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Synthetic data generation for the optimization of strains in metabolic engineering using latent space representations derived from a Conditional Variational Autoencoder

Alwani, Neil (author)

This study investigates the application of generative models for synthetic data generation in pathway optimization experiments within the field of metabolic engineering. Conditional Variational Autoencoders (CVAEs) use neural networks and latent variable distributions to generate new, plausible data samples. We adapt this model by conditioning...

bachelor thesis 2024

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Learning Reduced Order Mappings of Navier-Stokes: An Investigation of Generalization on the Viscosity Parameter

Kiste, Amund (author)

Solving Partial Differential Equations (PDEs) in engineering such as Navier-Stokes is incredibly computationally expensive and complex. Without analytical solutions, numerical solutions can take ages to simulate at great expense. In order to reduce this cost, neural networks may be used to compute approximations of the solution for use during...

bachelor thesis 2024

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Data Driven Approximations Of PDEs: On Robustness of Reduced Order Mappings between Function Spaces Against Noise

Lacombe, Pablo (author)

This paper presents a comprehensive exploration of a novel method combining Principal Component Analysis (PCA) and Neural Networks (NN) to efficiently solve Partial Differential Equations (PDEs), a fundamental challenge in modeling a wide range of real-world phenomena. Our research extends the work of Bhattacharya et al. by focusing on PCA for...

bachelor thesis 2024

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Electrical Impedance Measurements in the Gastrointestinal Tract: Cancerous or Non-Cancerous?

Remmerswaal, Evan (author)

Objective: This work focuses on the feasibility of using Electrical Impedance Spectroscopy (EIS) to differentiate between cancerous and healthy tissues in real-time alongside the GI tract. This is to see whether it is possible to support surgeons when taking biopsies, or to see if it is possible to make biopsies obsolete with EIS. Methods: The...

master thesis 2023

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Treatment Prediction in PDAC Patients: A Predictive Model for FOLFIRINOX Chemotherapy Response using Random Forest and Integrative Analysis of Blood and Tumor Markers

Lu, Jenny (author)

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a high mortality rate, poor prognosis, and a mere 7.7% 5-year survival rate [1] compared to 65% for all cancer types [2]. Approximately 80% of patients are diagnosed at the advanced stage [3], for which only palliative chemo(radio)therapy remains as treatment option. However,...

master thesis 2023

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Comparative analysis of clutter filtering techniques on freehand micro-Doppler ultrasound imaging

Gao, Xuan (author)

Micro-Doppler (µDoppler) ultrasound imaging is a high frame rate ultrasound imaging modality that provides high spatiotemporal resolution ultrasound images of blood flow. It is sensitive to slow blood flow and particularly suitable for capturing fast-changing phenomena like rapid blood flow. Clutter filtering is an essential step in µDoppler...

master thesis 2023

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A Methodology for Damage Detection Using Unsupervised Learning in the Field of Structural Health Monitoring: Based on Gaussian Mixture Modeling

Vilhjálmsson, Thor (author)

This thesis aims to investigate the feasibility of developing a successful unsupervised Structural Health Monitoring (SHM) methodology to detect damage in structures, specifically bridges. Detecting damage, especially in its earliest stages, is challenging, thus prompting the need for robust and effective methods. The success of such a...

master thesis 2023

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Elimination of traffic induced operational variability with Robust Principal Component Analysis (rPCA)

Sigurðsson, Snorri Þór (author)

Regular maintenance of civil engineering structures is essential for their safety. Current maintenance regimes involve periodic inspections at regular time intervals. In the time between inspections, there can be a critical development in the structural integrity of a structure, which can be expensive to repair or could even lead to structural...

master thesis 2023

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Distinguishing ’Sugar’, ’Gravel, ’Flowers’ and ’Fish’ mesoscale cloud patterns in the trades using cluster analysis

Luchmun, Gyan (author)

In this thesis we are interested in distinguishing patterns of mesoscale cloud patterns in the trades. Specifically, whether Sugar, Gravel, Fish and Flowers patterns can objectively be identified using physical quantities. For this purpose, we use cloud fraction data attained by the CORAL Ka-Band cloud radar at the Barbados Cloud Observatory...

bachelor thesis 2022

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Identifying high Alpine geomorphological processes using permanent laser scanning time series

Frantzen, Paco (author)

Global climate change affects mountain regions such as the European Alps. Consequently, glacier extents decrease, and proglacial areas, the areas that recently lost their ice cover, increase in size. These proglacial areas are subject to a high frequency and magnitude of geomorphological activity and act as a sediment source for downstream...

master thesis 2022

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Characterizing the spatio-temporal dynamics of social vulnerability in Burkina Faso: A comparison of Principal Component Analysis with Equal Weighting

Savelberg, Lotte (author)

Global climate change has results in a higher frequency of extreme disaster events and is therefore a serious challenge in disaster impact management. Disaster risk is composed of several components, such as vulnerability, susceptibility, exposure and the probability of occurence and intensity of a hazard. Vulnerability has become a topical...

master thesis 2022

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Water Quality Measurements in the Brantas, Indonesia: Constructing Different Perspectives with Principal Component Analysis

Willard, Tijmen (author)

The water quality of the Brantas river in Indonesia is of concern to several agencies on East Java. These agencies all measure its water quality in their own way in terms of locations, rhythms and parameters. The goal of this thesis is to find out if these agencies measure the same and if not, how these measurements differ. From these...

master thesis 2022

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Unravelling sediment transport driven by a multimodal wind-wave spectrum

Hoogervorst, Chris (author)

This thesis analyses the importance and application of considering multiple coexisting wave trains in sediment transport predictions.<br/><br/>The wave trains at offshore and nearshore locations are analyzed by wave spectral partitions (Portilla at el., 2009). The temporal variability of consistently occurring wave trains can be analyzed through...

master thesis 2022

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Synergies-Based Teleoperation of a Robot Hand by a Hand Tracking System

Lee, Chia-Fu (author)

Hand pose tracking in 3D configuration is one of the popular components of human-computer interaction research, which can be seen applying in virtual reality (VR) and augmented reality (AR). Although the research field has been thoroughly studied in the past few decades, most methods emphasized recognizing hand gestures or joint locations....

master thesis 2021

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Quaternion PCA and sparse PCA for shape variability

van Steijn, Z.A. (author)

Principal component analysis (PCA) is commonly used in the fields of computer graphics and geometry processing for constructing subspaces that represent the variability present in a dataset. Examples of such datasets are configurations of a non-rigid object, poses of a deformable character or snapshots from a simulation. By applying PCA to the...

master thesis 2020

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Nonnegative Robust PCA for Background and Foreground Image Decomposition

Ling, Chenyang (author)

Nowadays, video surveillance and motion detection system are widely used in various environments. With the relatively low-price cameras and highly automated monitoring system, video and image analysis on road, highway and skies becomes realistic. The key process in the analysis is to separate the useful information such as moving foreground...

master thesis 2020

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Principal Component Analysis of Education-Related Data Sets

Nguyen, T.P.K. (author)

Principal Component Analysis (PCA) is a mathematical instrument beneficial for its dimension reduction whilst keeping the most important data. Due to its advantages, PCA is chosen to handle a substantial amount of data. In this thesis two questions are answered: what variables influence a pupil's attainment test score using linear regression and...

bachelor thesis 2020

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Influence of Climate and Vegetation on Root Zone Storage Capacity: A case study in Australia

Wei, Mengya (author)

Root zone storage capacity Sr is a significant variable for hydrology and climate studies, as it strongly influences the hydrological behaviour of a catchment. A climate-derived method (water-balance between precipitation and transpiration) was applied for estimating Sr values for 113 catchments in Australia. Various climate, hydrological and...

master thesis 2020

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Interpretable Machine Learning for Biomarker Discovery in Imaging Mass Spectrometry Data

Tideman, Leonoor (author)

Imaging mass spectrometry (IMS) is a multiplexed chemical imaging technique that enables the spatially targeted molecular mapping of biological samples at cellular resolutions. Within a single experiment, IMS can measure the spatial distribution and relative concentration of thousands of distinct molecular species across the surface of a tissue...

master thesis 2019

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Designing with dynamic light textures: Enlightening designers

Louwers, Gijs (author)

This thesis provides the reader with the necessary theoretical frameworks to understand the research aimed towards answering the question: which associations do people have with atmospheres influenced by dynamic light textures? This question is then used to provide a framework of guidelines for the designer. A review of lighting design history...

master thesis 2019