Discovery Early Career Researcher Award - Grant ID: DE170100106
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
Measuring interference from prior memories using experience sampling. The project aims to better understand the causes of forgetting in recognition memory. This project will measure participants' experiences using smartphone technology for four weeks before a recognition memory experiment. Similarities between the images in the experiment and images in prior experience can be used to fully specify all interference components within a computational model of recognition memory, leading to a comple ....Measuring interference from prior memories using experience sampling. The project aims to better understand the causes of forgetting in recognition memory. This project will measure participants' experiences using smartphone technology for four weeks before a recognition memory experiment. Similarities between the images in the experiment and images in prior experience can be used to fully specify all interference components within a computational model of recognition memory, leading to a complete model of recognition memory. Better understanding the causes of forgetting in recognition memory could show how interference contributes to memory impairments in ageing, and ultimately Alzheimer’s and other clinical disorders.Read moreRead less
Investigating the role of Zona Incerta RXFP3+ cells in learning and memory. Learning and memory are fundamental to human and animal behaviour. We identified a specific population of cells in the zona incerta of the brain, where activation inhibits expression of memory, and facilitates the acquisition of new learning. Aside from our observations, nothing is currently known about the anatomy and function of these cells. This project aims to map how they connect to the rest of the brain, to observe ....Investigating the role of Zona Incerta RXFP3+ cells in learning and memory. Learning and memory are fundamental to human and animal behaviour. We identified a specific population of cells in the zona incerta of the brain, where activation inhibits expression of memory, and facilitates the acquisition of new learning. Aside from our observations, nothing is currently known about the anatomy and function of these cells. This project aims to map how they connect to the rest of the brain, to observe how these connections are recruited during learning and memory, and then to test their function experimentally. The outcomes will extend the known neural circuitry that controls learning by defining how and where these unexplored pathways fit within it; thus advancing knowledge regarding neural regulation of behaviour.
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Social engagement in Spiritualism. This project aims to investigate the sociological, anthropological and historical dimensions of Spiritualism in Australia, a small but highly influential religious movement. 19th century Spiritualist ideas about the afterlife have shaped many citizens’ beliefs that individual personality survives death in a family-centred spirit realm. Combining both sociological and anthropological approaches, the project will map the production and effect of belief on family, ....Social engagement in Spiritualism. This project aims to investigate the sociological, anthropological and historical dimensions of Spiritualism in Australia, a small but highly influential religious movement. 19th century Spiritualist ideas about the afterlife have shaped many citizens’ beliefs that individual personality survives death in a family-centred spirit realm. Combining both sociological and anthropological approaches, the project will map the production and effect of belief on family, civic participation and ethics. This project aims to give scholars a fuller, more accurate view of religious dynamics in Australia.Read moreRead less
Fast effective clustering technologies for highly dynamic massive networks. Clustering is a fundamental data mining and analysis task. In an interconnected evolving world, friendships and information flows are modelled as large dynamic networks. Structural clustering and correlation clustering are important and well-studied approaches for static networks; for evolving networks, where links appear and disappear over time, we lack efficient techniques. Anticipated outcomes are new practical cluste ....Fast effective clustering technologies for highly dynamic massive networks. Clustering is a fundamental data mining and analysis task. In an interconnected evolving world, friendships and information flows are modelled as large dynamic networks. Structural clustering and correlation clustering are important and well-studied approaches for static networks; for evolving networks, where links appear and disappear over time, we lack efficient techniques. Anticipated outcomes are new practical clustering algorithms for dynamic networks – with performance guarantees of efficiency and clustering quality – and prototype software, guiding us to pick a good clustering. Expected benefits include better understanding of spread in evolving social networks, accelerating the software testing cycle, and improved topic detection.Read moreRead less
Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require c ....Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require computational techniques that run extremely efficiently. The project expects to develop and improve approximate data structures that operate in tight resource bounds. Anticipated outcomes are improved event recognition and dramatic speedup in analysis of streams in areas such as finance, health, transport, and urban data.Read moreRead less
Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and ....Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and efficient algorithms for searching and monitoring cohesive subgraphs in big and dynamic attributed graphs from both structure and attribute perspectives. The methods, techniques, and prototype systems developed in this project can be deployed to facilitate the smart use of big graph data across the nation. Read moreRead less
Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for differen ....Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for different applications and devise efficient algorithms for searching and monitoring those cohesive groups based on different models. The methods, techniques, and evaluation systems developed in this project can be deployed to facilitate the smart use of heterogeneous information networks across the nation.Read moreRead less
Algorithms for Future-Proof Networks. This project will design algorithms to construct, augment and route on geometric graphs in the presence of obstacles. Such graphs have many real-world applications, including transport networks. This project aims to give solutions with hard guarantees on the timeliness of the delivery of the people, goods, or information being transported in these networks. Expected outcomes of this project include efficient and innovative algorithms for realistic geometric ....Algorithms for Future-Proof Networks. This project will design algorithms to construct, augment and route on geometric graphs in the presence of obstacles. Such graphs have many real-world applications, including transport networks. This project aims to give solutions with hard guarantees on the timeliness of the delivery of the people, goods, or information being transported in these networks. Expected outcomes of this project include efficient and innovative algorithms for realistic geometric graphs, which both advances the knowledge in this field of computer science and make our existing networks more reliable. This should provide significant benefits in the maintenance and utilisation of the communication and transport networks we use every day.Read moreRead less
New approaches to interactive sessional search for complex tasks. This project aims to develop new tools and techniques to improve the accuracy and speed of search and data analytics for complex information tasks. There are currently no publicly available search engines which support users engaged in complex interactive search, or that allow searchers to fully control their own data and privacy. Fundamental research advances, based on understanding real user behaviour and search needs will have ....New approaches to interactive sessional search for complex tasks. This project aims to develop new tools and techniques to improve the accuracy and speed of search and data analytics for complex information tasks. There are currently no publicly available search engines which support users engaged in complex interactive search, or that allow searchers to fully control their own data and privacy. Fundamental research advances, based on understanding real user behaviour and search needs will have an impact on important academic, industrial, and government domains, including virtual assistants, health care (clinical decision support), precision medicine, eDiscovery, crime prevention, and detailed socio-economic evaluations.Read moreRead less