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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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Jaldevik, Albin (author)Over the last decade, there have been significant advances in model-based deep reinforcement learning. One of the most successful such algorithms is AlphaZero which combines Monte Carlo Tree Search with deep learning. AlphaZero and its successors commonly describe a unified framework for tree construction and acting. For instance, build the tree...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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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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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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Lee, Y. (author)E-learning has shifted the traditional learning paradigms in higher education, offering more flexible, ubiquitous, and personalized learning experiences. The previous years COVID-19 pandemic required a re-calibration of education to accommodate virtual learning environments from the traditional classroom-based education. Widespread learning...doctoral thesis 2024
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Ramsundersingh, Pravesha (author)A learning curve can serve as an indicator of the “performance of trained models versus the training set size” [1]. Recent research on learning curve analysis has been carried out within the Learning Curve Database (LCDB) [2] This paper will investigate if there are similarities amongst these curves by clustering those provided by the LCDB. The...bachelor thesis 2024
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Johari, Pratham (author)This study explores the extrapolation of learning curves, a crucial aspect in evaluating learner performance with varying dataset sample sizes. We use the Learning Curve Prior Fitted Network (LC-PFN), a transformer pre-trained on synthetic data with proficiency in approximate Bayesian inference, to investigate its predictive accuracy using the...bachelor thesis 2024
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Homborg, A.M. (author), Mol, J.M.C. (author), Tinga, Tiedo (author)This paper for the first time treats the interpretation of electrochemical noise time-frequency spectra as an image classification problem. It investigates the application of a convolutional neural network (CNN) for deep learning image classification of electrochemical noise time-frequency transient information. Representative slices of these...journal article 2024
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Singha, Chiranjit (author), Swain, Kishore Chandra (author), Moghimi, Armin (author), Foroughnia, Fatemeh (author), Swain, Sanjay Kumar (author)Accurately assessing forest fire susceptibility (FFS) in the Similipal Tiger Reserve (STR) is essential for biodiversity conservation, climate change mitigation, and community safety. Most existing studies have primarily focused on climatic and topographical factors, while this research expands the scope by employing a synergistic approach...journal article 2024
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Adla, Soham (author), Bruckmaier, Felix (author), Arias-Rodriguez, Leonardo F. (author), Tripathi, Shivam (author), Pande, S. (author), Disse, Markus (author)Sensor data and agro-hydrological modeling have been combined to improve irrigation management. Crop water models simulating crop growth and production in response to the soil-water environment need to be parsimonious in terms of structure, inputs and parameters to be applied in data scarce regions. Irrigation management using soil moisture...journal article 2024
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Glab, K. (author), Wehrmeyer, G. (author), Thewes, M. (author), Broere, W. (author)Designing the main drive motor capacity of Earth Pressure Balanced Tunnel Boring Machines (EPB TBMs) is a crucial task for every EPB tunnelling project. The machine needs to be equipped with sufficient power to master the geotechnical conditions of the respective project. On the other hand, overpowering the machine should be avoided for...journal article 2024
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Shan, X. (author), Steele-Dunne, S.C. (author), Hahn, Sebastian (author), Wagner, Wolfgang (author), Bonan, Bertrand (author), Albergel, Clement (author), Calvet, Jean Christophe (author), Ku, Ou (author)ASCAT normalized backscatter (σ<sub>40</sub><sup>o</sup>) and slope (σ<sup>′</sup>) contain valuable information about soil moisture and vegetation. While σ<sub>40</sub><sup>o</sup> has been assimilated to constrain soil moisture, sometimes together with Leaf Area Index (LAI), this study is the first to assimilate σ<sup>′</sup> directly to...journal article 2024
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Wu, D. (author), Zhang, R. (author), Pore, Ameya (author), Ha, Xuan Thao (author), Li, Z. (author), Herrera, Fernando (author), Kowalczyk, Wojtek (author), De Momi, Elena (author), Dankelman, J. (author), Kober, J. (author)Minimally Invasive Procedures (MIPs) emerged as an alternative to more invasive surgical approaches, offering patient benefits such as smaller incisions, less pain, and shorter hospital stay. In one class of MIPs, where natural body lumens or small incisions are used to access deeper anatomical locations, Flexible Surgical and Interventional...review 2024
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Zhang, D. (author), Wang, Zhenpo (author), Liu, Peng (author), She, Chengqi (author), Wang, Qiushi (author), Zhou, Litao (author), Qin, Z. (author)Accurately evaluating battery degradation is not only crucial for ensuring the safe and reliable operation of electric vehicles (EVs) but also fundamental for their intelligent management and maximum utilization. However, the non-linearity, non-measurability, and multi-stress coupled operating conditions have posed significant challenges for...journal article 2024
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Koohmishi, Mehdi (author), Kaewunruen, Sakdirat (author), Chang, L. (author), Guo, Y. (author)Railway track health monitoring and maintenance are crucial stages in railway asset management, aiming to enhance the train operation quality and service life. For this aim, various inspection means (using diverse non-destructive testing techniques) have been applied, however, these means are mostly not able to monitor whole railway track...review 2024