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a digital format. Computer visions techniques have been recently developed for structural health monitoring of civil structures, including vibration displacement measurements, crack detection and
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, leveraging existing literature and data from controlled experiments. The model will consider multiple photosynthesis parameters to predict microalgae growth. It will offer specific design criteria and
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mechanisms involved in the leaching of copper concentrate by glycine solutions. • Optimize process parameters such as temperature, pH, glycine concentration, and particle size to maximize copper
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an ARC Linkage Project focused on developing an autonomous system for detecting and quantifying structural damage in infrastructures (e.g., bridges, grain silos) using computer vision, digital twins, and
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characterization for parameters like particle size, surface charge, drug loading capacity, and in vitro release profile. The second stage involves in vitro cell culture studies using GBM cell lines (e.g., U87-MG
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distribution, and kinetic parameters for step reactions. Revealing catalyst electronic structures and reaction energy barriers using ab initio calculations. Significance To date, over 70% of electricity in
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children. Mechanistic modelling of disease transmission involves the use of computer code to represent the epidemic dynamics of infectious disease spread within the community. This allows modellers
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to estimate their age, but if resorption occurs, it would lead to underestimation and inadequate conservation efforts. Additionally, investigating the role of mononuclear clastic cells in resorption during
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the area of structural health monitoring of civil engineering structures on an Australian Research Council Early Career Industry Fellowship project titled, 'Transforming Smart Bridge Monitoring by Computer
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data