Searched for: subject%3A%22machine%22
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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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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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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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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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Verburg, Corné (author)
This thesis addresses the challenge of segmenting ultra-high-resolution images. Limitations of current approaches to segment these are that either detailed spatial contextual information is lost or many redundant computations are necessary. To overcome these issues, we propose a novel approach combining the U-Net architecture with domain...
master thesis 2024
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Var, Sezer (author)
Semiconductor product development becomes increasingly challenging due to diminishing product life cycles, miniaturization, introduction of new physical principles, and new manufacturing processes. These problems are compounded in the absence of standardized development processes for the most complex semiconductor products like MEMS technologies...
master thesis 2024
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Yin, Junzhe (author)
The thesis explores an innovative technique for enhancing the precision of short-term weather forecasts, particularly in predicting extreme weather phenomena, which present a notable challenge for existing models such as PySTEPS due to their volatile behavior. Leveraging precipitation and meteorological data sourced from the Royal Netherlands...
master thesis 2024
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Buriani, Gioele (author)
This work introduces a novel methodology for the development of interpretable reduced-order dynamic models specifically tailored for jumping quadruped robots. Leveraging Symbolic Regression combined with autoencoder neural networks, the framework autonomously derives symbolic equations from data and fundamental physics principles capturing the...
master thesis 2024
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Rijs, Joyce (author)
<b>Background</b>: Undetected Intellectual Disability (ID) can lead to chronic stress due to overestimation by society. Chronic stress can cause stress-related health issues, like hypertension, chronic fatigue and abdominal complaints. When a physician (General Practitioner (GP) or medical specialist) does not recognize that a patient has ID,...
master thesis 2024
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Bekooy, Mark (author)
Type annotations in Python are an integral part of static analysis. They can be used for code documentation, error detection and the development of cleaner architectures. By enhancing code quality, they contribute to the robustness, maintainability and comprehensibility of codebases. Tools like static type checkers use type annotations to detect...
master thesis 2024
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Aalders, Jaime (author)
Addressing the increasingly urgent need for sustainable aviation solutions, this study explores operational innovations as a quicker and more scalable addition to novel zero-emission propulsion systems. Through the use of regression-based causal inference methods, this study aims to understand the relationship between flight fuelburn...
master thesis 2024
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van Winden, Brian (author)
Introduction<br/>Approximately 9 in 1000 children are born with congenital heart disease (CHD), of whom a quarter are classified as critical CHD (CCHD) and require an intervention within their first year. Monitoring these patients in the Paediatric Intensive Care Unit (PICU) is crucial, yet with increasing amounts of data, detecting subtle...
master thesis 2024
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Bink, Kiki (author)
Facing the critical challenge of reducing greenhouse gas (GHG) emissions in the maritime industry, this thesis explores the potential of smart control systems using Reinforcement Learning (RL) for autonomous sailing. Traditional controls for sailing fall short in navigating the complex, dynamic conditions of maritime environments. RL has shown...
master thesis 2024
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Groenenboom, Max (author)
Sound pollution is becoming an increasingly pressing issue in today’s world. To effectively address it, it must be measured. To this end, Serval was developed, an edge-ai powered sound recognition solution. Its lack of accuracy, however, makes it difficult to deploy. This thesis examines the potential for improving this solution while staying...
master thesis 2024
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Niemantsverdriet, Ruben (author)
The periconceptional period, encompassing the embryonic phase, is a critical window where a majority of reproductive failures, pregnancy complications, and adverse pregnancy outcomes arise. The Carnegie staging system comprises 23 stages which are based on embryonic morphological development. This allows for the assessment of normal and abnormal...
master thesis 2024
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Mckenzie, Max (author)
Haptic shared controllers (HSCs) are a promising solution to prevent human over-reliance on automation during tasks such as car driving. However, research has shown that if the HSC is tuned incorrectly, then there is a risk of haptic conflicts between the human and HSC. To address this challenge, this paper presents the design and implementation...
master thesis 2024
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