document

Improving Medical Care for Adults with Intellectual Disabilities (ID): Can Automated Processing of Electronic Health Record Clinical Text Assist in ID Detection Among the General Outpatient Population?

Rijs, Joyce (author)

<b>Background</b>: Undetected Intellectual Disability (ID) can lead to chronic stress due to overestimation by society. Chronic stress can cause stress-related health issues, like hypertension, chronic fatigue and abdominal complaints. When a physician (General Practitioner (GP) or medical specialist) does not recognize that a patient has ID,...

master thesis 2024

document

AI-Assisted Design & Optimization for Predictive Maintenance: A Case Study using Deep Learning and Search Metaheuristics for Structural Health Monitoring in Aviation

Ewald, Vincentius (author)

One of the classical solutions to maintain the aircraft structural integrity is to rely on the analysis of non-destructive testing (NDT) inspector with various inspection methods. However, it is relatively expensive in matter of time and costs to train human resources until the certification is reached. Further, in majority of the cases of...

doctoral thesis 2023

document

Control of Dynamical Systems via Deep Kernel Learning

Tan, Martin (author)

In the field of Systems and Control, optimal control problem-solving for complex systems is a core task. The development of accurate mathematical models to represent these systems’ dynamics is often difficult. This complexity comes from potential uncertainties, complex non-linearities, or unknown factors that might affect the system. Because of...

master thesis 2023

document

Decoding EEG signals

Dai, Anthony (author), van de Weg, Joris (author)

In the context of designing a real-time brain-computer interface for playing a game using the OpenBCI Ultracortex "Mark IV" headset, this paper focuses on the work of the decoding subgroup. The primary responsibility is to analyse EEG data retrieved from the OpenBCI headset and classify the intention of the user. Our objective is to achieve a...

bachelor thesis 2023

document

Data-driven optimal control for safe quadrotor navigation in windy environments

Probst, Johanna (author)

Creating autonomous Micro Aerial Vehicles for executing complex missions poses various challenges, including safe navigation in the presence of external wind disturbances. Most current navigation methods handle external wind disturbances through real-time estimation and rejection algorithms in the control stage, but lack safety guarantees in...

master thesis 2023

document

Continuous People Crowd Monitoring defined as a Regression Problem using Radar Networks

Guendel, Ronny (author), Ullmann, I. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)

Radar-based human activity recognition in crowded environments using regression approaches is addressed. Whereas previous research has focused on single activities and subjects, the problem of continuous activity recognition involving up to five individuals moving in arbitrary directions in an indoor area is introduced. To treat the problem, a...

conference paper 2023

document

Influence and Detection of Vacuum Bag Leakages in Composites Manufacturing

Haschenburger, A.I. (author)

Composites are increasingly used in the aerospace industry due to their lightweight potential and flexible design options. The most widespread manufacturing process for large components made of fibre composites is still the open mould process. In this process, a composite component is placed on a mould and hermetically sealed with a vacuum bag...

doctoral thesis 2022

document

An Empirical Assessment on the Limits of Binary Code Summarization with Transformer-based Models

Al-Kaswan, Ali (author)

Reverse engineering binaries is required to understand and analyse programs for which the source code is unavailable. Decompilers can transform the largely unreadable binaries into a more readable source code-like representation. However, many aspects of source code, such as variable names and comments, are lost during the compilation and...

master thesis 2022

document

Digital Soil Mapping based on PDFs of Cone Penetration Tests and Vibro Cores using Image Processing and Machine Learning

Ordeman, Sam (author)

Digital Soil Mapping (DSM) of soil types in geotechnical project areas is a top priority. These maps are often used in decision making and can have significant consequences related to costs and risks. Usually, these maps are generated by digital soil models that interpolate soil types at known locations. In practice, conventional spatial...

master thesis 2022

document

CatIss: An Intelligent Tool for Categorizing Issues Reports using Transformers

Izadi, M. (author)

Users use Issue Tracking Systems to keep track and manage issue reports in their repositories. An issue is a rich source of software information that contains different reports including a problem, a request for new features, or merely a question about the software product. As the number of these issues increases, it becomes harder to manage...

conference paper 2022

document

Learning-Based Model Predictive Control for a Wind-Powered Fresh Water Production Plant with Integrated Electricity Production

van Hanswijk, Daniel (author)

Growth of the population, industry and agriculture increases the demand for fresh water. However, with only a small portion of the water on earth being suitable for direct human use and consumption, this growth makes water scarcity an increasing problem. Seawater desalination is an effective method to counter such water stress. Reverse Osmosis ...

master thesis 2021

document

Reinforcement Learning approach for decision-making in driver control shifting for semi-autonomous driving

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

document

Preparing Stance Detection: Feature Extraction Methods and Their Performance Used for Feature-Based Machine Learning Algorithms

Vass, Kristóf (author)

Stance detection is a Natural Language Processing task that aims to detect the stance (support, agreement, or disagreement) of a piece of text towards some target. In this paper, we aim to find the best performing pair of feature extraction method and feature-based machine learning algorithm. By doing so, an explainable method can be found to...

bachelor thesis 2021

document

Gaussian Process Regression for Data-Driven Model Predictive Control

Seco Rodrigues, Nuno António (author)

Systems and Control deals with modelling and control design of many different types of systems with different behaviour and characteristics. Often times it is challenging to build mathematical models to describe the system dynamics due to limited knowledge of the underlying system, complex nonlinearities, or the existence of unknown exogenous...

master thesis 2021

document

“What is OUV” revisited: A computational interpretation on the statements of outstanding universal value

Bai, N. (author), Nourian, Pirouz (author), Luo, Renqian (author), Pereira Roders, A. (author)

The Statements of Outstanding Universal Value (OUV) concerns the core justification for nominating and inscribing cultural and natural heritage properties on the UNESCO World Heritage List, ever since 2007. Ten criteria are specified and measured independently for the selection process. The 2008 ICOMOS Report “What is OUV” has been a successful...

journal article 2021

document

Measuring Cybercrime as a Service (CaaS) Offerings in a Cybercrime Forum

Akyazi, U. (author), van Eeten, M.J.G. (author), Hernandez Ganan, C. (author)

The emergence of Cybercrime-as-a-Service (CaaS) is a critical evolution in the cybercrime landscape. A key area of research on CaaS is where and how the supply of CaaS is being matched with demand. Next to underground marketplaces and custom websites, cybercrime forums provide an important channel for CaaS suppliers to attract customers. Our...

conference paper 2021

document

Design of a reconfigurable metamaterial with the use of Bayesian optimization and machine learning

Kasprzyk, Szymon (author)

Metamaterials are a relatively new group of materials whose behaviour strongly depends on the design of their internal structure. They can be employed in a wide range of applications, one of which is presented in this thesis. As cardiovascular diseases account for around 30% of deaths worldwide the research done in the field of Materials Science...

master thesis 2020

document

Surrogate Constitutive Models with Multi-fidelity Gaussian Processes for Composite Micromodels

Turan, O.T. (author)

Various engineering applications rely on efficient, high performance materials to overcome design challenges. This high performance can be achieved by engineering micro-heterogenous materials also known as composites. Since the behavior of composites relies heavily on micro-scale interactions between different components, modeling...

master thesis 2020

document

Conversation Quality: Modeling in Free-Standing Conversational Groups

Laxminarayanan Raj Prabhu, N. (author)

Social interactions in general are multifaceted and there exists an wide set of factors and events that influence them. Hence, interactions as a social phenomena have been studied by researchers in the fields of psychology and social signal processing from different stand points. The common trend in literature is to perform an in-depth study on...

master thesis 2020

document

Human activity classification with radar signal processing and machine learning

Jia, Mu (author), Li, Shaoxuan (author), Le Kernec, Julien (author), Yang, Shufan (author), Fioranelli, F. (author), Romain, Olivier (author)

As the number of older adults increases worldwide, new paradigms for indoor activity monitoring are required to keep people living at home independently longer. Radar-based human activity recognition has been identified as a sensing modality of choice because it is privacy-preserving and does not require end-users compliance or manipulation. In...

conference paper 2020