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Janssen, Boris (author)
The Statix meta-language has been developed in order to simplify the definition of static semantics in programming languages. A high-level static semantics definition of a language in Statix can be used to generate a type-checker, hence abstracting over the shared implementation details. Statix should be able to express the static semantics of...
master thesis 2023
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van Rijn, Cas (author)
Sequential decision-making problems are problems where the goal is to find a sequence of actions that complete a task in an environment. A particularly difficult type of sequential decision-making problem to solve is one in which the environment has sparse rewards, a large state space, and where the goal is to complete a complex task. In this...
master thesis 2023
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Liu, Yang (author)
Reinforcement learning (RL) has grown tremendously over one and a half decades and is increasingly emerging in many real-life applications. However, the application of RL is still limited due to its low training efficiencies and surplus training cost. The sampling and computation complexity normally depends on the size of the state space and...
master thesis 2022
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Molano Valencia, Juan Esteban (author)
By increasing the step frequency of the runners, it is possible to reduce the risk of injuries due to overload. Techniques like auditory pacing help the athletes to have better control over their step frequency. Nevertheless, synchronizing to a continuous external rhythm costs energy. For this reason, the use of intermittent pacing may be more...
master thesis 2022
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Broekhoff, Jochem (author)
Agda, a promising dependently typed function language, needs more mainstream adoption. By the process of code extraction, we compile proven Agda code into a popular existing language, allowing smooth integration with existing workflows. Due to Agda’s pluggable nature, this process is relatively straightforward. We implement a solution in Haskell...
bachelor thesis 2022
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Milliken, Louis (author)
Dependently typed languages such as Agda can provide users certain guarantees about the correct- ness of the code that they write, however, this comes at the cost of excess code that is not used at run time. Agda code is currently compiled to another language before it is run, there are not many target languages in popular use, so it is unclear...
bachelor thesis 2022
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Meluzzi, Matteo (author)
Dependently typed languages such as Agda have the potential to revolutionize the way we write software because they allow the programmer to catch more bugs at compile time than classical languages. Nonetheless, dependently typed languages are hardly used in practice. One of the reasons is the lack of mature compilers for them.<br/>This paper...
bachelor thesis 2022
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Peeters, Hector (author)
Agda is a functional programming language with built-in support for dependent types. A dependent type depends on a value. This allows the developer to specify strict constraints for the types used in an application. Writing code with dependent types results in fewer type-related errors slipping through the compilation process. <br/>When...
bachelor thesis 2022
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Poeth, Ole (author)
Cognitive processes have been used in recent years for context sensing and this has shown promising results. Multiple sets of features have shown good performance but no set of features has been determined the best for classifying gaze data. This paper looks at different feature sets and the heterogeneity of gaze signals from subjects and...
bachelor thesis 2022
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Chatalbasheva, Violeta (author)
Sedentary activity recognition is an important research field due to its various positive implications in people’s life. This study builds upon previous research which is based on low level features extracted from the gaze signals using a fixation filter and uses a dataset of 24 participants performing 8 different sedentary activities. The main...
bachelor thesis 2022
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Brockbernd, Bob (author)
This research proposes a novel method to classify cognitive behavior based on eye-movement data. Most state-of-the-art approaches use conventional machine learning techniques needing manual feature extraction. This experiment explores the possibility of applying deep learning algorithms to cognitive activity recognition for feature extraction...
bachelor thesis 2022
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Vaessen, Kasper (author)
Classification of sedentary activities using gaze tracking data can be of great use in fields such as teaching, human-computer interaction and surveilling. Conventional machine learning methods such as k-nearest neighbours, random forest and support vector machine might be used to classify such activities, but this requires knowledge about the...
bachelor thesis 2022
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Druijf, Teun (author)
In the current economy, there is an increasing focus on sustainability. Green transport solutions, like rail freight, are becoming more and more popular. We will look into the shunting operations at Kijfhoek shunting yard. This yard functions as the central hub for DB Cargo Nederland and connects the Port of Rotterdam with the hinterland. About...
master thesis 2022
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Weijs, George (author)
Bus bunching is a problem that occurs in many high frequent bus systems. This can be averted by several countermeasures of which holding control is the most popular one in practice. Holding control strategies are often implemented using predefined rules. In this study, multi-agent reinforcement learning is selected to develop an effective...
master thesis 2021
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Monica Sidarta, Monica (author)
Inaccurate truck cycle time (TCT) prediction in earthworks impacts construction projects because more equipment and human resources must be added to complete the project. It also increases fuel consumption and emissions from the machinery. However, the current method gives inaccurate prediction because of subjectivity and human error. <br/>This...
master thesis 2021
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Kreynen, Bernd (author)
Dementia care is a growing problem, both due to a rising number of cases and due to a shortage in healthcare workers. Aside from cognitive symptoms persons with dementia (PwDs) often deal with psychological symptoms such as agitation. The individualized music intervention (IMI) by Linda Gerdner has been proposed to reduce these. This is the...
master thesis 2021
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Latoškinas, Evaldas (author)
Semi-autonomous driving innovations aim to bridge the gap to fully autonomous driving by co-operating with human drivers to lead to optimal choices on who should drive in different scenarios by offering different automation levels. However, in the present day, known semi-autonomous driving solutions do not generalise to every complex case of...
bachelor thesis 2021
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Klop, Pepijn (author), Shah, Mozafar (author), Sitaram, Ashwin (author)
During this project, we have explored the possibilities for an algorithm that can schedule multiple visits taking into consideration constraints and KPIs. The solution we came up with has been integrated into Dropboard and is ready to be used in production by Dropboard’s clients. Our algorithm takes as input the visits to be scheduled. It then...
bachelor thesis 2021
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Ómarsdóttir, Þórunn (author)
In this thesis, we study automatically generating explanatory reports for anomalous incidents in a train control system (TCS) using Natural Language Generation (NLG). A TCS is a type of safety-critical software that allows train controllers to correctly set the tracks for a train to pass. The goal of this research is to process the majority of...
master thesis 2020
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Subramanian, Sai Medha (author)
The de-carbonisation of the energy system, more commonly known as the 'Energy Transition' has a vital role to play in the pursuit of mitigating the climate emergency’s impact. There is a global trend of moving toward making power systems more future-proof and this largely affects the roles and activities of a Transmission System Operator (TSO)...
master thesis 2020
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