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Llasag Rosero, Raúl (author), Silva, Catarina (author), Ribeiro, Bernardete (author), Santos, Bruno F. (author)Artificial Intelligence (AI) is transforming the future of industries by introducing new paradigms. To address data privacy and other challenges of decentralization, research has focused on Federated Learning (FL), which combines distributed Machine Learning (ML) models from multiple parties without exchanging confidential information....journal article 2024
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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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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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Tselentis, D. (author), Papadimitriou, E. (author), van Gelder, P.H.A.J.M. (author)Recent research in transport safety focuses on the processing of large amounts of available data by means of intelligent systems, in order to decrease the number of accidents for transportation users. Several Machine Learning (ML) and Artificial Intelligence (AI) applications have been developed to address safety problems and improve efficiency...journal article 2023
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Aleebrahimdehkordi, M. (author), Lechner, J.M. (author), Ghorbani, Amineh (author), Nikolic, I. (author), Chappin, E.J.L. (author), Herder, P.M. (author)Agent-based modelling and simulation (ABMS), whether simple toy models or complex data-driven ones, is regularly applied in various domains to study the system-level patterns arising from individual behaviour and interactions. However, ABMS still faces diverse challenges such as modelling more representative agents or improving computational...journal article 2023
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Jung, Jiwon (author), Kim, K. (author), Peters, T. (author), Snelders, H.M.J.J. (author), Kleinsmann, M.S. (author)Designers are increasingly collaborating with data scientists to apply smart data technologies to understand large-scale user behavior during their design research. This is useful in specific impact domains with vulnerable users and unfamiliar contexts, such as healthcare design. Patient journey mapping is the most common design tool for...journal article 2023
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Tselentis, D. (author), Papadimitriou, E. (author)This study reviews the Artificial Intelligence and Machine Learning approaches developed thus far for driver profile and driving pattern recognition, representing a set of macroscopic and microscopic behaviors respectively, to enhance the understanding of human factors in road safety, and therefore reduce the number of crashes. It provides a...journal article 2023
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Kamel Targhi, Elahe (author), Emami Niri, Mohammad (author), Zitha, P.L.J. (author)Cross-linked polymer gel is widely used in the oil and gas industry to block high permeability conduits and reduce water cut. The complex nature of this fluid, especially regarding flow in porous media, makes its numerical simulation very time-consuming. This study presents an approach to designing an Artificial Neural Network (ANN) model...journal article 2023
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Forouzandeh Shahraki, N. (author), Zomorodian, Zahra Sadat (author), Tahsildoost, Mohammad (author), Shaghaghian, Zohreh (author)Recent studies have focused on data-driven methods for building energy efficiency, by using simulated or empirical data, for energy-based design assessment rather than the common physics-based techniques, which are mostly time-consuming. In this paper, the feasibility of using seven different Machine Learning models, including three single...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
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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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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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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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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
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Haakman, Mark (author), Cruz, Luis (author), Huijgens, H.K.M. (author), van Deursen, A. (author)Tech-leading organizations are embracing the forthcoming artificial intelligence revolution. Intelligent systems are replacing and cooperating with traditional software components. Thus, the same development processes and standards in software engineering ought to be complied in artificial intelligence systems. This study aims to understand the...journal article 2021
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Nurunnabi, A. (author), Teferle, F. N. (author), Li, J. (author), Lindenbergh, R.C. (author), Parvaz, S. (author)Semantic segmentation of point clouds is indispensable for 3D scene understanding. Point clouds have credibility for capturing geometry of objects including shape, size, and orientation. Deep learning (DL) has been recognized as the most successful approach for image semantic segmentation. Applied to point clouds, performance of the many DL...journal article 2021
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Dahle, F. (author), Arroyo Ohori, G.A.K. (author), Agugiaro, G. (author), Briels, Sven (author)In many countries digital maps are generally created and provided by Cadastre, Land Registry or National Mapping Agencies. These maps must be accurate and well maintained. However, in most cases, the update process of these maps is still done by hand, often using satellite or aerial imagery. Supporting this process via automatic change...journal article 2021
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Kudina, O. (author), de Boer, Bas (author)Rationale: This paper aims to show how the focus on eradicating bias from Machine Learning decision-support systems in medical diagnosis diverts attention from the hermeneutic nature of medical decision-making and the productive role of bias. We want to show how an introduction of Machine Learning systems alters the diagnostic process....journal article 2021
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Coraddu, A. (author), Kalikatzarakis, M. (author), Oneto, L. (author), Meijn, G. J. (author), Godjevac, M. (author), Geertsma, R.D. (author)Condition Based Maintenance on diesel engines can help to reduce maintenance load and better plan maintenance activities in order to support ships with reduced or no crew. Diesel engine performance models are required to predict engine performance parameters in order to identify emerging failures early on and to establish trends in...journal article 2018