Adaptive Key-value Store for Future Extreme Heterogeneous Systems. Safe, lasting storage of data, and efficient access to it, is vital for all aspects of computing, ranging from e-commerce applications, and data-management in governments. For the storage of data, persistent key-value stores are central in modern computing platforms. However, contemporary key-value stores have not been designed for emerging extreme heterogeneous computational systems with future hardware accelerators and storage ....Adaptive Key-value Store for Future Extreme Heterogeneous Systems. Safe, lasting storage of data, and efficient access to it, is vital for all aspects of computing, ranging from e-commerce applications, and data-management in governments. For the storage of data, persistent key-value stores are central in modern computing platforms. However, contemporary key-value stores have not been designed for emerging extreme heterogeneous computational systems with future hardware accelerators and storage capabilities, including graphics processor and flash-based memory. This project will devise an adaptive key-value store framework for heterogeneous systems. Our new framework will adaptively harvest the performance potential of future hardware such that applications can cope with fast-growing data sets.Read moreRead less
Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this contex ....Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this context. Expected outcome include new database technologies for data signature generation and similarity-based search, and improved location data privacy protection methods. This project should provide significant benefits to all areas where high quality spatiotemporal data fusion is essential to meaningful data analysis.Read moreRead less
Making eMaking Accessible for People with Intellectual Disabilities. This interdisciplinary research will create an evidence based eMaking program that empowers people with Intellectual Disabilities. eMaking benefits include collaborative problem solving and employment pathways; however, people with disabilities are often excluded. Through a unique, inclusive, outreach van, strategies to build accessible eMaking will be generated. Project outcomes include replicable, scalable eMaking activities ....Making eMaking Accessible for People with Intellectual Disabilities. This interdisciplinary research will create an evidence based eMaking program that empowers people with Intellectual Disabilities. eMaking benefits include collaborative problem solving and employment pathways; however, people with disabilities are often excluded. Through a unique, inclusive, outreach van, strategies to build accessible eMaking will be generated. Project outcomes include replicable, scalable eMaking activities and toolkits to facilitate Science, Technology, Engineering and Mathematics for all. Project benefits include opportunities for people with Intellectual Disability to participate in meaningful recreational or work-focused eMaking, and changing community attitudes through shared eMaking participation.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
Indigenist Archaeology: New Ways of Knowing the Past and Present. This project aims to explore how Indigenous Australian worldviews can transform archaeological practice and understandings of the past. Archaeological research practice has typically relied on Western science, theories and interpretive frameworks. As an alternative approach, we will develop a new epistemological conceptualisation for how archaeology can be practiced. Based on surveys and interviews with six Aboriginal communities ....Indigenist Archaeology: New Ways of Knowing the Past and Present. This project aims to explore how Indigenous Australian worldviews can transform archaeological practice and understandings of the past. Archaeological research practice has typically relied on Western science, theories and interpretive frameworks. As an alternative approach, we will develop a new epistemological conceptualisation for how archaeology can be practiced. Based on surveys and interviews with six Aboriginal communities in the Northern Territory and South Australia, and using Indigenous theories and concepts, the project will identify and explore how Aboriginal ways of knowing (epistemology), being (ontology) and doing (axiology) can be integrated into a new model for archaeological research that we call “Indigenist Archaeology”.Read moreRead less
Intergenerational cultural transfer of Indigenous knowledges. Aboriginal cultural systems hold knowledge of national and international significance for Aboriginal wellbeing and addressing climate change, food insecurity, water scarcity and species loss. However, the continuity and integrity of these knowledges is of considerable concern to Aboriginal people, due to disruptions to Aboriginal lifeways. This Aboriginal environmental humanities research will investigate, describe and compare the tra ....Intergenerational cultural transfer of Indigenous knowledges. Aboriginal cultural systems hold knowledge of national and international significance for Aboriginal wellbeing and addressing climate change, food insecurity, water scarcity and species loss. However, the continuity and integrity of these knowledges is of considerable concern to Aboriginal people, due to disruptions to Aboriginal lifeways. This Aboriginal environmental humanities research will investigate, describe and compare the transfer of knowledge in a Kimberley and a southwest region of Western Australia to understand how cultural values, knowledge and practices can persist despite on-going colonial interruptions. Outcomes will contribute to Aboriginal wellbeing, enhance biodiversity and advance water communication. Read moreRead less
Building An Indigenist Health Humanities Collective. This proposal aims to develop Indigenist Health Humanities as a new and innovative field of inquiry, building an intellectual collective capable of bridging the knowledge gap that hinders current efforts to close the gap in Indigenous health inequality. Bringing together health and the humanities through the particularity of Indigenous scholarship, a deeper understanding of the human experience of health will be developed alongside a greater u ....Building An Indigenist Health Humanities Collective. This proposal aims to develop Indigenist Health Humanities as a new and innovative field of inquiry, building an intellectual collective capable of bridging the knowledge gap that hinders current efforts to close the gap in Indigenous health inequality. Bringing together health and the humanities through the particularity of Indigenous scholarship, a deeper understanding of the human experience of health will be developed alongside a greater understanding of the enablers to building a transdisciplinary collective of Indigenous health researchers. The potential benefits include a more sustainable, relational and ethical approach to advancing new knowledge, advancing research careers and advancing health outcomes for Indigenous people. Read moreRead less
Developing Adversary-Aware Classifiers for Android Malware Detection. Smartphones have become increasingly ubiquitous in people’s everyday life. However, it was reported that one in every five Android applications were actually malware, considering that Android has taken 88% market share of mobile phones. As an effective technique, machine learning has been widely adopted to detect Android malware. However, recent work suggests that deliberately-crafted malware makes machine learning ineffective ....Developing Adversary-Aware Classifiers for Android Malware Detection. Smartphones have become increasingly ubiquitous in people’s everyday life. However, it was reported that one in every five Android applications were actually malware, considering that Android has taken 88% market share of mobile phones. As an effective technique, machine learning has been widely adopted to detect Android malware. However, recent work suggests that deliberately-crafted malware makes machine learning ineffective. In this project, we propose to develop a series of new techniques, such as 1) Android contextual analysis, 2) wrapper-based hill climbing algorithm, and 3) ensemble learning, to solve this problem. The outcomes will help Australia gain cutting edge technologies in adversarial machine learning and mobile security.Read moreRead less
Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a sys ....Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a system that is highly efficient, accurate and corrupted-data-tolerant classification solutions for individual stream data as well as multiple stream data. The expected benefits will be far-ranging and adaptable to many domains, such as smart home, medical and healthcare, transportation and manufacturing. Read moreRead less
Effective and Efficient Situation Awareness in Big Social Media Data . Crisis management services using traditional methods like phone calls can be easily delayed due to limited communication ability in the disaster area. This project aims to help users make smart decision in critical situations by using big social media data to detect complex social events, receive recommendations, and observe event summaries. We will invent advanced social data models, efficient indices and query techniques fo ....Effective and Efficient Situation Awareness in Big Social Media Data . Crisis management services using traditional methods like phone calls can be easily delayed due to limited communication ability in the disaster area. This project aims to help users make smart decision in critical situations by using big social media data to detect complex social events, receive recommendations, and observe event summaries. We will invent advanced social data models, efficient indices and query techniques for situation awareness in big media. We expect to develop a system to evaluate the proposed situation awareness framework. The outcomes of the project will benefit social media analysis and big data fields. It will also improve the government services by enabling the real time situation awareness in crisis.Read moreRead less