Searched for: subject:"machine"
(1 - 20 of 278)

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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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Yu, Rui (author)
The development of intelligent vehicle and autonomous driving asked a higher requirement of ADAS on its functionality. Currently, ADAS systems are able to detect and segment urban and highway driving scenes. They cannot, in general, extract ’meaning’ from this segmentation yet. Learning the intention of other road users will help ADAS understand...
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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Kapadia, Husain (author)
Listening in noise is a challenging problem that affects the hearing capability of not only normal hearing but especially hearing impaired people. Since the last four decades, enhancing the quality and intelligibility of noise corrupted speech by reducing the effect of noise has been addressed using statistical signal processing techniques as...
master thesis 2019
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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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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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Sirenko, Mikhail (author)
master thesis 2019
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Venkatesan, Karthik (author)
This research project was initiated as a result of a curiosity and desire to investigate the applicability of surrogate modelling to analyse complex non-linear behaviour in aircraft structures. The study chose to focus on modelling damage in composite plates, and through a literature review, deemed that the generation of graphical outputs was a...
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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Noppen, Marko (author)
Adaptive optics are widely used to correct the wavefront distortion imposed by atmospheric turbulence. Focal plane phase retrieval from intensity measurements has advantages due to the ease of implementation, potential broader application, less computations, low cost, high system bandwidth, simplified hardware and less calibration. To cope with...
master thesis 2019
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Dong, Jiaao (author)
In order to achieve redundancy and improve the robustness of an autonomous driving system, radar is a suitable choice for road user detection task in severe working conditions (e.g. darkness, bad weather). However, the real-time multi-class radar based road user detection algorithm is less explored compared with camera and LiDAR solutions. To...
master thesis 2019
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Janssens, Martin (author)
Today's leading projections of climate change predicate on Atmospheric General Circulation Models (GCMs). Since the atmosphere consists of a staggering range of scales that impact global trends, but computational constraints prevent many of these scales from being directly represented in numerical simulations, GCMs require "parameterisations'' -...
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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Bassem Tarek Abdelraheem Elsayed Safieldeen, Bassem (author)
We present a powerful approach for learning about uncomputability and undecidability in informationtheory. Our approach is to use automata from automata theory that have undecidable properties toconstruct channels for which an information-theoretic quantity is uncomputable or undecidable. Wedemonstrate this approach by showing that, for channels...
master thesis 2019
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Driessen, Tom (author)
An appropriate understanding of a machine's competences may be critical for safe use. Sharing measures of real-time function reliability could help users to adjust their reliance on machine capabilities. We designed a vibrotactile interface that communicates spatiotemporal information about surrounding events and further encodes a representation...
master thesis 2019
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Valentini, Carlo (author)
Machine Learning Control is a control paradigm that applies Artificial Intelligence methods to control problems. Within this domain, the field of Reinforcement Learning (RL) is particularly promising, since it provides a framework in which a control policy does not have to be programmed explicitly, but can be learned by an intelligent controller...
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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Yoon, Ahhyun (author)
Demand for machine learning is ever-growing in today’s business. Situated at the convergence point of big data and Artificial Intelligence (AI), machine learning allows companies not only to unlock hidden insights from the data deluge but also to fundamentally revolutionize their products and services. Recognizing the opportunities, industrial...
master thesis 2019
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Torres Di Zeo, Alvaro (author)
The availability of photolithography machines is key in the semiconductor industry, as downtime generally incurs in immense economic loss. Time to market is also very important for suppliers of photolithography systems, such as ASML. Photolithography machines include numerous measurement systems that are frequently used for qualification and...
master thesis 2019
Searched for: subject:"machine"
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