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Bhoraskar, Akshay (author)
This study aims at a possible solution to predict the fuel consumption of heavy duty diesel trucks, particularly, the tractor semitrailer for their long haul operations using various machine learning techniques. It intends to provide a possible alternative to simulation or physics based models, which often are very complicated. The stringent...
master thesis 2019
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Kras, Etienne (author)
Today's coastal zones are densely inhabited as the majority of the world's population lives in these attractive areas. The shorelines in coastal zones are shaped by complex spatial and temporal variable interactions between natural forcings like changes in mean sea-level, tides, wave and wind conditions, and storm surges. Besides, natural...
master thesis 2019
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Elghlan, Faris (author)
This M.Sc. thesis report investigates the application of one-class classification techniques to complex high-dimensional data. The aim of a one-class classifier is to separate target data from non-target data, but only a dataset containing target data is available for training. The issue with high-dimensional data is that it is difficult to...
master thesis 2019
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Sirenko, Mikhail (author)
master thesis 2019
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Gu, Nien-Hua (author)
The thesis addresses the implementation challenges of Machine Learning (ML) for merchandisers in the scenario of digitalization of retailing, and proposes a product-service design as the solution. The digitalization of retailing is defined as an on-going process to integrate Internet-connected digital technologies into interfaces between...
master thesis 2019
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Friđriksdóttir, Esther (author)
Physical activity and mobility are important indicators of the recovery process of patients in the general ward of the hospital. Currently, monitoring mobility of hospitalized patients relies largely on direct observation from the caregivers. Accelerometers have the potential to quantify physical activity of patients objectively and without...
master thesis 2019
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van Dam, Geart (author)
This research investigates and proposes a new method for obstacle detection and avoidance on quadrotors. One that does not require the addition of any sensors, but relies solely on measurements from the accelerometer and rotor controllers. The detection of obstacles is based on the principle that the airflow around a quadrotor changes when the...
master thesis 2019
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Hens, Joris (author)
The importance of value-based health care<br/>Worldwide, health care systems are struggling to control costs while improving care outcomes. An ageing population, increase in chronic patients and shortage in care professionals result in high burdens on our health care systems. Current health care systems are organized around delivering quantity....
master thesis 2019
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van der Arend, Dennis (author)
Traditionally a wind turbine’s power curve is used to model the long-term energy yield of the wind turbine and afterwards assess the performance of the turbine (power curve verification). But the current power curve is typically univariate: only dependent on the wind speed and slightly adjusted for site density, turbulence intensity and wind...
master thesis 2018
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Döpke, Max (author)
In this research a global-coefficient non-linear eddy viscosity model (NLEVM) is studied. This model stems from the inherent inability of the Boussinesq approximation to model anisotropy and therefore flow features such as: swirl, stream-line curvature and secondary motions (Lumley, 1970; Pope, 1975; Craft et al., 1996). The focus lies on the...
master thesis 2018
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Çete, Ceylan (author)
It is already acknowledged that Nature-based Solutions can be used to attenuate waves, however it is still uncertain to what extent the vegetation can contribute to decreasing the flood risk. So far mainly small-scale tests have been performed to quantify wave attenuating properties of vegetation. To quantify the effect of more extreme wave...
master thesis 2019
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Claes, Jochem (author)
The Low Earth Orbit (LEO) region has been attractive to many space agencies and organisations because of its ease of access and the ideal opportunity for remote sensing. Due to the low altitudes, a satellite's orbital state is highly affected by the atmospheric drag force acting on the satellite's body. The largest variation in this drag force...
master thesis 2019
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Ritsma, Folkert (author)
Performance of set based fault detection is highly dependent on the complexity of the set bounding methods used to bound the healthy residual set. Existing methods achieve robust performance with complex set bounding that narrowly define healthy system behavior, yet at the cost of higher computation times. In this thesis a major improvement is...
master thesis 2019
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van Schetsen, Anouk (author)
Predicting the trends in Bitcoin market prices is a very challenging task due to the many uncertainties and variables influencing the market value. The market is susceptible to quick changes, causing seemingly random fluctuations in the Bitcoin price. Due to the chaotic and highly volatile nature of Bitcoin behavior, investments come with high...
master thesis 2019
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Bouwman, Lieve (author)
Low-thrust trajectories can benefit the search for propellant-optimal trajectories, but increases in modeling complexity and computational load remain a challenge for efficient mission design and optimization. An approach for developing models utilizing Gaussian Process (GP) regression and classification is proposed to perform computationally...
master thesis 2019
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Arnaoutis, Vasos (author)
Deep Learning performance dependents on the application and methodology. Neural Networks with convolutional layers have been a great success in multiple tasks trained under Supervised Learning algorithms. For higher dimensional problems, the selection of a deep network architecture can significantly improve the accuracy of the network, however...
master thesis 2019
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van Odenhoven, Bas (author)
Air forces demand aircraft availability for their operations. In order to increase this availability, there is a need for insight in the effect of environmental conditions on the usage profiles of components and systems. Existing frameworks and standards only provide for static environmental effects on component degradation. The research...
master thesis 2019
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Diez Sanhueza, Rafael (author)
Turbulence modelling corresponds to one of the greatest unsolved problems in physics and mathematics. This phenomenon is marked by the emergence of chaotic vortex structures in the solution of the Navier-Stokes equations, and it corresponds to the leading-order effect in the majority of the flows observed in nature. Due to the importance of...
master thesis 2018
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Graur, Dan (author)
Given the increasing popularity of Machine Learning, and the ever increasing need to solve larger and more complex learning challenges, it is unsurprising that numerous distributed learning strategies have been brought forward in recent years, along with many large scale Machine Learning frameworks. It is however unclear how well these...
master thesis 2019
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Blauw, Alexander (author)
Turbulent flows are commonly encountered in scientific research or engineering applications and need simulations to be resolved. The Navier-Stokes equations govern the simulations of turbulent flows. One of the most common ways to solve the Navier-Stokes equations is to analyse the Reynolds averaged form (RANS). Next to the increasing...
master thesis 2019
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