Design automation for secure, reliable and energy efficient embedded processors. This project seeks to create a methodology to design and generate processors which are both secure, reliable and energy efficient for deployment in Internet of Things (IoT) systems, which require little on-going maintenance. In such systems, both security and reliability are paramount, particularly in medical devices, control devices in critical machinery, financial transactions and automotive electronics. The proje ....Design automation for secure, reliable and energy efficient embedded processors. This project seeks to create a methodology to design and generate processors which are both secure, reliable and energy efficient for deployment in Internet of Things (IoT) systems, which require little on-going maintenance. In such systems, both security and reliability are paramount, particularly in medical devices, control devices in critical machinery, financial transactions and automotive electronics. The project will use an open RISC-V processor which is sufficiently flexible to function as a base processor, with a myriad of tools such as compilers and debuggers available. Reliable computing machinery will enable systems to work in hostile environments and be functionally correct for longer.Read moreRead less
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