impact of this project will be automatic feature extractors and classifiers for real-world applications.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120102948
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Interactive computer vision for image interpretation. This project aims at pushing forward the fundamental research in interactive computer vision. The outcome of this project will enable reliable and efficient solutions to real world image interpretation tasks, such as medical image analysis, financial document processing, and impact evaluation from natural disasters.
Examining multi-level Information Technology (IT) project alignment in government services: the case of contracted employment services. Improved Information Technology (IT) alignment is essential for the delivery of government services within a complex public-private, inter-organisational environment. This project will investigate the extent to which well-aligned IT support systems contribute positively to the efficient and effective delivery of contracted employment services.
The Intended and Unintended Impact of Policy for Adaptive Policy Management. The project aims to advance knowledge about the intended and unintended consequences of policy on health and well-being. It expects to innovate through new methods and novel data to integrate policy evaluation into the policy cycle in a timely fashion to prevent harm from occurring. It also leverages technology to track policy effects in real time. Expected outcomes of this project include new knowledge and enhanced pol ....The Intended and Unintended Impact of Policy for Adaptive Policy Management. The project aims to advance knowledge about the intended and unintended consequences of policy on health and well-being. It expects to innovate through new methods and novel data to integrate policy evaluation into the policy cycle in a timely fashion to prevent harm from occurring. It also leverages technology to track policy effects in real time. Expected outcomes of this project include new knowledge and enhanced policy infrastructure using new methods and interdisciplinary approaches. Significant benefits include improvements to: (1) policy management by government departments; (2) the health and wellbeing of the Australians they serve; (3) our Partners' capacity to consult governments on how technology can assist policy management. Read moreRead less
Special Research Initiatives - Grant ID: SR0354696
Funder
Australian Research Council
Funding Amount
$30,000.00
Summary
ARC Research Network in Enterprise Information Infrastructure (EII). This research network targets investigation of Enterprise Computing and its infrastructure, with an emphasis on emerging advanced technologies and practices, for large-scale enterprises, government agencies and community groups. EII will bring together the best IT researchers, leading edge users and key IT technology providers to support consolidated, technically sound, integrated and strategically positioned research towards s ....ARC Research Network in Enterprise Information Infrastructure (EII). This research network targets investigation of Enterprise Computing and its infrastructure, with an emphasis on emerging advanced technologies and practices, for large-scale enterprises, government agencies and community groups. EII will bring together the best IT researchers, leading edge users and key IT technology providers to support consolidated, technically sound, integrated and strategically positioned research towards solutions for next generation Enterprise Computing. Web services, the Semantic Web and Service Oriented Computing are fast emerging new disciplines with far reaching impacts. EII will contribute to their growth and to their practical deployment in Australia and beyond. The establishment of EII network will dramatically add value to already supported but often fragmented research projects.Read moreRead less
Multi-level analysis of human resource management systems on hospital outcomes. This project explores the relationships among human resource management systems, perceived organisational support, trust-in-management and commitment of healthcare workers. The fundamental aim is to assist hospital managers to determine where to direct their efforts to have maximum impact upon staff and hospital performance.