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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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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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van de Pol, Dani (author)The Dutch banking sector is mandated to identify and report transactions that may signify money laundering (ML) activities. Banks have been reliant on rule-based transaction monitoring (TM) systems that flag transactions exceeding predefined thresholds. While such systems are instrumental in filtering potential ML transactions, the inherently...master thesis 2023
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Eek, Majolie (author)This study is an analysis of sand mining in the Vietnamese Mekong Delta (VMD) with the use of the optical satellite data set PlanetScope. This is done with a detection and classification model of sand mining vessels in the VMD. The classification model is based on machine-learning and it is trained with three classes: sand mining vessels, other...master thesis 2023
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Veeger, Lucas (author)Reducing cost and improving computability of reservoir simulation is an important goal in the process of enabling CCS (Carbon Capture \& Storage) as a large-scale technology for mitigating CO2 emissions. In terms of computation time data-driven approaches have potential to outweigh the performance of numerical reservoir simulators, learning...master thesis 2023
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Maes, Vincent (author)The aerodynamic model of a combat aircraft is essential for its success and competitiveness compared to other combat aircraft. This thesis aims to research the most optimal machine learning model to create an aerodynamic model of a combat aircraft. The very large but still sparse, highly nonlinear dataset forms a challenge for using specific...master thesis 2023
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Weijenberg, Yannick (author)This thesis investigates clinical phase recognition for cardiac catheterization purposes, focusing on coronary angiography (CAG) procedures, in the context of an increasing annual prevalence of coronary artery disease. It applies machine learning to analyze C-arm logs and video recordings, aiming to improve procedural efficiency by recognizing...master thesis 2023
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Apak, Boran (author)The goal of this thesis is expanding quantum algorithm datasets to enhance our capability to benchmark quantum systems and to open up possibilities for using machine learning techniques in quantum circuit mapping. Both of these areas are currently hindered by the lack of a wide range of useful quantum algorithms. To solve this problem, KetGPT is...master thesis 2023
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Heidekamp, Mathijs (author)Resistive random access memory (RRAM) is an emerging memory technology that has the potential to replace dynamic random access memory (DRAM) or FLASH. The current memory technology suffer from scalability issues. RRAM can be used as potential replacement for Flash and DRAM. RRAM stores information using resistance states instead of charge. RRAM...master thesis 2023
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Li, David (author)Technological devices are ubiquitous, think of for example smartphones and in-vehicle information systems. Both can contribute towards distracted driving where the visual field of the human controller is shifted away from the primary control task. In this paper a neural network model is trained using the InceptionTime architecture and used to...master thesis 2023
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Gnanavarothayan, Kabilan (author)The use of Internet of Things (IoT) devices has experienced an increase since its inception and is expected to continue to do so. However, this growth has also attracted individuals with malicious intentions. Botnet attacks on IoT devices have become more potent each year, exploiting new vulnerabilities and attacking more devices. Therefore, it...master thesis 2023
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Rang, Jugo (author)This paper presents a novel approach for the estimation of conditional multivariate cumulative distribution functions (CDFs) within a nonparametric framework. To achieve this, we introduce a binary random variable that indirectly represents conditional CDFs and construct a dataset by pairing input vectors with the binary variables. We developed...master thesis 2023
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Smeenk, Rutger (author)This research aims at quantifying the uncertainty in the predictions of tensor network constrained kernel machines, focusing on the Canonical Polyadic Decomposition (CPD) constrained kernel machine. Constraining the parameters in the kernel machine optimization problem to be a CPD results in a linear computational complexity in the number of...master thesis 2023
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Nijsse, Paul (author)Myeloproliferative Neoplasms (MPNs) are a group of bone marrow diseases with potentially lethal cardio-vascular complications. Two sub-diseases of MPN are Essential Thrombocytosis (ET) and Polycythemia Vera (PV), which are recognised by an abnormal blood count of respectively thrombocytes and red blood cells.<br/><br/>If an MPN is treated...master thesis 2023
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VASILEIOU, ANTONIOS (author)Graph data is widely used in various applications, driving the rapid development of graph-based machine learning methods. However, traditional algorithms tailored for graphs have constraints in capturing intricate node relationships and higher-order patterns. Recent insights from prior research have shed light on comparing different graph neural...master thesis 2023
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Schmidt, Stephan (author)This paper examines the end-to-end development process for a Convolution Neural Network (CNN) based damage classification tool for ultrasonic inspection of aerospace-grade composite structures. The recent advent of Artificial Intelligence (AI) and Machine Learning (ML) has piqued the interest of the aerospace industry since it has the potential...master thesis 2023
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Patalay, Prathamesh (author)PROBLEM<br/>Foundation Models are emerging as a new paradigm in AI research &<br/>commercialisation. While this opens up possibilities for radically innovative<br/>solutions and significant value creation, startups are challenged with finding<br/>unique & differentiated ways to leverage the technology, while simultaneously<br/>mitigating...master thesis 2023
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van Spengler, Olivier (author)Demand forecasting plays a critical role in organizational planning, encompassing inventory management, capacity allocation, and financial decision-making. However, achieving accurate forecasts can be challenging, particularly in industries characterized by high demand volatility, such as semiconductor assembly equipment manufacturing,...master thesis 2023