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van den Belt, Glenn (author)Earthquakes can have tremendous effects. They can result in casualties, massive damage, and hurt the economy. Therefore, one would like to predict earthquakes as early as possible and with the highest accuracy possible. This paper contains the proposal for the optimal prediction-time, which is the time between the execution of a prediction and...bachelor thesis 2022
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Glynis, Konstantinos (author)Water utilities face many challenges, including pipe bursts that cause significant non-revenue water losses. Detecting those bursts early is important for the water sector in its path to achieve sustainable water resource management. This study presents a scalable data-driven methodology for burst detection in water distribution systems that is...master thesis 2022
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van Ulsen, Hidde (author)Image registration is a fundamental requirement for many medical applications. In recent years, deep learning approaches for registration have shown to be a promising alternative to conventional methods. However, most learning based methods do not consider the different physical properties of various tissues, which can result in unrealistic...master thesis 2022
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Karayalçin, Sengim (author)Some of the most prominent types of attacks against modern cryptographic implementations are side-channel attacks. These attacks leverage some unintended, often physical, leakage of the implementation to retrieve secret information. In recent times, a large part of the focus of side-channel research has been on deep learning methods. These...master thesis 2022
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Zhou, H. (author)Applying deep neural networks (DNNs) for system identification (SYSID) has attracted more andmore attention in recent years. The DNNs, which have universal approximation capabilities for any measurable function, have been successfully implemented in SYSID tasks with typical network structures, e.g., feed-forward neural networks and recurrent...doctoral thesis 2022
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Petsch, Carmen (author)Traffic flow predictions are an important component in the rising demand for solutions to cope with the increasing pressure on transportation networks. Especially on a long prediction horizon, traffic flow predictions remain challenging due to the complex, nonlinear nature of traffic flow and the influence of both temporal and external features....master thesis 2022
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Bastek, Jan Hendrik (author), Kumar, Siddhant (author), Telgen, Bastian (author), Glaesener, Raphaël N. (author), Kochmann, Dennis M. (author)Inspired by crystallography, the periodic assembly of trusses into architected materials has enjoyed popularity for more than a decade and produced countless cellular structures with beneficial mechanical properties. Despite the successful and steady enrichment of the truss design space, the inverse design has remained a challenge: While...journal article 2022
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Wang, Dandan (author), Xu, Jinlan (author), Gao, Fei (author), Wang, C.C. (author), Gu, Renshu (author), Lin, Fei (author), Rabczuk, Timon (author), Xu, Gang (author)In this paper, a deep learning framework combined with isogeometric analysis (IGA for short) called IGA-Reuse-Net is proposed for efficient reuse of numerical simulation on a set of topology-consistent models. Compared with previous data-driven numerical simulation methods only for simple computational domains, our method can predict high...journal article 2022
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Chen, Zhijun (author), Lu, Zhe (author), Chen, Qiushi (author), Zhong, Hongliang (author), Zhang, Yishi (author), Xue, J. (author), Wu, Chaozhong (author)Short-term traffic flow prediction is a core branch of intelligent traffic systems (ITS) and plays an important role in traffic management. The graph convolution network (GCN) is widely used in traffic prediction models to efficiently handle the graphical structural data of road networks. However, the influence weights among different road...journal article 2022
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Allahabadi, H. (author), Amann, J. (author), Balot, I. (author), Beretta, A. (author), Binkley, C. (author), Bozenhard, J. (author), Bruneault, F. (author), Brusseau, J. (author), Umbrello, S. (author)This article’s main contributions are twofold: 1) to demonstrate how to apply the general European Union’s High-Level Expert Group’s (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does “trustworthy AI” mean at the time of the COVID-19 pandemic. To this end, we...journal article 2022
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Wu, L. (author), Perin, G. (author), Picek, S. (author)In the last decade, machine learning-based side-channel attacks have become a standard option when investigating profiling side-channel attacks. At the same time, the previous state-of-the-art technique, template attack, started losing its importance and was more considered a baseline to compare against. As such, most of the results reported...journal article 2022
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Lin, Y. (author), Wiersma, R.T. (author), Pintea, S. (author), Hildebrandt, K.A. (author), Eisemann, E. (author), van Gemert, J.C. (author)Deep learning has improved vanishing point detection in images. Yet, deep networks require expensive annotated datasets trained on costly hardware and do not generalize to even slightly different domains, and minor problem variants. Here, we address these issues by injecting deep vanishing point detection networks with prior knowledge. This...conference paper 2022
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Perin, G. (author), Wu, L. (author), Picek, S. (author)One of the main promoted advantages of deep learning in profiling side-channel analysis is the possibility of skipping the feature engineering process. Despite that, most recent publications consider feature selection as the attacked interval from the side-channel measurements is pre-selected. This is similar to the worst-case security...journal article 2022
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Ganguly, Amlan (author), Abadal, Sergi (author), Thakkar, Ishan (author), Enright Jerger, Natalie (author), Riedel, Marc (author), Babaie, M. (author), Balasubramonian, Rajeev (author), Sebastian, Abu (author), Pasricha, Sudeep (author), Taskin, Baris (author)The computing world is witnessing a proverbial Cambrian explosion of emerging paradigms propelled by applications, such as artificial intelligence, big data, and cybersecurity. The recent advances in technology to store digital data inside a deoxyribonucleic acid (DNA) strand, manipulate quantum bits (qubits), perform logical operations with...journal article 2022
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Pérez-Dattari, Rodrigo (author), Ferreira de Brito, B.F. (author), de Groot, O.M. (author), Kober, J. (author), Alonso-Mora, J. (author)The successful integration of autonomous robots in real-world environments strongly depends on their ability to reason from context and take socially acceptable actions. Current autonomous navigation systems mainly rely on geometric information and hard-coded rules to induce safe and socially compliant behaviors. Yet, in unstructured urban...journal article 2022
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Yang, Ximei (author), Guendel, Ronny (author), Yarovoy, Alexander (author), Fioranelli, F. (author)Human activities classification in assisted living is one of the emerging applications of radar. The conventional analysis considers micro-Doppler signatures as the chosen input for feature extraction or deep learning classification algorithms, or, less frequently, other radar data formats such as the range-time, the range-Doppler, or the...conference paper 2022
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Xing, Xuejun (author), Guo, Jianwei (author), Nan, L. (author), Gu, Qingyi (author), Zhang, Xiaopeng (author), Yan, Dong Ming (author)The point pair feature (PPF) is widely used in industrial applications for estimating 6D poses of known objects from unrecognized point clouds. The key to the success of PPF matching is to establish correct 3D correspondences between the object and the scene, i.e., finding as many valid similar point pairs as possible. Thus, a set of...journal article 2022
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Xiao, C. (author), Lin, H.X. (author), Leeuwenburgh, O. (author), Heemink, A.W. (author)History matching can play a key role in improving geological characterization and reducing the uncertainty of reservoir model predictions. Application of reservoir history matching is restricted by the huge computational cost by amongst others the many runs of the full model. Surrogate models with a reduced complexity are therefore used to...journal article 2022
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Castillo, J.M. (author), Arif, M. (author), Starmans, M.P.A. (author), Niessen, W.J. (author), Bangma, C.H. (author), Schoots, Ivo G. (author), Veenland, J.F. (author)The computer-aided analysis of prostate multiparametric MRI (mpMRI) could improve significant-prostate-cancer (PCa) detection. Various deep-learning-and radiomics-based methods for significant-PCa segmentation or classification have been reported in the literature. To be able to assess the generalizability of the performance of these methods,...journal article 2022
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Jeon, Jaemin (author), Kim, Jaeyong (author), Lee, Jong Jun (author), Shin, D. (author), Kim, Yoon Young (author)This study presents a new modeling technique to estimate the stiffness matrix of a thin-walled beam-joint structure using deep learning. When thin-walled beams meet at joints, significant sectional deformations occur, such as warping and distortion. These deformations should be considered in the one-dimensional beam analysis, but it is...journal article 2022