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Displaying 61–72 of 565 results

Fairy circle landscapes formed in the Great Barrier Reef…but how?

Destabilising feedbacks between ecology and the local physical environment yield spatial pattern formation in various contexts throughout nature. For example, these feedbacks can lead to ring-shaped pattern formation in the spatial distribution of submerged aquatic plants. Recently, unusual crater-like structures have been identified in a large area of the Great Barrier Reef where the algae genus Halimeda constructs mounds called 'bioherms'.This project seeks to use partial differential equation models of the spatial growth of Halimeda to identify whether its long-term …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Modelling and managing uncertain Antarctic species networks

Antarctic ecosystems are complex, and data is limited since it is expensive to collect. Species interact in food webs which can be modelled as mathematical networks. The relationships between species are not always known, or we might know they interact but not how strongly. Noisy (or imperfect) data can be used to model these species interactions to give more certainty about how the ecosystem works as a whole – although the worse the data is, the less information it contributes. …

Study level
Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Adversarial attacks to machine learning based models in cybersecurity

Modern Intrusion Detection Systems (IDSs) rely on machine learning for detecting and defending cyber-attacks in information technology (IT) networks. However, the introduction of such systems has introduced an additional attack dimension; the trained IDS models may also be subject to attacks.The act of deploying attacks towards machine learning based systems is known as Adversarial Machine Learning (AML) [1]. The aim is to exploit the weaknesses of the pretrained model which has “blind spots” between data points it has seen during …

Study level
Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science

Designing efficient sampling algorithms for ensemble ecosystem modelling

This project seeks to use a combination of matrix algebra and advanced Monte Carlo methods for rare-event simulation to identify efficient algorithms for ensemble ecosystem modelling in large ecosystems. This project has the potential to significantly change the methods that researchers useto investigate complex ecosystems for the purposes of environmental management and future predictions.Ensemble ecosystem modelling (EEM) is a novel and increasingly popular method for generating predictions of future species abundance in complex ecosystems represented by generalisations of the Lotka-Volterra …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Designing a digital health platform to manage health and well-being

An individual's health status is very important to personal well-being and plays a significant role at workplace, home, and school/university. We do not worry or think too much about our health value until we experience bad consequences. Individuals will make an excellent contribution to schools, industries, and workplace provided that they have a good quality of life. With the advances in wearable technology, we can leverage their utility to monitor and manage our health.Emerging smart devices have potential benefits for …

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science

Optimal ecosystem management in rapidly changing systems

Delays in acting in collapsing ecosystems can be catastrophic. With every passing year, the chances that the ecosystem has progressed past some point of no return increases. Yet the research and development needed to develop a new technology can take a long time. Balance between these two dynamic processes is needed to determine the optimal length and effort for developing new technologies. This project will develop a method for finding the optimal schedule for developing technological readiness, social acceptability, a …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Hierarchical visualisation of large social networks

Networks have been extensively used to capture social interactions, by representing individuals as nodes and their relationships as edges.Such networks have been used to model the spread of epidemics. A few nodes are 'infected', and over time they gradually infect their neighbours on the network, who in turn infect their neighbours, etc. This type of model can then be used to simulate different intervention strategies aimed at containing outbreaks.However, an important limitation is the difficulty to visualise these networks when …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Mathematically optimising value of information for biodiversity management

When planning environmental management, data are only valuable if they lead to improved outcomes. As new monitoring technologies and approaches are developed, it is critical that they are used optimally to focus on the most important information gaps.Monitoring technologies should only be adopted if they can deliver improved management utility, and new data should be rapidly gathered in locations where early information could offer warning signals of future ecosystem change. Mathematical and statistical approaches to assessing the value of new …

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Digital inclusion and participation

Working in partnership with industry, government and community organisations, the Digital Inclusion and Participation research program within QUT's Digital Media Research Centre uses innovative digital ethnographic and co-design methods to understand, intervene, and advocate for digital access and literacy as vital elements of social inclusion.We help equip citizens and consumers with the knowledge and skills to confidently, effectively and ethically navigate the increasingly complex digital media environment; and we deliver actionable new knowledge of the structural conditions and circumstances that …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Communication
Research centre(s)
Digital Media Research Centre

Optimal conservation management in uncertain Antarctic environments

Species and ecosystems in Antarctica are threatened. Optimal biodiversity conservation is an interdisciplinary field combining mathematical modelling and optimisation with ecology and conservation. We can use mathematics to understand the system, model how management actions might impact it, and then optimise which actions should be used. For example, we can explore where protected areas should be placed, how species should be managed, or how tourist impacts should be reduced. However, the complexities of conservation in Antarctica necessitate the application of …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Spatial statistics for microchemical maps of rocks

Synchrotron X-ray Fluorescence Microscopy (XFM) provides exceptionally detailed, large multi-element microchemical maps of thin rock specimens. Together with conventional optical and electron-beam imaging methods, XFM maps permit novel insights into coupled mass transfer processes at the grain scale controlling important Earth processes such as earthquake formation, volcanism, reactive fluid flow, and CO2-sequestration.However, to this date, most scientific work using XFM is mostly qualitative and does not make full use of the statistical information that can be obtained from the data. …

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Earth and Atmospheric Sciences

Exercise in extreme environments

A number of projects are currently being undertaken by the E3 Lab.These projects investigate the influence of extreme environmental conditions on exercise and work performance.The E3 research laboratory is well equipped to answer how the environment affects human thermoregulatory performance.This project is based at QUT Kelvin Grove campus.

Study level
Vacation research experience scheme
Faculty
Faculty of Health
School
School of Exercise and Nutrition Sciences

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