Vision Model Based Perceptual Digital Video Coding. Digital video coding and compression is an enabling technology and has diversified applications in audiovisual communications, multimedia computing, digital television broadcast and electronic entertainment industries. The project aims at spearheading research in theory, techniques and implementation of perceptual video coding in order to achieve constant and guaranteed quality in visual communications and services. It will explore a new appr ....Vision Model Based Perceptual Digital Video Coding. Digital video coding and compression is an enabling technology and has diversified applications in audiovisual communications, multimedia computing, digital television broadcast and electronic entertainment industries. The project aims at spearheading research in theory, techniques and implementation of perceptual video coding in order to achieve constant and guaranteed quality in visual communications and services. It will explore a new approach to digital video coding other than the constant bit rate coding techniques which have dominated digital video research for the past four decades. It will form a part of the theoretical foundation and principles for the next generation video coding and compression techniques, and may lead to new standards and practice.Read moreRead less
Data Management Technologies for the Magnetic Resonance Imaging e-Research Grid. Howard Florey Institute researchers will collaborate with SGI's file-systems engineering team. Substantial benefits are expected from the development of techniques to support centralized and distributed processing medical image datasets. Issues requiring research include file space allocation algorithms and caching strategies. The proposed rapid database access technologies aim at solving these problems in the medic ....Data Management Technologies for the Magnetic Resonance Imaging e-Research Grid. Howard Florey Institute researchers will collaborate with SGI's file-systems engineering team. Substantial benefits are expected from the development of techniques to support centralized and distributed processing medical image datasets. Issues requiring research include file space allocation algorithms and caching strategies. The proposed rapid database access technologies aim at solving these problems in the medical imaging research context. The project attempts to 'improve data management for existing and new business applications'. This enhanced sharing of information will improve critical mass therefore fostering national and international collaboration. 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
Integrating deep-earth and surface processes for frontier-basin exploration. It is well-known that mantle convection has a profound influence on basin evolution, and the next step will be to quantify this relationship and provide the science that will make these concepts applicable to exploration. To do this, we will develop a workflow to link plate-reconstruction software with the mantle convection modelling to link plate motions mantle convection and the history of sedimentation systematically ....Integrating deep-earth and surface processes for frontier-basin exploration. It is well-known that mantle convection has a profound influence on basin evolution, and the next step will be to quantify this relationship and provide the science that will make these concepts applicable to exploration. To do this, we will develop a workflow to link plate-reconstruction software with the mantle convection modelling to link plate motions mantle convection and the history of sedimentation systematically for the first time for frontier basin-scale applications. We will apply these emerging technologies to the evolution of basins in the Arctic borderlands frontier for resource exploration and on the Australian continent.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
Multi-modal, Multi-dimensional Virtual Microscopy for Diagnostic Quantitative Pathology. This project will contribute to the development of a new generation of virtual microscopy (VM) systems that provide new and innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of pathology. These systems have the potential to significantly enhance the efficiency and efficacy of not only primary diagnostic workflows, but also aspects of profi ....Multi-modal, Multi-dimensional Virtual Microscopy for Diagnostic Quantitative Pathology. This project will contribute to the development of a new generation of virtual microscopy (VM) systems that provide new and innovative features capable of significantly increasing the adoption of digital imaging technology throughout the field of pathology. These systems have the potential to significantly enhance the efficiency and efficacy of not only primary diagnostic workflows, but also aspects of proficiency testing and continuing education vital for a vibrant, well regulated discipline. In addition, the project will contribute to our knowledge of the pathology assessed in the screening and diagnosis of cancers such as cervical, lung and bladder cancers.Read moreRead less
Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business t ....Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business tasks and handle fast-changing scenarios in business. The Self-Evolving EIA is a critical step on the path towards the future generation of EIA. Expected outcomes of this project are to develop adaptive EIA for Small and Medium Enterprise to improve their customer service quality.Read moreRead less
Optimum control of the in-use performance of talc-based compositions. It is important to improve the quality of their Talcom body powder, baby powder and other cosmetic products involving talc. The areas that can and need to be improved are shining characteristics, assessing the slip properties as well as developing the cosmetic chemistry of talc and other additives. The proposed project will generate: a) simple but reliable test methods for measuring slip and shine, b) methods for control of t ....Optimum control of the in-use performance of talc-based compositions. It is important to improve the quality of their Talcom body powder, baby powder and other cosmetic products involving talc. The areas that can and need to be improved are shining characteristics, assessing the slip properties as well as developing the cosmetic chemistry of talc and other additives. The proposed project will generate: a) simple but reliable test methods for measuring slip and shine, b) methods for control of the physical and chemical characteristics of talc blends, c) mathematical model(s) for property and process control, which is useful to improvement of the final talc properties and in-use service.Read moreRead less
Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the ....Interaction Mining for Cyberbullying Detection on Social Networks. This project plans to build an interactive mining system to detect cyberbullying on social networks that have a large number of participants and a variety of inputs, including conversation texts, time-variant changes and user profiles. The project is designed to change the existing cyberbullying prevention services from reactive keyword filtering to proactive social interaction pattern mining. The intended outcome will enable the early detection and warning of cyberbullying and approach open a new way to discover interaction patterns with a large number of participants over evolving and complex social networks.Read moreRead less