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Reed, Robert (author), Laurenti, L. (author), Lahijanian, Morteza (author)Deep Kernel Learning (DKL) combines the representational power of neural networks with the uncertainty quantification of Gaussian Processes. Hence, it is potentially a promising tool to learn and control complex dynamical systems. In this letter, we develop a scalable abstraction-based framework that enables the use of DKL for control...journal article 2023
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Kartal, S. (author)Spatiotemporal time series prediction plays a crucial role in a wide range of applications. However, in most of the studies, spatial information was ignored and predictions were carried out either on a few points or on average values. In this study, 37 different configurations of 4 traditional ML models and 3 Neural Network (NN) based models...journal article 2023
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Wenzel, P.A. (author), Jovanovic, Raka (author), Schulte, F. (author)Ensuring the accuracy of the estimated time of arrival (ETA) information for ships approaching ports and inland terminals is increasingly critical today. Waterway transportation plays a vital role in freight transportation and has a significant ecological impact. Improving the accuracy of ETA predictions can enhance the reliability of inland...conference paper 2023
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Fang, G. (author)Soft robots that are built from materials with mechanical properties similar to those of living tissues can achieve tasks like never before in comparison to conventional rigid robots. Powered by the compliance of soft materials and novel structure designs, complex motion (e.g., bending, twisting, and extension) can be accomplished in robotic...doctoral thesis 2022
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Hehn, T.M. (author)that do not require any action from the drivers for a short period of time. Although these systems are still limited and only reliable in certain situations, it shows the general trend: cars will become more and more autonomous. The reasons why people and companies are eagerly anticipating fully autonomous cars are manifold: self-driving...doctoral thesis 2022
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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
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van der Waa, J.S. (author)As a society, we have come to notice the influence and impact Artificially Intelligent (AI) agents have on the way we live our lives. For these AI agents to support us both effectively and responsibly, we require an understanding on how they make decisions and what the consequences are of these decisions. The research _field of Explainable...doctoral thesis 2022
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Zhang, T. (author)Fine-grained emotion recognition is the process of automatically identifying the emotions of users at a fine granularity level, typically in the time intervals of 0.5s to 4s according to the expected duration of emotions. Previous work mainly focused on developing algorithms to recognize only one emotion for a video based on the user feedback...doctoral thesis 2022
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Meister, S. (author)In modern aircraft, structural lightweight composite components are increasingly<br/>used. To manufacture these components in a costeffective way, robust production systems for the manufacturing of complex fibre composite components are necessary. A rather novel but already established process for fibre material deposition is the Automated Fibre...doctoral thesis 2022
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Delfos, J. (author), Zuiderwijk-van Eijk, A.M.G. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)As the application of machine learning (ML) algorithms becomes more widespread, governmental organisations try to benefit from this technology. While ML has the potential to support public services, its application also introduces challenges. Several scholars have described the possible opportunities and challenges of ML applications in the...conference paper 2022
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Tang, Ruifan (author), De Donato, Lorenzo (author), Bešinović, Nikola (author), Flammini, Francesco (author), Goverde, R.M.P. (author), Lin, Zhiyuan (author), Liu, Ronghui (author), Tang, Tianli (author), Vittorini, Valeria (author), Wang, Z. (author)Nowadays it is widely accepted that Artificial Intelligence (AI) is significantly influencing a large number of domains, including railways. In this paper, we present a systematic literature review of the current state-of-the-art of AI in railway transport. In particular, we analysed and discussed papers from a holistic railway perspective,...review 2022
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Dahle, F. (author), Tanke, Julian (author), Wouters, B. (author), Lindenbergh, R.C. (author)A huge archive of historical images of the Antarctica taken by the US Navy between 1940 and 2000 is publicly available. These images have not yet been used for large-scale computer-driven analysis as they were captured with analog cameras. They were only later digitized and contain no semantic information. Most modern deep-learning based...journal article 2022
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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
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Mir, S.A.M. (author), Latoskinas, Evaldas (author), Proksch, S. (author), Gousios, G. (author)Dynamic languages, such as Python and Javascript, trade static typing for developer flexibility and productivity. Lack of static typing can cause run-time exceptions and is a major factor for weak IDE support. To alleviate these issues, PEP 484 introduced optional type annotations for Python. As retrofitting types to existing code-bases is...conference paper 2022
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Zhang, H. (author), Cruz, Luis (author), van Deursen, A. (author)The popularity of machine learning has wildly expanded in recent years. Machine learning techniques have been heatedly studied in academia and applied in the industry to create business value. However, there is a lack of guidelines for code quality in machine learning applications. In particular, code smells have rarely been studied in this...conference paper 2022
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Bellizio, Federica (author), Bugaje, Al Amin B. (author), Cremer, Jochen (author), Strbac, Goran (author)Machine Learning (ML) for real-time Dynamic Security Assessment (DSA) promises a probabilistic approach to secure lower safety margins and costs. However, future systems with a high share of renewables have low inertia and converter-interfaced devices resulting in faster dynamics. Past research on ML-based DSA used high inertia systems to...journal article 2022
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Murray-Rust, D.S. (author), Nicenboim, I. (author), Lockton, D (author)In this paper, we explore the use of metaphors for people working with artificial intelligence, in particular those that support designers in thinking about the creation of AI systems. Metaphors both illuminate and hide, simplifying and connecting to existing knowledge, centring particular ideas, marginalising others, and shaping fields of...conference paper 2022
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Valchev, I. (author), Coraddu, A. (author), Oneto, L. (author), Kalikatzarakis, M. (author), Tiddens, W. (author), Geertsma, R.D. (author)Deterministic models based on the laws of physics, as well as data-driven models, are often used to assess the current state of vessels and their systems, as well as predict their future behaviour. Predictive maintenance methodologies (i.e., Condition Based Maintenance) and advanced control strategies (i.e., Model Predictive Control) are...journal article 2022
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Apruzzese, Giovanni (author), Pajola, Luca (author), Conti, M. (author)Enhancing Network Intrusion Detection Systems (NIDS) with supervised Machine Learning (ML) is tough. ML-NIDS must be trained and evaluated, operations requiring data where benign and malicious samples are clearly labeled. Such labels demand costly expert knowledge, resulting in a lack of real deployments, as well as on papers always relying...journal article 2022
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A Two-Step Feature Extraction Algorithm: Application to deep learning for point cloud classificationNurunnabi, A. (author), Teferle, F. N. (author), Laefer, D. F. (author), Lindenbergh, R.C. (author), Hunegnaw, A. (author)Most deep learning (DL) methods that are not end-to-end use several multi-scale and multi-type hand-crafted features that make the network challenging, more computationally intensive and vulnerable to overfitting. Furthermore, reliance on empirically-based feature dimensionality reduction may lead to misclassification. In contrast, efficient...journal article 2022