Searched for: subject%3A%22machine%255C+learning%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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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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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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Liang, M. (author)
Since the introduction of cementitious materials, shrinkage-induced earlyage cracking (EAC) has emerged as a significant issue that negatively influences the function, durability, and aesthetics of concrete structures like dams, tunnels, and underground garages. This thesis aims to develop new experimental and modelling techniques that help...
doctoral thesis 2024
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Nadeem, A. (author)
Understanding the behavior of cyber adversaries provides threat intelligence to security practitioners, and improves the cyber readiness of an organization. With the rapidly evolving threat landscape, data-driven solutions are becoming essential for automatically extracting behavioral patterns from data that are otherwise too time-consuming to...
doctoral 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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Ale Ebrahim Dehkordi, Molood (author)
In society, institutions are the foundation that governs human behaviour through rules, norms, and regulations. The actions and interactions of individuals are shaped by these institutions, forming a cyclic system with numerous parameters and factors. Altering any of these factors, triggers the entire system to transition into a new state that...
doctoral thesis 2024
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Aghaeian, S. (author)
H igh-temperature (HT) oxidation plays a significant role in various stages of the steelmaking process, including hot rolling. When exposed to high temperatures and oxygen partial pressure, the steel composition near the surface can be altered as alloying elements deplete. Additionally, the characteristics of the oxide scale, such as thickness...
doctoral 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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