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Measuring soundmark temporal variations in ecoacoustic recordings

The QUT Ecoacoustics research group collects a massive amount of passively-recorded environmental audio data. The data, currently 93TB in size, constitutes more than 46 years of combined environmental monitoring. This audio data is analyzed so that ecologists may scale their observations of the environment.However, as with all data-intensive projects, the data is not perfect. One of our larger collections of data, collected from the Sturt desert, has been misdated. The result is that for large sub-sections of the data, audio …

Study level
Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Enhancing discrete choice models using insights from behavioural economics and psychology

Behavioural economics studies the impact of psychological factors on economic decisions and how these decisions deviate from those implied by classical economic theory. It merges the fields of economics and psychology to provide a better understanding of choice behaviour.When it comes to transportation individuals face long-term choices, such as car ownership and residential/work locations, and short-term choices, such as destination and departure time.Insights from behavioural economics can be applied to these choices to gain a better understanding of the conditions …

Study level
PhD, Master of Philosophy
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Responsible Analytics of Process Data

Technological advances in the field of data science empowers organisations to become ‘data-driven’ by applying new techniques to analyse large amounts of data. The potential benefits include a better understanding of business performance and more-informed decision making for business growth. However, a key roadblock to this vision is the lack of transparency surrounding the quality of data.Process mining is a specialised form of data-driven process analytics where process data, collated from the different IT systems typically available in organisations, is …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Privacy-Preserving Process Analytics

Modern organisations consider data to be their lifeblood. While the importance of data science and the potential benefits of data analytics are widely acknowledged, many people have grave concerns about irresponsible use of their data.Negative publicity surrounding large collections of personal data (incl. location, videos, pictures, emails, etc.) by corporations such as Google and Facebook and subsequent breaches have resulted in people losing trust in, and becoming more suspicious about, how their personal data is being used by such organisations.Process …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Robotic Process Automation: Research Opportunities

Recently, there has been a strong interest in industry in a specific area of automation Robotic Process Automation (RPA). This term can include robotics, software agents acting as human beings in system interactions, and process automation, workflow management systems or systems that are process-aware.RPA is a relatively new technology comprising of software agents called `bots' that mimic the manual path taken by a human through a range of computer applications when performing certain tasks in a business process. The tasks …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Big data computing in distributed or cloud environments

Big data is data with large volume, fast and dynamic generation and diversity of data formats. Their management, storage, retrieval and processing is a challenge due to these features.In distributed computing environments, the MapReduce pattern and its Haddoop and Smark implementations are widely used for big data computing. However, they are not directly suitable for many real-world applications such as some bioinformatics problems and other all-to-all comparison problems.As well as that, the efficient utilisation and scheduling of the resources for …

Study level
PhD
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

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