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Found 5 matching student topics

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Process-data governance patterns

Data is recognised a strategic asset for organisations. There is a growing need to manage the voluminous data an organisation is exposed to in order to use it for decision-making.Of particular significance is process data, which consists of information about the execution of processes. Such information is used to uncover behaviour of processes within an organisation. This brings forth the significance of data governance. Data governance is the exercise of control and authority over management of data. Despite its significance, …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems

Understanding local government artificial intelligence policy landscape

Artificial intelligence (AI) is driving transformation across all areas of society today. An umbrella term encompassing a range of technologies both sophisticated and simple that are used to make predictions, inferences, recommendations, or decisions with data. AI is used in many products and services that people use, interact with, or are impacted by every day. It already in place of local government and assisting government officials in providing services effectively and conduct their activities more efficiently to the public. The …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Engineering
School
School of Architecture and Built Environment

Praeclarus process-data quality framework

Praeclarus is an open-source software framework that aims to facilitate data pre-processing for process mining. Process mining is specialised data mining focusing on process-data. It is of high interest to industry, with the market doubling every two years (e.g., increasing from $550M in 2020 to $1B in 2022). This market increase has meant that big companies like Microsoft, SAP, and IBM are acquiring process mining vendors such is Minit, Signavio, and myInvenio.Recent process mining surveys show that more than 60% …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Information Systems

A physics-guided deep learning-based framework for computational mechanics

Computational mechanics is an essential discipline that uses numerical schemes to approximately solve mechanics problems. It provides engineers with precious knowledge about the structures to identify the at-risk area and further guide the structural design and optimisation process.Deep learning (DL) is an important branch of machine learning (ML). The great success of the DL techniques has been witnessed in the past decade. Now, various fields have benefited from the DL techniques, including computer vision, financial prediction, and bioinformatics. Therefore, it …

Study level
Vacation research experience scheme
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering

A new physics informed machine learning framework for structural optimisation design of the biomedical devices

The machine learning based computer modelling and simulation for engineering and science is a new era. The optimisation analysis is widely used in the design of structures.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Mechanical, Medical and Process Engineering
Research centre(s)
Centre for Biomedical Technologies
Centre for Biomedical Technologies

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