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Liang, M. (author)
Since the introduction of cementitious materials, shrinkage-induced earlyage cracking (EAC) has emerged as a significant issue that negatively influences the function, durability, and aesthetics of concrete structures like dams, tunnels, and underground garages. This thesis aims to develop new experimental and modelling techniques that help...
doctoral thesis 2024
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Ale Ebrahim Dehkordi, Molood (author)
In society, institutions are the foundation that governs human behaviour through rules, norms, and regulations. The actions and interactions of individuals are shaped by these institutions, forming a cyclic system with numerous parameters and factors. Altering any of these factors, triggers the entire system to transition into a new state that...
doctoral thesis 2024
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Xiao, Y. (author)
Additively manufacturing can bring opportunities and risk factors to the aerospace industry. On one hand, additive manufacturing allows the manufacturing of structures with geometries that are difficult or impossible to fabricatewith conventional machining procedures. This geometry flexibility may lead to components with a greater strength-to...
doctoral thesis 2023
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Köylü, T.C. (author)
Machine learning has gained a lot of recognition recently and is now being used in many important applications. However, this recognition was limited in the hardware security area. Especially, very few approaches depend on this powerful tool to detect attacks during operation. This thesis reduces this gap in the field of fault injection attack...
doctoral 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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Ghavamian, F. (author)
We study the acceleration of the finite element method (FEM) simulations using machine learning (ML) models. Specifically, we replace computationally expensive (parts of) FEM models with efficient ML surrogates. We develop three methods to speed up FEM simulations. The primary difference between these models is their degree of intrusion into the...
doctoral thesis 2021
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Prisacaru, Alexandru (author)
This thesis describes a series of experiments, algorithms, and methodology development for implementing Prognostics and Health Management (PHM) in the field of automotive electronics. Furthermore, a new PHM framework is proposed explicitly tailored for the harsh environment electronics. In addition, the entire apparatus is built, such as the...
doctoral thesis 2021
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Ugwuoke, C.I. (author)
The genome is the blueprint of life and has a detailed genotype and phenotype description of any organism. This in itself attributes sensitivity to genetic data, be it in the biological or electronic format. The possibility of sequencing the genome has opened doors to further probing of the data in its electronic form. Post sequencing of the...
doctoral thesis 2021
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Coppola, M. (author)
The paradigm of swarm robotics aims to enable several independent robots to collaborate together toward collective goals. The distributed nature of a swarm, whereby each robot acts independently in accordance with its perceived environment, is expected to provide the system with a high degree of flexibility, robustness, and scalability. However,...
doctoral thesis 2021
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Makrodimitris, S. (author)
Billions of people world-wide rely on plant-based food for their daily energy intake. As global warming and the spread of diseases (such as the banana Panama disease) is substantially hindering the cultivation of plants, the need to develop temperature- and/or disease-resistant varieties is getting more and more pressing. The field of plant...
doctoral thesis 2021
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Virgolin, M. (author)
Machine learning is impacting modern society at large, thanks to its increasing potential to effciently and effectively model complex and heterogeneous phenomena. While machine learning models can achieve very accurate predictions in many applications, they are not infallible. In some cases, machine learning models can deliver unreasonable...
doctoral thesis 2020
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Bliek, L. (author)
Beamforming is a signal processing technique used in highly directional antennas. An array of antenna elements transmits the same signal, but with a different time delay for each element. By providing the right time delays for each antenna element, the whole array transmits a high-powered signal in one desired direction. This technique can be...
doctoral thesis 2019
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Zhang, Y. (author)
Among all the contributors to fatal accidents, in-flight loss of control (LOC-I) remains one of the largest categories, as indicated by statistics of investigations into past civil aircraft accidents. In flight LOC generally refers to accidents in which the flight crew was unable to maintain control of the aircraft in flight, resulting in an...
doctoral thesis 2019
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Bijl, H.J. (author)
Wind turbines are growing bigger to becomemore cost-efficient. This does increase the severity of the vibrations that are present in the turbine blades, both due to predictable effects like wind shear and tower shadow, and due to less predictable effects like turbulence and flutter. If wind turbines are to become bigger and more cost-efficient,...
doctoral thesis 2018
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Tajalizadehkhoob, S. (author)
In theory, hosting providers can play an important role in fighting cybercrime and misuse. This is because many online threats, be they high-profile or mundane, use online storage infrastructure maintained by hosting providers at the core of their criminal operations. <br/>However, in practice, we see large differences in the security measures...
doctoral thesis 2018
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Delipetrev, B. (author)
Reservoir operation is a multi-objective optimization problem traditionally solved with dynamic programming (DP) and stochastic dynamic programming (SDP) algorithms. The thesis presents novel algorithms for optimal reservoir operation named nested DP (nDP), nested SDP (nSDP), nested reinforcement learning (nRL) and their multi-objective (MO)...
doctoral thesis 2016
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Cheplygina, V. (author)
Multiple instance learning (MIL) is an extension of supervised learning where the objects are represented by sets (bags) of feature vectors (instances) rather than individual feature vectors. For example, an image can be represented by a bag of instances, where each instance is a patch in that image. Only bag labels are given, however, the...
doctoral thesis 2015
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Van den Berg, B.A. (author)
The development of high-throughput measurement techniques resulted in rapidlyincreasing amounts of biological data, which made computational methodsessential for biological research. Hence, the field of bioinformatics emergedthat since plays an important role in storing, making accessible, integrating,and analysing different types of biological...
doctoral thesis 2015
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Rudinac, S. (author)
To facilitate finding of relevant information in ever-growing multimedia collections, a number of multimedia information retrieval solutions have been proposed over the past years. The essential element of any such solution is the relevance criterion deployed to select or rank the items from a multimedia collection to be presented to the user....
doctoral thesis 2013
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Li, Y. (author)
Scale is an important parameter of images. Different objects or image structures (e.g. edges and corners) can appear at different scales and each is meaningful only over a limited range of scales. Multi-scale analysis has been widely used in image processing and computer vision, serving as the basis for many high-level image analysis systems....
doctoral thesis 2013
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