Searched for: contributor%3A%22Reinders%2C+M.J.T.+%28graduation+committee%29%22
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Drummer, Francesca (author)Single-cell sequencing allows measuring individual cells' molecular features and their responses to perturbations. Understanding which cells respond to a particular perturbation and how these responses vary across populations can be used to, for example, improve vaccine immunogenicity. However, an exhaustive exploration of single-cell...master thesis 2022
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Keukeleire, Pia (author)Cell-free DNA (cfDNA) are DNA fragments originating from dying cells that enter the plasma. Uncontrolled cell death, for example caused by cancer, induces an elevated concentration of cfDNA. As a result, determining the cell type origins of cfDNA can provide information about an individual's health. This research looks into how to increase the...master thesis 2022
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Jonker, Luc (author)For mobile augmented or virtual reality applications with limited processing power, representing realistic water geometry is a challenge. Many existing solutions are simulations that can only run at interactive rates on desktop computers. This paper presents a lightweight approximative approach to water representation achieved through mesh LOD...bachelor thesis 2022
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Lungu, Alexandru (author)This paper proposes a novel approach to visualizing events in sailing regattas, in a way that is engaging, informative and interactive to the users of the Sailing+ application. The approach used was to create two different types of visualizations for each type of event: artistic, which contains animations and effects such as depth of field, and...bachelor thesis 2022
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Botha, Christiaan (author)Clustering forms a major part of showing different relations between data points. Real-time clustering algorithms can visualise relationships between elements in a 3D environment, provide an analysis of data that is separate from the underlying structure and show how the data changes over time. <br/>This paper analyses whether conventional...bachelor thesis 2022
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Becheanu, Luca (author)This paper introduces the concept of the Voronoi Split-Screen in Augmented Reality inside a Sailing Regatta visualization application. We are making use of existing methods in 2D environments and modifying them to treat the implications of merging the screen where a user has complete camera control (3D/AR/VR). This is done in three phases which...bachelor thesis 2022
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Bobe, Alexandru (author)Scheduling is required in almost every industry and when done well it can bring a lot of revenue. Flexibility is often forgotten when creating the initial schedules. Therefore, in case of an unexpected delay, the whole schedule has to suffer. In this paper, we consider a re-entrant flow shop with sequence-dependent setup times and relative due...bachelor thesis 2022
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van Delft, Amir (author)Critical constraints in re-entrant flexible manufacturing systems(FMSs) schedules are those constraints that for some change to their weight (and only the weight), could make the sequence of operation in the schedule infeasible. This paper describes how to find critical constraints by representing the benchmark as a graph and finding its...bachelor thesis 2022
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van Ulsen, Hidde (author)Image registration is a fundamental requirement for many medical applications. In recent years, deep learning approaches for registration have shown to be a promising alternative to conventional methods. However, most learning based methods do not consider the different physical properties of various tissues, which can result in unrealistic...master thesis 2022
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Garst, Swier (author)Federated learning is an upcoming machine learning concept which allows data from multiple sources be usedfor training of classifiers without said data leaving its origin. In certain research cases using highly privatedata, the step of gathering data can be quite tedious. In such cases, federated learning has the potential tovastly speed up the...master thesis 2021
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Ruighaver, Ewoud (author)In recent years the advent of multi-omic techniques have shown great promise in the field of oncology. In light of these advancements, this thesis focuses on the use of multiple data types to find methylation markers around transcription start site regions for colorectal cancer in the cell-free DNA (cfDNA) domain. It combines several methods of...master thesis 2021
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van 't Wout, Maarten (author)Handling missing values is crucial for accurately forecasting time series with different sampling rates. In stock price prediction, for example, the daily stock prices and quarterly valuation figures are sampled at a different rate, and both are useful in estimating the daily stock price’s future. This research proposes combining imputation...master thesis 2021
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Kaur, Sukhleen (author)Survival analysis is a statistical method used to predict when an event will occur. Machine learning survival models have been used in many cancer studies. However, machine learning models may not always be interpretable. The current lack of research for explainable survival analysis for urothelial cancer prompted this study. This study offers...master thesis 2021
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Singh, Akash (author)Single-cell multi-modal omics promises to open new doors in bioinformatics by measuring different aspects of cells, thus offering multiple perspectives on the underlying biological phenomenon. Although simultaneous multi-modal measurement protocols do exist, their inherent technical limitations necessitate focus on single modality measurements....master thesis 2021
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Özyar, Muhammed Imran (author)The field of finance is an interesting field in which much research takes place. In particular, its sub-field of modeling the dynamics of order books is an interesting field, since it translates into modeling the behaviour of traders on the market. Most of the models proposed in this field can be divided into stochastic models or machine...master thesis 2021
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Pronk, Bram (author)Personalized treatment methods for a complex disease such as cancer benefit from using multiple data modalities from a patient's cancer cells. Multiple modalities allow for analysis of dependencies between complex biological processes and downstream tasks, such as drug response and/or expected survival rate. To this end, it is important to gain...bachelor thesis 2021
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van Groeningen, Boris (author)Using RNA sequence data for predicting patient properties is fairly common by now. In this paper, Variational Auto-Encoders (VAEs) are used to assist in this process. VAEs are a type of neural network seeking to encode data into a smaller dimension called latent space. These latent features are then used to do downstream task analysis such as...bachelor thesis 2021
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Kroskinski, Ivo (author)Variational Auto-Encoders are a class of machine learning models that have been used in varying context, such as cancer research. Earlier research has shown that initialization plays a crucial part in training these models, since it can increase performance. Therefore, this paper studies the effect initialization methods on VAEs. This research...bachelor thesis 2021
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Korkić, Armin (author)Cancer has been known as a deadly and complex disease to tackle. By applying machine learning algorithms we hope to improve personalized treatment for cancer patients. These machine learning algorithms are trying to learn a (latent) representation of the input. The problem is that this representation is hard to interpret and to observe the...bachelor thesis 2021
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d'Anjou, Raymond (author)This study presents a comparison of different VariationalAutoencoder(VAE) models to see which VAE models arebetter at finding disentangled representations. Specificallytheir ability to encode biological processes into distinct la-tent dimensions. The biological processes that will be lookedat are the cell cycle and differentiation state. The...bachelor thesis 2021
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