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Catalani, Giovanni (author)
Advancements in aircraft performance require increasingly complex design processes and tools. Simulating the unsteady non-linear aerodynamic interaction between a maneuvering aircraft and the surrounding flowfield poses serious challenges. High-Fidelity Computational Fluid Dynamics (CFD) methods, based on the numerical solution of the Navier...
master thesis 2022
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van Steijn, Jeroen (author)
In this work, it is investigated whether the predict+optimize framework could be utilized for combinatorial optimization problems with a linear objective that have uncertainty in the constraint parameters, such that it outperforms prediction-error-based training. To this end, a predict+optimize formulation of the 0-1 knapsack problem is used,...
master thesis 2022
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Pollack, Justin (author)
Nowadays, machine learning (ML) methods rapidly evolve for their use in model-based control applications. Model-based control requires an accurate model description of the dynamical system to reassure the performance of the controller. Conventionally, this model description is retrieved from first-principles modelling which can be problematic if...
master thesis 2022
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Aboueimehrizi, Maryamsadat (author)
Early design choices in building shape and fenestration significantly influ- ence the yearly daylight performance of office buildings. Annual daylight performance must be analyzed at the conceptual design stage to support building form and fenestration design decisions. However, the simulation modeling and daylight calculations necessary for the...
master thesis 2022
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Hoogeveen, Sylle (author)
The increase in complexity of mathematical models in an attempt to approximate reality and desire to have near real-time results have emphasized the need for fast numerical simulations. Especially in areas where classic numerical methods struggle to produce valid solutions in reasonable computational time due to their<br/>complex behaviour on...
master thesis 2022
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de Boer, Jurrian (author)
Recent advancements in quantification of repair outcomes of CRISPR-Cas9 mediated double-stranded DNA breaks (DSBs) have allowed for the use of machine learning for predicting the frequencies of these repair outcomes. Local DNA sequence context influences the frequencies of mutations that arise when DNA gets repaired after it is targeted by...
master thesis 2022
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Sitaldin, Dewwret (author)
In the open world, machine learning (ML) models can encounter a multitude of unknown or novel classes. In a surveillance, safety, or security use case, unknown samples can pose potential threats that are hard to detect since those samples have never been trained on. At the same time, most of the unknowns that will be encountered by a...
master thesis 2022
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de Brouchoven de Bergeyck, Aymar (author)
Vehicle routing problems have been studied for more than 50 years, and their in- terest has never been higher. It is partly due to their significant economic impact. Decreasing the traveling time, certainly for big organizations, can save costs in the range of millions of dollars and increase their service quality. Moreover, the wide variety of...
master thesis 2022
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van Haaften, Myrthe (author)
Many machine learning models have been developed to aid in the diagnosis of dementia, to predict dementia risk and to determine cognitive performance. While it is well known that vascular pathology is a critical contributing factor to dementia, cerebral small vessel disease is often not addressed by these methods, possibly causing impeded...
master thesis 2022
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Groot Beumer, Morris (author)
Recent advancements in causal inference and machine learning research have brought forward methods to estimate effects of interventions from observational data. The augmented inverse probability weighted (AIPW) estimator is such a method, which can be used to obtain estimates of potential outcomes. Potential outcomes are defined as a...
master thesis 2022
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van 't Sant, Sikko (author)
Metamaterials derive their properties from microstructure rather than from bulk material properties. This opens property spaces that are difficult, or impossible, to access with traditional methods. However, exploring this vast design space remains challenging because classical techniques can be computationally inefficient. Recent years has seen...
master thesis 2022
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Landré, Daniël (author)
The rapid adoption of e-bikes as an alternative mode of transportation to automobiles gives rise to new methods of safety regulations for cyclists. Modern e-bikes feature Internet of Things (IoT) modules capable of collecting and sending cycling data that can be used for traffic safety analysis. This study explores the potential of using cycling...
master thesis 2022
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Georgiou, Thomas (author)
Electrical faults in the distribution network can lead to interruptions in the power supply of the customers. Therefore penalties are applied to the DSOs if they overcome the benchmark set based on all the DSOs reliability performance. Hence, the fast restoration of the power supply is crucial for the grid operator in order for the operational...
master thesis 2022
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El Ouasgiri, Mohammed (author)
In this thesis, we use data science / statistical techniques to better understand the energy consumption behind a powder drying facility located in Zwolle, as part of Abbott's initiative to better manage its energy consumption. As powder drying is by far the facility's most energy intensive process, this project therefore focuses exclusively on...
master thesis 2022
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Marang, Ruben (author)
Machine learning models are increasingly being used within software engineering for their predictions. Research shows that these models’ performance is increasing with new research. This thesis focuses on models for method name prediction, for which the goal is to have a model that can accurately predict method names. With this thesis, we could...
master thesis 2022
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Kirchner, Joris (author)
Neural network is an active research field which involves many different (unsolved) issues, for example, different types of configuration of the network architectures, training strategies, etc. Amongst these active issues, the choice of loss (or cost) functions plays an important role in how a neural network model is to be optimized (trained)...
bachelor thesis 2022
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Engels, Ayla (author)
Activity classification in sports is a powerful tool for athlete monitoring, enhancing performance and injury prevention. In handball, detection and classification of throws during a practice or a (practice) match has not been done. Therefore, the aim of this study is to use machine learning algorithms to detect handball throws and to classify...
master thesis 2022
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Star, Quinten (author)
Perforated monopiles show promise in providing a better alternative to the commonly used jacket-like substructures used in intermediate water depths in the range of 30 to 120 m. By introducing perforations near the vicinity of the splash zone the wave loads on the monopile can be mitigated and the fatigue damage reduced, which is the main...
master thesis 2022
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Beens, Tim (author)
For the future demand prediction of identification documents the National Office for Identity Data is interested in a new prediction model based on machine learning techniques. Due to the existence of many different machine learning algorithms and the often competing model requirements regarding model performance and explainability it can be...
master thesis 2022
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Habib, Benjamin (author)
Whereas in the past, Distribution Systems played a passive role in connecting customers to electricity, Distribution System Operators (DSOs) will have to take in the future a more active role in monitoring and regulating the network to deal with the new behaviors and dynamics of the system brought by the energy transition. State Estimation, a...
master thesis 2022
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