The Development of Creative Thinking Ability in TAFE Design Students. The aim is to develop an instructional framework as a conceptual basis for instruction aimed at TAFE design student use of imagery in creative thinking. The research addresses the challenges of recent post-compulsory education initiatives, which include a more specific focus on the development of creative problem-solving skills, but provide little guidance on instructional strategies. The research will synthesise the framewo ....The Development of Creative Thinking Ability in TAFE Design Students. The aim is to develop an instructional framework as a conceptual basis for instruction aimed at TAFE design student use of imagery in creative thinking. The research addresses the challenges of recent post-compulsory education initiatives, which include a more specific focus on the development of creative problem-solving skills, but provide little guidance on instructional strategies. The research will synthesise the framework from theories about cognitive processes, creative problem-solving and the use of mental imagery; and the results of an imagery training program and creative problem-solving interventions. The outcome will be an instructional framework for guiding the development of student creative thinking in design-based courses in TAFE.Read moreRead less
Faster, cheaper, safer: how to accelerate rail driver training and avert the looming skills shortage. The Australian rail industry is growing rapidly and needs to double the number of drivers trained in order to meet demand. This project will bring together Australia's leading hi-tech simulator company and Australia's leading rail human factors research team to 'reinvent' driver training technologies and techniques for the 21st century.
Discovery Early Career Researcher Award - Grant ID: DE140100772
Funder
Australian Research Council
Funding Amount
$393,414.00
Summary
Response Time Constraints on Category Learning. Theories of associative learning and decision-making are among the most mathematically well developed in psychology. However, theories of learning do not account for the time course of decision-making, and theories of decision-making do not account for how decision-relevant information is learned. This project will develop an integrated theoretical framework linking core principles of associative learning theories with sequential sampling models of ....Response Time Constraints on Category Learning. Theories of associative learning and decision-making are among the most mathematically well developed in psychology. However, theories of learning do not account for the time course of decision-making, and theories of decision-making do not account for how decision-relevant information is learned. This project will develop an integrated theoretical framework linking core principles of associative learning theories with sequential sampling models of the time course of decision-making. The new theory will provide a quantitative account of how incremental associative learning processes drive changes in cognitive representations that, in turn, account for known changes in the time course of decision-making.Read moreRead less
The Material Science of Biomimetic Soft Network Composites. Nature combines stiff and strong collagen fibres intertwined within a weak polymer matrix of proteoglycans into soft tissues with outstanding mechanical durability and biological properties. We converge a biomimetic design strategy inspired in the architecture of natural soft tissues and a novel additive manufacturing technology termed melt electrowriting (MEW) to manufacture advanced biomimetic soft network composites (BSNC). The SNCs ....The Material Science of Biomimetic Soft Network Composites. Nature combines stiff and strong collagen fibres intertwined within a weak polymer matrix of proteoglycans into soft tissues with outstanding mechanical durability and biological properties. We converge a biomimetic design strategy inspired in the architecture of natural soft tissues and a novel additive manufacturing technology termed melt electrowriting (MEW) to manufacture advanced biomimetic soft network composites (BSNC). The SNCs are composed of a weak polymer matrix and a MEW reinforcing fibrous phase printed at the nanometre scale, containing patterns mimicking the natural tissue architectures. Advanced computational tools are applied for the rational design of the SNC while reducing costs and times associated to experimental work.Read moreRead less
Evaluating recurrence as a measure of change in interpersonal dynamics. This project aims to develop an automated conversation analysis system to quantify how communication changes over extended periods of time. It is innovative in proposing to extend the theory and methods of recurrence analysis (a dynamical systems technique) to interacting modalities combining text, audio and video, and to longitudinal analyses. The project is significant in being the first to aim to measure communication dyn ....Evaluating recurrence as a measure of change in interpersonal dynamics. This project aims to develop an automated conversation analysis system to quantify how communication changes over extended periods of time. It is innovative in proposing to extend the theory and methods of recurrence analysis (a dynamical systems technique) to interacting modalities combining text, audio and video, and to longitudinal analyses. The project is significant in being the first to aim to measure communication dynamics over time in the fields of education, health, public discourse and science. It is expected to result in new theories and methods for recurrence analysis validated using real-world data; and to enable new technologies for evaluating professional communication training and communication changes resulting from education or disease progression.Read moreRead less
Protein structure prediction by deep long-range learning. This project aims to address the challenging problem of protein structure prediction by developing deep long-range learning methods. The project expects to advance protein structure prediction by capturing the long-range interactions through whole sequence learning, rather than short window-based learning. Expected outcomes include next-generation machine-learning techniques for predicting one, two and three-dimensional protein structures ....Protein structure prediction by deep long-range learning. This project aims to address the challenging problem of protein structure prediction by developing deep long-range learning methods. The project expects to advance protein structure prediction by capturing the long-range interactions through whole sequence learning, rather than short window-based learning. Expected outcomes include next-generation machine-learning techniques for predicting one, two and three-dimensional protein structures from their sequences. The expected outcomes should provide significant benefits by computationally determining protein structures beyond homologous sequences, and enabling structure-based drug discovery to disease-causing protein targets previously inaccessible to biotech and pharmaceutical companies.Read moreRead less
Planet Formation at Solar System Scales with the James Webb Space Telescope. Planetary systems like our own form within vast disks of primordial gas and dust around newborn stars. This project will observe such disks spanning a range of ages with the James Webb Space Telescope to reveal the detailed in-situ physics of planet-forming disks themselves. We will deliver the sharpest-ever infrared images in astronomy, exploiting the only Australian-designed instrument on the spacecraft: the Aperture ....Planet Formation at Solar System Scales with the James Webb Space Telescope. Planetary systems like our own form within vast disks of primordial gas and dust around newborn stars. This project will observe such disks spanning a range of ages with the James Webb Space Telescope to reveal the detailed in-situ physics of planet-forming disks themselves. We will deliver the sharpest-ever infrared images in astronomy, exploiting the only Australian-designed instrument on the spacecraft: the Aperture Masking Interferometer. This yields new physics for actively growing protoplanets, carved rings and gaps in disks, and gravitationally sculpted patterns of leftover cometary debris. Confronting state-of-the-art models with these data will immediately yield profound insights into planetary system formation, including our own.Read moreRead less
Combining modal logics for dynamic and multi-agent systems. Modern computer software systems are required to operate in complex dynamic environments and to handle functioning of highly sensitive (security and safety-critical) organizations in government and commerce. Typical applications include air-traffic control systems, telecommunication networks, and banking systems. To ensure robustness, computationally predictable behaviour and trustworthiness of these systems, their designs and implement ....Combining modal logics for dynamic and multi-agent systems. Modern computer software systems are required to operate in complex dynamic environments and to handle functioning of highly sensitive (security and safety-critical) organizations in government and commerce. Typical applications include air-traffic control systems, telecommunication networks, and banking systems. To ensure robustness, computationally predictable behaviour and trustworthiness of these systems, their designs and implementations must be formally well grounded. This is an important but difficult challenge. This project will systematically develop a framework by combining modal-logics to adequately capture and reason about temporal, epistemic and social aspects of dynamic and multi-agent systems. The combined logics would be evaluated on practical applications.
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Discovery Early Career Researcher Award - Grant ID: DE240100816
Funder
Australian Research Council
Funding Amount
$444,000.00
Summary
Probing dark energy with the largest 3D Map of the Universe. Dark Energy is one of the most profound mysteries of modern physics. It makes up about 70 percent of the Universe, but no compelling theory can explain its nature. This project aims to measure the properties of Dark Energy with unprecedented accuracy: an order of magnitude better than the state of the art. It aims to accomplish this by extracting information from the largest 3D map of the cosmos, built with the optical spectra of 35 mi ....Probing dark energy with the largest 3D Map of the Universe. Dark Energy is one of the most profound mysteries of modern physics. It makes up about 70 percent of the Universe, but no compelling theory can explain its nature. This project aims to measure the properties of Dark Energy with unprecedented accuracy: an order of magnitude better than the state of the art. It aims to accomplish this by extracting information from the largest 3D map of the cosmos, built with the optical spectra of 35 million galaxies, observed by the Dark Energy Spectroscopic Instrument. This project will foster Australia's historic leadership and investments in galaxy surveys via unique international partnerships, and produce cutting-edge tools for big data analyses with important applications in a wide range of industries.Read moreRead less