Zero Defect Manufacturing of Complex Assemblies. The aim of this research project is to develop the tools required to design and implement zero defect manufacturing systems. It is intended that generic guidelines will be developed for achieving zero defect manufacturing of complex assemblies in a cost effective manner. Methodologies and techniques derived from these guidelines will be tested and validated on an existing door trim assembly production line. This project with its emphasis on utilis ....Zero Defect Manufacturing of Complex Assemblies. The aim of this research project is to develop the tools required to design and implement zero defect manufacturing systems. It is intended that generic guidelines will be developed for achieving zero defect manufacturing of complex assemblies in a cost effective manner. Methodologies and techniques derived from these guidelines will be tested and validated on an existing door trim assembly production line. This project with its emphasis on utilising manufacturing systems involving a mix of human and robot based operations and in process inspection techniques to achieve defect free manufacturing is particularly relevant to medium size component suppliers.Read moreRead less
Discovering justified knowledge from data. Knowledge discovery from data has assumed a critical role in numerous areas of science, commerce and public administration. However, its effectiveness is limited by the undesirable propensity of current techniques to make many false, as well as real, discoveries. This research will rectify that problem, a critical outcome given the potential cost of making decisions or setting policy using flawed information. For example, it may prevent the adoption of ....Discovering justified knowledge from data. Knowledge discovery from data has assumed a critical role in numerous areas of science, commerce and public administration. However, its effectiveness is limited by the undesirable propensity of current techniques to make many false, as well as real, discoveries. This research will rectify that problem, a critical outcome given the potential cost of making decisions or setting policy using flawed information. For example, it may prevent the adoption of ineffective strategies for addressing land degradation; inappropriately targeted public health expenditure; expensive development and clinical trialing of drugs which prove ineffective; and wasted police and security investigations into unfounded suspicions of criminal or terrorist activity.Read moreRead less
Learning Semi-Naive Bayesian Classifiers from Numeric Data. This project addresses research priority 3, offering frontier technologies. It will deliver better and faster classification technologies that greatly help accomplish many real-world tasks including medical diagnosis, fraud detection, spam filtering and webpage search, where accurate and fast classification is critical to save life, increase efficiency, reduce crime and conserve resources. Hence this project addresses priority 4 as well ....Learning Semi-Naive Bayesian Classifiers from Numeric Data. This project addresses research priority 3, offering frontier technologies. It will deliver better and faster classification technologies that greatly help accomplish many real-world tasks including medical diagnosis, fraud detection, spam filtering and webpage search, where accurate and fast classification is critical to save life, increase efficiency, reduce crime and conserve resources. Hence this project addresses priority 4 as well, better safeguarding Australia from disease and crime. This project will also support a young research group of international standing. It will train the involved researchers to attain a high level of proficiency and excellence in machine learning research and development.Read moreRead less
A generic decision-making design environment to enable end users in rural industries to develop expert systems. Successful decision support systems developed by end-users has been limited: our proposed approach advances this capability. Using natural representations of industry knowledge, this project will specify a generic design environment in which industry end-users can develop relevant decision support systems. It extends expert systems technologies to overcome known limitations, increasin ....A generic decision-making design environment to enable end users in rural industries to develop expert systems. Successful decision support systems developed by end-users has been limited: our proposed approach advances this capability. Using natural representations of industry knowledge, this project will specify a generic design environment in which industry end-users can develop relevant decision support systems. It extends expert systems technologies to overcome known limitations, increasing context and relevance and encouraging user uptake. Key industry stakeholders will select relevant problems to identify decision categories, leading to specification of the generic design environment. This promises improved decision quality for dairy farmers in the recently deregulated dairy industry; the design environment will be transferable to other rural industries.Read moreRead less
Achieving higher availability of storage subsystems through application of a self learning expert system. In todays global business environment the management, storage and security of enterprise data (data unavailability, data loss and corruption, systems performance) has become the heart of so-called Enterprise computing. The storage subsystems increasingly have become the critical subcomponent and single point of failure. Discovering the cause of failure in complex environments involving mul ....Achieving higher availability of storage subsystems through application of a self learning expert system. In todays global business environment the management, storage and security of enterprise data (data unavailability, data loss and corruption, systems performance) has become the heart of so-called Enterprise computing. The storage subsystems increasingly have become the critical subcomponent and single point of failure. Discovering the cause of failure in complex environments involving multiple vendors, machines, software products, topologies and cultures (languages) is in many cases time consuming and difficult resulting in unacceptable systems downtime and high maintenance costs. A more sophisticated tool is needed allowing the accumulation of knowledge, the ability to deal with complexity and change, the ability to interface with unlike knowledge bases and predict solution probability based on experience and feedback. Multi-lingual support and capability through the development of a Natural Language interface would provide a functional capability suited to managing enterprise data in todays global businesses.Read moreRead less
Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are a ....Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are at high risk of incurring debt and defaulting on paying taxes. In turn, the early identification of clients in financial distress will allow the ATO to give them assistance so that they can reduce their debts and meet their financial obligations.Read moreRead less
Incremental Knowledge Acquisition for Machine Translation from Multiple Experts. With increasing globalisation and an increasing amount of electronically available documents the need for machine translation is growing dramatically. The state-of-the-art in machine translation is still far from satisfactory. Substantial post-editing is necessary for most non-technical texts and even for many technical documents to make the translation really understandable. This project will develop a new approach ....Incremental Knowledge Acquisition for Machine Translation from Multiple Experts. With increasing globalisation and an increasing amount of electronically available documents the need for machine translation is growing dramatically. The state-of-the-art in machine translation is still far from satisfactory. Substantial post-editing is necessary for most non-technical texts and even for many technical documents to make the translation really understandable. This project will develop a new approach for buildingmachine translation systems by extending the unorthodox approach of Ripple-Down Rules, which proved very successful for building expert systems in the medical domain.It is intended to build a machine translation system by integrating the knowledge from many experts.Read moreRead less
Improving human reasoning with causal Bayes networks: a multimodal approach. This project aims to improve human causal and probabilistic reasoning about complex systems by taking a user-centric, multimodal, interactive approach. The project will explore new integrated visual and verbal ways of explaining a causal probabilistic model and its reasoning, to reduce known human reasoning difficulties, and investigate how to reduce cognitive load by prioritising the most useful user- and context-speci ....Improving human reasoning with causal Bayes networks: a multimodal approach. This project aims to improve human causal and probabilistic reasoning about complex systems by taking a user-centric, multimodal, interactive approach. The project will explore new integrated visual and verbal ways of explaining a causal probabilistic model and its reasoning, to reduce known human reasoning difficulties, and investigate how to reduce cognitive load by prioritising the most useful user- and context-specific information. Expected outcomes include novel AI methods that empower users to drive the reasoning process and strengthen trust in the system’s reasoning. Performance will be assessed in medical and legal domains, with significant potential benefits to end users from better, more transparent reasoning and decision making.Read moreRead less
Advanced Bayesian Networks for Epidemiology. We will demonstrate the potential of advanced Artificial Intelligence for medical informatics by extending the capabilities of Bayesian Networks. Bayesian Networks excel when researchers need to combine causal and diagnostic reasoning in areas characterised by uncertainty. But they have one flaw which hinders their use: they do not yet easily mix continuous and discrete variables. We will extend them to handle such mixes, then demonstrate how much the ....Advanced Bayesian Networks for Epidemiology. We will demonstrate the potential of advanced Artificial Intelligence for medical informatics by extending the capabilities of Bayesian Networks. Bayesian Networks excel when researchers need to combine causal and diagnostic reasoning in areas characterised by uncertainty. But they have one flaw which hinders their use: they do not yet easily mix continuous and discrete variables. We will extend them to handle such mixes, then demonstrate how much they can improve on current methods for predicting, among other things, coronary heart disease (CHD).Read moreRead less
Multi-Ontologies meet UML: Improving the Software Engineering of Multi-Agent Systems. Multi-agent systems are a new style of software well suited for open, dynamic, distributed, global, heterogeneous environments such as the Internet. Systematic methods are needed to allow multi-agent systems to reason effectively with high level knowledge. This research draws on software engineering practice to develop a theory and methodology for multi-ontologies for expressing knowledge within multi-agent sys ....Multi-Ontologies meet UML: Improving the Software Engineering of Multi-Agent Systems. Multi-agent systems are a new style of software well suited for open, dynamic, distributed, global, heterogeneous environments such as the Internet. Systematic methods are needed to allow multi-agent systems to reason effectively with high level knowledge. This research draws on software engineering practice to develop a theory and methodology for multi-ontologies for expressing knowledge within multi-agent systems that facilitate adaptation and change.
Read moreRead less