Searched for: subject%3A%22Machine%255C+learning%22
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Slokom, M. (author)
In the field of machine learning (ML), the goal is to leverage algorithmic models to generate predictions, transforming raw input data into valuable insights. However, the ML pipeline, consisting of input data, models, and output data, is susceptible to various vulnerabilities and attacks. These attacks include re-identification, attribute...
doctoral thesis 2024
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Dekhovich, A. (author)
Deep learning models have made enormous strides over the past decade. However, they still have some disadvantages when dealing with changing data streams. One of these flaws is the phenomenon called catastrophic forgetting. It occurs when a model learns multiple tasks sequentially, having access only to the data of the current task. However,...
doctoral thesis 2024
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Schijvenaars, Sofie (author)
Globally, coastal communities face increasing risks from climate-related hazards such as flooding, shoreline erosion, and salt intrusion. These hazards pose threats to both people and their environment, with extreme sea level events increasing these risks. Satellite altimetry allows for global observation of the sea level, reaching remote...
master thesis 2024
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de Vries, Floris (author)
The present study focuses on utilizing the Bayesian Optimization Machine Learning algorithm for the weight optimization of a shear web of given size (a x b), material properties, boundary conditions, and loading conditions. The study is carried out in cooperation with GKN Fokker Aerostructures. The main objective of the research is to replace a...
master thesis 2024
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van Putten, Noël (author)
In this paper, the Proximal Policy Optimization (PPO) algorithm is used to perform a constrained wing shape optimization. The PPO algorithm is a Machine Learning (ML) algorithm that improves itself by repeatedly performing the same optimization and learning from its results. The complete adaptation of the PPO framework to the design problem is...
master thesis 2024
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Zoutendijk, M. (author)
The aerospace industry annually provides transport for billions of passengers along trillions of kilometers. The industry is continuously aiming to provide these services in a more efficient and sustainable way. One possibility is to consider improving airside airport operations, both current types and those expected in the near future....
doctoral thesis 2024
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Walinga, Hielke (author)
The behavior of software systems can be modeled as state machines by looking at the log data from these systems. Conventional algorithms, such as L∗, however, require too much memory to process log data when it gets too large. These algorithms must first load all available data into memory, which is often way too much.<br/>The approach...
master thesis 2024
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Gheorghe, Andrada (author)
Predicting aircraft Take-Off Weight (TOW) has been a long-sought task by aviation stakeholders, especially for operational and regulatory bodies involved in flight planning. Unfortunately, TOW being a sensitive parameter to operational trends and cost indices, aircraft operators tend to keep it confidential. In recent years, Machine Learning (ML...
master thesis 2024
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Vos, Geert (author)
This research has aimed to investigate the possibility of applying a neural network algorithm into the structural design process of bascule bridge leaves, by creating a workflow in Grasshopper. The demand for this tool, originates from the fact that the current design process is experienced as linear and slow, and does not fit the dynamic design...
master thesis 2024
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Kluft, Annefleur (author)
Introduction: Heart failure (HF) poses a significant burden on public health. This can be largely attributed to recurrent hospitalizations in consequence of HF decompensation. Detection of early signs of impending fluid retention may facilitate timely medical intervention and thereby prevent hospitalizations. Monitoring of Cardiac Implantable...
master thesis 2024
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Floris, Mihnea (author)
<br/>This research contributes to addressing climate change challenges through the examination of hydrogen combustion. It investigates the flow dynamics within a simplified model of Ansaldo Energia's GT36 reheat combustor using Large Eddy Simulation (LES) at a high pressure of 20 bar, focusing on the autoignition flashback phenomena observed....
master thesis 2024
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Mouw, Zeger (author)
The advancement of artificial intelligence (AI) has led to an increased demand for both a greater volume and quality of data. In many companies, data is dispersed across multiple tables, yet AI models typically require data in a single table format. This necessitates the merging of these tables and the selection of optimal features for the model...
master thesis 2024
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Leenen, Femke (author)
Introduction <br/>Opioids are vital for pain management but are highly addictive and may lead to opioid-induced respiratory depression (OIRD), which is the primary cause of death related to both prescription and illicit opioid use. This study employed unsupervised machine learning (ML) to examine potential changes in cluster patterns post-opioid...
master thesis 2024
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Anton, Mihai (author)
In large-scale ML, data size becomes a critical variable, especially in the context of large companies, where models already exist and are hard to change and fine-tune. Time to market and model quality are essential metrics, thus looking for ways to select, prune and augment the input data while treating the model as a black box can speed up the...
master thesis 2024
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te Marvelde, Pepijn (author)
In the realm of machine learning (ML), the need for efficiency in training processes is paramount. The conventional first step in an ML workflow involves collecting data from various sources and merging them into a single table, a process known as materialization, which can introduce inefficiencies caused by redundant data. Factorized ML strives...
master thesis 2024
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Vermeer, Jort (author)
The Random Finite Element Method (RFEM) is a robust stochastic method for slope reliability analysis that incorporates the spatial variability of soil properties. However, the extensive computational time associated with the direct Monte Carlo simulation limits its practical application. To overcome this problem, this study investigates the use...
master thesis 2024
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de Bie, Melissa (author)
Introduction<br/>Patient-ventilator asynchrony (PVA) poses a significant challenge in the management of mechanically ventilated patients, contributing to adverse clinical outcomes. Current methods of detecting PVA rely on visual assessment by clinicians, leading to subjectivity and inconsistency. Therefore, there is a need for automated...
master thesis 2024
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Jansen, Hidde (author)
Reinforcement Learning applied to flight control has shown to have several benefits over classical, linear flight controllers, as it eliminates the need for gain scheduling and it could provide fault-tolerance. The application to civil aviation in practice, however, is non-existent as there are multiple safety concerns. This research...
master thesis 2024
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Pozzi, G. (author)
The advancement of AI-based technologies, such as machine learning (ML) systems, for implementation in healthcare is progressing rapidly. Since these systems are used to support healthcare professionals in crucial medical practices, their role in medical decision-making needs to be epistemologically and ethically assessed. However, a central...
doctoral thesis 2024
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Koronaios, Panagiotis (author)
This study investigates the development and application of meta-models for crashworthiness assessment of helicopter structures and components. It aims to address the challenges associated with scarcity of data from computationally expensive simulations and experimental drop-tests, and enable the use of surrogates in a crashworthiness...
master thesis 2024
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