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investigate the optimal methods for combining multi-satellite InSAR with a network of Kurloo GNSS devices to provide robust 3D ground motion monitoring from space. The potential benefits may include
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treated differently, and whether the current arrangements are optimal or could be improved. Documenting cumulative Adelaide Park Lands losses, over time For a student interested in local history, heritage
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inorganic AEMWEs by integrating the perovskite electrolyte with perovskite electrodes from cell fabrication to cell configuration optimization and to single cell performance. Significance The project has
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to: - Developing underwater communication systems using deep learning which are well-performing to nonlinear channels. - Establishing a deep learning architecture which is optimal for underwater acoustic
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for examining and imaging the magnetic fields from exotic conducting materials (e.g. superconductors, topological insulators), performing high bandwidth and high sensitivity vector magnetic sensing and developing
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selection of the most optimal medical therapy. Predictors of response to the current arsenal of treatment are paramount to achieve endoscopic and histologic healing, reduce disease complications including
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to understand the roles of the geometrical properties and the surface chemistry on CO2 adsorption in the developed porous carbons, to facilitate the optimized adsorbents development. Student type Future Students
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materials. Develop and optimize materials for efficient hydrogen liquefaction. Analyze data and contribute to the publication of research findings. Collaborate with a team of researchers and engineers. Join
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Efficient Data-Driven Optimization in Cooperative Control Systems with Constraints 2 Minute read This is one of two research projects studying unmanned aerial and surface vehicles (UAVs and USVs
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contributing to final layer predictions. • Objective 3: Non-convex Optimization and Local Minima -- Study the theoretical foundations and empirical behaviors of deep neural networks in the context of non-convex