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Rahmani, S. (author), Baghbani, Asiye (author), Bouguila, Nizar (author), Patterson, Zachary (author)
Graph neural networks (GNNs) have been extensively used in a wide variety of domains in recent years. Owing to their power in analyzing graph-structured data, they have become broadly popular in intelligent transportation systems (ITS) applications as well. Despite their widespread applications in different transportation domains, there is no...
journal article 2023
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Bafti, Alireza Ghaderi (author), Ahmadi, Arman (author), Abbasi, A. (author), Kamangir, Hamid (author), Jamali, Sadegh (author), Hashemi, Hossein (author)
Actual evapotranspiration (ET<sub>a</sub>) plays a crucial role in the water and energy cycles of the earth. An accurate estimate of the ET<sub>a</sub> is essential for management of the water resources, agriculture, and irrigation, as well as research on atmospheric variations. Despite the importance of accurate ET<sub>a</sub> values,...
journal article 2023
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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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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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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
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Cuperman, Rafael (author), Jansen, K.M.B. (author), Ciszewski, M.G. (author)
Action statistics in sports, such as the number of sprints and jumps, along with the details of the corresponding locomotor actions, are of high interest to coaches and players, as well as medical staff. Current video-based systems have the disadvantage that they are costly and not easily transportable to new locations. In this study, we...
journal article 2022
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Mostafavi, F. (author), Tahsildoost, Mohammad (author), Zomorodian, Zahra Sadat (author), Shahrestani, Seyed Shayan (author)
Purpose: In this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the decision-making process at the early-stage design. Design/methodology/approach: A methodology using an image-based deep learning model called pix2pix is proposed...
journal article 2022
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Li, Fang (author), Li, Xueyuan (author), Liu, Qi (author), Li, Z. (author)
Pedestrian detection is an important branch of computer vision, and it has important applications in the fields of autonomous driving, artificial intelligence and video surveillance.With the rapid development of deep learning and the proposal of large-scale datasets, pedestrian detection has reached a new stage and achieves better performance...
journal article 2022
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Smirnova, Alisa (author), Yang, J. (author), Yang, Dingqi (author), Cudre-Mauroux, Philippe (author)
Noisy labels represent one of the key issues in supervised machine learning. Existing work for label noise reduction mainly takes a probabilistic approach that infers true labels from data distributions in low-level feature spaces. Such an approach is not only limited by its capability to learn high-quality data representations, but also by...
journal article 2022
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Viana, Paula (author), Andrade, Maria Teresa (author), Carvalho, Pedro (author), Vilaça, Luis (author), Teixeira, Inês N. (author), Costa, Tiago (author), Jonker, P.P. (author)
Applying machine learning (ML), and especially deep learning, to understand visual content is becoming common practice in many application areas. However, little attention has been given to its use within the multimedia creative domain. It is true that ML is already popular for content creation, but the progress achieved so far addresses...
journal article 2022
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Mohammadpourfard, Mostafa (author), Weng, Yang (author), Khalili, Abdullah (author), Genc, Istemihan (author), Shefaei, A. (author), Mohammadi-Ivatloo, Behnam (author)
The expansion of power systems over large geographical areas renders centralized processing inefficient. Therefore, the distributed operation is increasingly adopted. This work introduces a new type of attack against distributed state estimation of power systems, which operates on inter-area boundary buses. We show that the developed attack...
journal article 2022
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