document

Real-time Adaptive Nonlinear MPC for Collision Imminent Control and Planning in Automated Vehicles: Enforcing constraints and utilizing the full control potential

Trip, Kenrick (author)

With the introduction of autonomous vehicles on public roads, their performance in emergency situations has become a strong focus. Collision Imminent Control (CIC) concerns the planning and control of aggressive evasive maneuvers for collision avoidance of automated vehicles. CIC is implemented using adaptive Nonlinear Model Predictive Control ...

master thesis 2024

document

Elaine: Elaborations of Higher-Order Effects as First-Class Language Feature

Diepraam, Terts (author)

Algebraic effects and handlers have become a popular abstraction for effectful computation, with implementations even in mainstream programming languages, such as OCaml. The operations of an algebraic effect define the syntax of the effect, while handlers define the semantics. This provides modularity, because we can choose which handler to...

master thesis 2023

document

Elastic gradient boosting decision trees under limited labels by sequential epistemic uncertainty quantification: Elastic CatBoost Uncertainty (eCBU)

Sennema, Erik (author)

Intrusion detection systems (IDSs) are essential for protecting computer systems and networks from malicious attacks. However, IDSs face challenges in dealing with dynamic and imbalanced data, as well as limited label availability. In this thesis, we propose a novel elastic gradient boosting decision tree algorithm, namely Elastic CatBoost...

master thesis 2023

document

Comparing Static Semantics Specifications for the IceDust DSL: A Case Study of Statix

Tilro, Jesse (author)

Reusable tools for engineering software languages can bridge the gap between formal specification and implementation, lowering the bar for engineers to design and implement programming languages. Among such tools belong NaBL2 and its successor Statix, which are meta-languages for declaratively specifying the static semantics of programming...

master thesis 2023

document

Computing the Scanwidth of Directed Acyclic Graphs

Holtgrefe, Niels (author)

Phylogenetic networks are a specific type of directed acyclic graph (DAG), used to depict evolutionary relationships among, for example, species or other groups of organisms. To solve computationally hard problems, treewidth has been used to parametrize algorithms in phylogenetics. In the hope of simplifying the algorithmic design process, Berry...

master thesis 2023

document

VoBERT: Unstable Log Sequence Anomaly Detection: Introducing Vocabulary-Free BERT

Hofman, Daan (author)

With the ever-increasing digitalisation of society and the explosion of internet-enabled devices with the Internet of Things (IoT), keeping services and devices secure is becoming more important. Logs play a critical role in sustaining system reliability. Manual analysis of logs has become increasingly difficult, accelerating the development of...

master thesis 2023

document

Speeding up program synthesis using specification discovery

de Jong, Jaap (author)

How convenient would it be to have an AI that relieves us programmers from the burden of coding? Program synthesis is a technique that achieves exactly that: it automatically generates simple programs that meet a given set of examples or adhere to a provided specification. This is often done by enumerating all programs in the search space and...

master thesis 2023

document

Bootstrapping the statix meta-language

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

document

Combining Multi-Objective Planning with Reinforcement Learning to Solve Complex Tasks in Environments with Sparse Rewards

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

document

Hierarchical Clustering Based State Abstraction In Reinforcement Learning

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

document

Pacing regulation for runners

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

document

Extracting LLVM Intermediate Representation from Agda

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

document

Agda2Rust: A Study on an Alternative Backend for the Agda Compiler

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

document

Code extraction from Agda to HVM

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

document

Code Extraction from a Dependently Typed Language to a Stack Based Language

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

document

Gaze-Based Activity Recognition with a LSTM

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

document

Cognitive activity recognition by analyzing eye movement with convolutional neural networks

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

document

Eye tracking-based Sedentary Activity Recognition with Conventional Machine Learning Algorithms

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

document

Eye Tracking-Based Desktop Activity Recognition with Conventional Machine Learning

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

document

Optimizing Shunting Operations: A case-study at Kijfhoek shunting yard

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