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rework, waste, and delays. This project tackles that challenge by developing camera-based process monitoring system that observes the weld in real time, detects and predicts anomalies as they emerge, and
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opportunities for better design. AI-driven optimisation offers a promising parallel route forward. Techniques such as Bayesian optimisation have already proven successful in related contexts, such as optimising
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application, developed through parallel funding. The project sits at the intersection of Life and Health Sciences and Software/Cyber innovation, aligning with Northern Ireland’s strategic goals for Med-Tech
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-controlled process, weaving through-thickness reinforcements directly into a component. This project will focus on the mechanical performance of tufted, 3D woven and z-pinned CFRP laminates. Key objectives
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. This PhD will use state-of-the-art natural language processing (NLP) methods to extract quality signals from European patent documents and examine how financial markets incorporate this information
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-spinning, embedding heritage within process and sustaining Donegal’s unique position in international markets. The research addresses contemporary challenges facing the wool industry synthetic competition
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managing the improvement process. This research will focus on the UK NHS. It is anticipated that a mixed methodology will be employed incorporating action research with qualitative research. Essential
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Apply and key information This project is funded by: Department for the Economy (DfE) Summary Many modern technologies — from medical brain-computer interfaces (BCIs) to automated factories — use
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% including pain, joint swelling, stiffness and hemarthrosis post-operation [1,2]. With over 103,000 primary knee replacements in the UK in 2022 alone [3] the number of yearly patients experiencing
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through the vessels and how diseases like heart blockages or artery wall damage develop. However, most current computer models used to study blood flow treat arteries as if they are rigid and motionless