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Chen, Linda (author)Background: Histopathological examination in the diagnostic workflow of oropharyngeal squamous cell carcinoma (OPSCC) is essential. We aimed to develop a machine learning pipeline to predict human papillomavirus (HPV) status in OPSCC patients based on clinical variables and multiparametric magnetic resonance imaging (MRI). <br/>Methods: In a...master thesis 2023
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Stals, Michael (author)Numerical modelling in Geo-Engineering is used to solve complex problems by simulating, analysing, or predicting soil behaviour under certain loading and boundary conditions. The soil behaviour is simulated by constitutive models that describe the relationship between stresses and strains through a mathematical formulation. Model parameters are...master thesis 2023
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Lagerweij, Jelle (author)In this work, the added value of machine learning (ML) molecular force fields (FF) for the community of molecular simulations is showcased by successfully calculating transport properties of aqueous potassium hydroxide (KOH (aq)). Classical FFs use relatively simple interatomic potentials to simulate the nano scale. These simulations can predict...master thesis 2023
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Trap, Cyril (author)Privacy is a human right, yet, people’s behavior on the web is constantly tracked. Tor, an anonymity network, is an effective defence against tracking. However, Tor’s multiplexing of logically independent data streams into a single TCP connection causes issues. Tor with QUIC has been implemented as an alternative with better performance but it...master thesis 2023
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de Beer, Arne (author)This paper presents a study focused on developing an efficient signal processing pipeline and identifying suitable machine learning models for real-time gesture recognition using a testbed consisting of an Arduino Nano 33 BLE and three OPT101 photodiodes. Our research aims to address the challenges of limited computational power whilst...bachelor thesis 2023
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Rugină, Alissia (author)Studies in Music Affect Content Analysis use varying emotion schemes to represent the states induced when listening to music. However, there are limited studies that explore the translation between these representation schemes. This paper explores the feasibility of using machine learning models to translate from a dimensional scheme of Valence,...bachelor thesis 2023
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Popica, Tudor (author)This research investigates the improvement of Kernel Density Estimation (KDE) comprehension in a university context via visualization-enhanced teaching. The study tackles KDE misconceptions, the efficacy of visual aids, and the role of previous mathematical and machine learning knowledge. Using a mix of literature review, survey, and...bachelor thesis 2023
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Dijkstra, Jonathan (author)In recent years, the agricultural sector has seen significant techno- logical improvements under the flag of precision agriculture, assisting farmers in the manageability that coincides with large-scale farming. Moreover, precision agriculture aims to enable plant-specific farming on the macro scale that is demanded by the current global...master thesis 2023
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Herle, Olivier (author)This thesis evaluates the effects of including automated event data for interstate conflict prediction. Automated event data are web-scraped news stories converted into data and they may allow conflict models to increase their performance. Accurate models can then be used for early-warning purposes.<br/><br/>To predict three separate problems,...master thesis 2023
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Mourragui, S.M.C. (author)Extensive efforts in cancer research over the past decades have markedly improved diagnosis and treatments, leading to better outcomes for cancer patients. Paradoxically, however, these discoveries have begun to shed light on a level of complexity that rules out the emergence of a universal cancer treatment. As any tumor is now known to be...doctoral thesis 2023
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Kanniainen, Konsta (author)Various techniques have been studied to handle unexpected changes in data streams, a phenomenon called concept drift. When the incoming data is not labeled and the labels are also not obtainable with a reasonable effort, detecting these drifts becomes less trivial. This study evaluates how well two data distribution based label-independent drift...bachelor thesis 2023
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Meester, Anne (author)Introduction: Critically ill children admitted to the Paediatric Intensive Care Unit (PICU) have a high risk of disruption of their normal sleep rhythm, which is associated with disturbances in physiology and negative effects on psychological and cognitive functioning. There is a need for real-time, automatic sleep monitoring to minimise...master thesis 2023
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Rajesh, A. (author), Ya, Wei (author), Hermans, M.J.M. (author)The current research work investigates the possibility of using machine learning models to deduce the relationship between WAAM (wire arc additive manufacturing) sensor responses and defect presence in the printed part. The work specifically focuses on three materials from the nickel alloy family (Inconel 718, Invar 36 and Inconel 625) and uses...journal article 2023
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Yuan, Y. (author), Wang, Kaiyi (author), Duives, D.C. (author), Hoogendoorn, S.P. (author), Hoogendoorn-Lanser, S. (author), Lindeman, Rick (author)Data-driven approaches are helpful for quantitative justification and performance evaluation. The Netherlands has made notable strides in establishing a national protocol for bicycle traffic counting and collecting GPS cycling data through initiatives such as the Talking Bikes program. This article addresses the need for a generic framework to...journal article 2023
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Peng, C. (author), May, Ali (author), Abeel, T.E.P.M.F. (author)BackgroundEnteric methane from cow burps, which results from microbial fermentation of high-fiber feed in the rumen, is a significant contributor to greenhouse gas emissions. A promising strategy to address this problem is microbiome-based precision feed, which involves identifying key microorganisms for methane production. While machine...journal article 2023
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Tepeli, Y.I. (author), Seale, C.F. (author), P. Gonçalves, Joana (author)Motivation<br/><br/>Anti-cancer therapies based on synthetic lethality (SL) exploit tumour vulnerabilities for treatment with reduced side effects, by targeting a gene that is jointly essential with another whose function is lost. Computational prediction is key to expedite SL screening, yet existing methods are vulnerable to prevalent selection...journal article 2023
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Sav, Andra Georgiana (author), Demetriou, A.M. (author), Liem, C.C.S. (author)Machine Learning (ML) models influence all aspects of our lives. They also commonly are integrated in recommender systems, which facilitate users’ decision-making processes in various scenarios, such as e-commerce, social media, news and online learning. Training performed on large volumes of data is what ultimately drives such systems to...journal article 2023
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Guo, Rongge (author), Bhatnagar, Saumya (author), Guan, Wei (author), Vallati, Mauro (author), Sharif Azadeh, S. (author)This paper presents a novel framework for customised modular bus systems that leverages travel demand prediction and modular autonomous vehicles to optimise services proactively. The proposed framework addresses two prediction scenarios with different forward-looking operations: optimistic operation and pessimistic operation. A mixed integer...journal article 2023
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Sturm, Patrick Obin (author), Manders, Astrid (author), Janssen, Ruud (author), Segers, Arjo (author), Wexler, Anthony S. (author), Lin, H.X. (author)The chemical transport model LOTOS-EUROS uses a volatility basis set (VBS) approach to represent the formation of secondary organic aerosol (SOA) in the atmosphere. Inclusion of the VBS approximately doubles the dimensionality of LOTOS-EUROS and slows computation of the advection operator by a factor of two. This complexity limits SOA...journal article 2023
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Sharman, Kavya (author), Patterson, Nathan Heath (author), Weiss, Andy (author), Neumann, Elizabeth K. (author), Guiberson, Emma R. (author), Ryan, Daniel J. (author), Gutierrez, Danielle B. (author), Spraggins, Jeffrey M. (author), Van de Plas, Raf (author), Skaar, Eric P. (author), Caprioli, Richard M. (author)Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate...journal article 2023