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In practice, most operational activity-based models have focused on single-day analyses. This common simplifying assumption significantly limits the models' behavioural realism, as they cannot adequately capture the dynamics and processes involved in the s ...
Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...
Intelligent Tutoring Systems (ITS) enhance personalized learning by predicting student answers to provide immediate and customized instruction. However, recent research has primarily focused on the correctness of the answer rather than the student's perfor ...
2024
Keeping track of Internet latency is a classic measurement problem. Open measurement platforms like RIPE Atlas are a great solution, but they also face challenges: preventing network overload that may result from uncontrolled active measurements, and maint ...
2023
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The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...
COPERNICUS GESELLSCHAFT MBH2023
This thesis demonstrates that it is feasible for systems code to expose a latency interface that describes its latency and related side effects for all inputs, just like the code's semantic interface describes its functionality and related side effects.Sem ...
In this thesis we will present and analyze randomized algorithms for numerical linear algebra problems. An important theme in this thesis is randomized low-rank approximation. In particular, we will study randomized low-rank approximation of matrix functio ...
Cardiac digital twins provide a physics and physiology informed framework to deliver personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs. Artificial Intelligence-b ...
We discover alignments of views between interest groups (lobbies) and members of the European Parliament (MEPs) by automatically analyzing their texts. Specifically, we do so by collecting novel datasets of lobbies’ position papers and MEPs’ speeches, and ...
We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, elimina ...