Anticipatory, Adaptive, and Scalable Mobility Infrastructure for On-board Information Access. The recent advances in wireless technologies are offering new opportunities for ubiquitous information access in on-board mobile computing. Realising an effective on-board mobile computing infrastructure poses significant technical challenges at both application and data transport layers. Our approach features the integration of techniques from satellite communications, anticipatory transport protocols ....Anticipatory, Adaptive, and Scalable Mobility Infrastructure for On-board Information Access. The recent advances in wireless technologies are offering new opportunities for ubiquitous information access in on-board mobile computing. Realising an effective on-board mobile computing infrastructure poses significant technical challenges at both application and data transport layers. Our approach features the integration of techniques from satellite communications, anticipatory transport protocols, and personalised data management systems. The final outcome will be generic techniques and concepts for effective and efficient on-board access to global information sources and services (e.g., weather information, stock quotes, and infotainment). These concepts and techniques will have wider application scope, such as aeronautical, maritime and terrestrial public transport systems.Read moreRead less
Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended ....Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.Read moreRead less
Distributed Data Processing for Wireless Sensor Networks. This project falls within the national research priorities of Frontier Technologies for building and transforming Australian Industries, and will provide Australian companies with state-of-the-art technology in wireless sensor networks (WSN). Australia's priorities are mainly in sustainable environment, health maintenance, and home-land security. Any application in these priority areas that uses our system will have less maintenance costs ....Distributed Data Processing for Wireless Sensor Networks. This project falls within the national research priorities of Frontier Technologies for building and transforming Australian Industries, and will provide Australian companies with state-of-the-art technology in wireless sensor networks (WSN). Australia's priorities are mainly in sustainable environment, health maintenance, and home-land security. Any application in these priority areas that uses our system will have less maintenance costs and a significantly longer lifetime.
This project will generate numerous articles in first-class journals and conferences and will contribute to the strength of Australian Research in sensor technologies and ICT. Read moreRead less
Efficient Strategies for Mining Negative Association Rules. Negative association rules (NAR) catch mutually-exclusive correlations
among items. They play important roles just as traditional association
rules (TAR) do. For example, in stock market surveillance based on alert logs, NARs detect which alerts are false. There are essential differences between mining TARs and NARs because NARs are hidden in infrequent itemsets. This research will develop efficient strategies for mining NARs in datab ....Efficient Strategies for Mining Negative Association Rules. Negative association rules (NAR) catch mutually-exclusive correlations
among items. They play important roles just as traditional association
rules (TAR) do. For example, in stock market surveillance based on alert logs, NARs detect which alerts are false. There are essential differences between mining TARs and NARs because NARs are hidden in infrequent itemsets. This research will develop efficient strategies for mining NARs in databases. These strategies are expected to be about ten times faster than existing ones. This project will deliver database-independent and high-performance mining algorithms for decision-making. The results can benefit Australian marketing and financial companies as well as health and security departments for smart information use.Read moreRead less
Multiple Data Source Discovery: Group Interaction Approach. This project will develop new technology and theory to identify and evaluate incomplete data. It will deliver a high-performance group-interaction based global pattern discovery system that enables decision-makers (like doctors) to access valuable implicit information that is contained in their data but not currently accessible. Mining group interactions will greatly extend the scope of pattern discovery and new product evaluation. The ....Multiple Data Source Discovery: Group Interaction Approach. This project will develop new technology and theory to identify and evaluate incomplete data. It will deliver a high-performance group-interaction based global pattern discovery system that enables decision-makers (like doctors) to access valuable implicit information that is contained in their data but not currently accessible. Mining group interactions will greatly extend the scope of pattern discovery and new product evaluation. The outcomes of the project will lead to better diagnostic decisions and will lead to increased efficiency in Australian Industries.Read moreRead less
Effective Techniques and Methodologies for Multi-Database Mining. This project develops a high-performance multi-database mining system. This project is significant because (1) it is imperative due to a great deal of multi-databases widely used in organizations; (2) it is difficult due to essential differences between mono- and multi-databases; (3) existing multi-database mining techniques are inadequate; and (4) the new mining strategies in this project can make a vast improvement of the abilit ....Effective Techniques and Methodologies for Multi-Database Mining. This project develops a high-performance multi-database mining system. This project is significant because (1) it is imperative due to a great deal of multi-databases widely used in organizations; (2) it is difficult due to essential differences between mono- and multi-databases; (3) existing multi-database mining techniques are inadequate; and (4) the new mining strategies in this project can make a vast improvement of the ability and performance of multi-database mining systems. The expected outcomes are: an application-independent database classification, a local instance analysis and a prototype system. These proposed techniques are innovative, effective and efficient in identifying novel patterns from multi-databases.Read moreRead less
Ontology-Based Group Pattern Discovery Systems for Mining Multiple Data Sources. This project will aim at the frontier technologies development for practical techniques in the context of real multiple-data-source mining systems, including stock data and e-business data analysis. It will bring Australian individuals and organizations (i) high quality information from multiple data sources and (ii) automatically pattern discovery systems for tackling the multiple data source problem. This will lea ....Ontology-Based Group Pattern Discovery Systems for Mining Multiple Data Sources. This project will aim at the frontier technologies development for practical techniques in the context of real multiple-data-source mining systems, including stock data and e-business data analysis. It will bring Australian individuals and organizations (i) high quality information from multiple data sources and (ii) automatically pattern discovery systems for tackling the multiple data source problem. This will lead to greatly enhance the international competition of Australian companies and significantly reduce investing risks. Read moreRead less
Mining multi-typed and dynamic graphs. Large volumes of data collected nowadays from real-world applications are often represented as graphs. The nodes and the edges of such graphs represent different types of entities and interactions, and they have time information. This project will develop algorithms that mine efficiently such multi-typed and dynamic graphs.
Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling rese ....Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling research and practical solutions for this important cloud and big data research area; benefiting key big data application areas on the cloud, such as hospitals, insurance companies and government information services; and helping to maintain Australia at the forefront of cloud and big data research with innovative industry applications.Read moreRead less
From Data to Artefact: a Key Ingredient in Service Interoperation. Supporting service interoperation in the e-Business environment is crucial in automating business transactions across organisation boundaries. If no proper mechanism is in place, business delays, failures, and serious disputes can occur. This project will explore new avenues to this long-standing and challenging problem by providing an artefact framework to model and manage business collaboration. Given this project's unique pers ....From Data to Artefact: a Key Ingredient in Service Interoperation. Supporting service interoperation in the e-Business environment is crucial in automating business transactions across organisation boundaries. If no proper mechanism is in place, business delays, failures, and serious disputes can occur. This project will explore new avenues to this long-standing and challenging problem by providing an artefact framework to model and manage business collaboration. Given this project's unique perspective and approaches that are directly applicable to existing enterprise systems, there is a strong potential for its results to lead to a new generation of e-Business design and management, advance the knowledge base of the discipline and yield high returns to the Australian service society and IT industry.Read moreRead less