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Demirel, Omer Burak (author), Yaman, Burhaneddin (author), Shenoy, Chetan (author), Moeller, Steen (author), Weingärtner, S.D. (author), Akçakaya, Mehmet (author)
Purpose: To develop a physics-guided deep learning (PG-DL) reconstruction strategy based on a signal intensity informed multi-coil (SIIM) encoding operator for highly-accelerated simultaneous multislice (SMS) myocardial perfusion cardiac MRI (CMR). Methods: First-pass perfusion CMR acquires highly-accelerated images with dynamically varying...
journal article 2022
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Estebanez Camarena, M. (author), Taormina, R. (author), van de Giesen, N.C. (author), ten Veldhuis, Marie-claire (author)
Food and economic security in West Africa rely heavily on rainfed agriculture and are threatened by climate change and demographic growth. Accurate rainfall information is therefore crucial to tackling these challenges. Particularly, information about the occurrence and length of droughts as well as the onset date of the rainy season is...
journal article 2023
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Perin, G. (author), Wu, L. (author), Picek, S. (author)
The adoption of deep neural networks for profiling side-channel attacks opened new perspectives for leakage detection. Recent publications showed that cryptographic implementations featuring different countermeasures could be broken without feature selection or trace preprocessing. This success comes with a high price: an extensive...
journal article 2023
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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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Pahlavani, H. (author), Tsifoutis-Kazolis, Kostas (author), Cruz Saldivar, M. (author), Mody, Prerak (author), Zhou, J. (author), Mirzaali, Mohammad J. (author), Zadpoor, A.A. (author)
Practical applications of mechanical metamaterials often involve solving inverse problems aimed at finding microarchitectures that give rise to certain properties. The limited resolution of additive manufacturing techniques often requires solving such inverse problems for specific specimen sizes. Moreover, the candidate microarchitectures...
journal article 2023
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Wilbrand, K. (author), Taormina, R. (author), ten Veldhuis, Marie-claire (author), Visser, Martijn (author), Hrachowitz, M. (author), Nuttall, Jonathan (author), Dahm, Ruben (author)
Streamflow predictions remain a challenge for poorly gauged and ungauged catchments. Recent research has shown that deep learning methods based on Long Short-Term Memory (LSTM) cells outperform process-based hydrological models for rainfall-runoff modeling, opening new possibilities for prediction in ungauged basins (PUB). These studies usually...
journal article 2023
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Zhu, S. (author), Yarovoy, Alexander (author), Fioranelli, F. (author)
The problem of instantaneous ego-motion estimation with mm-wave automotive radar is studied. DeepEgo, a deep learning-based method, is proposed for achieving robust and accurate ego-motion estimation. A hybrid approach that uses neural networks to extract complex features from input point clouds and applies weighted least squares (WLS) for...
journal article 2023
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Rivera-Arbeláez, José M. (author), Keekstra, Danjel (author), Cofiño-Fabres, Carla (author), Boonen, Tom (author), Dostanic, M. (author), ten Den, Simone A. (author), Vermeul, Kim (author), Mastrangeli, Massimo (author), van den Berg, A (author)
The high rate of drug withdrawal from the market due to cardiovascular toxicity or lack of efficacy, the economic burden, and extremely long time before a compound reaches the market, have increased the relevance of human in vitro models like human (patient-derived) pluripotent stem cell (hPSC)-derived engineered heart tissues (EHTs) for the...
journal article 2023
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Picek, S. (author), Perin, G. (author), Mariot, L. (author), Wu, L. (author), Batina, Lejla (author)
Side-channel attacks represent a realistic and serious threat to the security of embedded devices for already almost three decades. A variety of attacks and targets they can be applied to have been introduced, and while the area of side-channel attacks and their mitigation is very well-researched, it is yet to be consolidated. Deep learning...
journal article 2023
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Pastor Serrano, O. (author), Habraken, S.J.M. (author), Hoogeman, M.S. (author), Lathouwers, D. (author), Schaart, D.R. (author), Nomura, Yusuke (author), Xing, Lei (author), Perko, Z. (author)
Objective. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. To assess the need for adaptation, motion models can be used to simulate dominant motion patterns and assess anatomical robustness before delivery. Traditionally, such models are based on principal...
journal article 2023
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Huang, Charles (author), Vasudevan, Varun (author), Pastor Serrano, O. (author), Islam, Md Tauhidul (author), Nomura, Yusuke (author), Dubrowski, Piotr (author), Wang, Jen Yeu (author), Schulz, Joseph B. (author), Yang, Yong (author)
Objective. In this work, we propose a content-based image retrieval (CBIR) method for retrieving dose distributions of previously planned patients based on anatomical similarity. Retrieved dose distributions from this method can be incorporated into automated treatment planning workflows in order to streamline the iterative planning process....
journal article 2023
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Wu, L. (author), Weissbart, L.J.A. (author), Krcek, M. (author), Li, H. (author), Perin, G. (author), Batina, Lejla (author), Picek, S. (author)
The efficiency of the profiling side-channel analysis can be significantly improved with machine learning techniques. Although powerful, a fundamental machine learning limitation of being data-hungry received little attention in the side-channel community. In practice, the maximum number of leakage traces that evaluators/attackers can obtain is...
journal article 2023
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Huang, Y. (author), Yu, Suihuai (author), Chu, Jianjie (author), Su, Zhaojing (author), Zhu, Yaokang (author), Wang, Hanyu (author), Wang, Mengcheng (author), Fan, Hao (author)
Design knowledge is critical to creating ideas in the conceptual design stage of product development for innovation. Fragmentary design data, massive multidisciplinary knowledge call for the development of a novel knowledge acquisition approach for conceptual product design. This study proposes a Design Knowledge Graph-aided (DKG-aided)...
journal article 2023
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Estebanez Camarena, M. (author), Curzi, Fabio (author), Taormina, R. (author), van de Giesen, N.C. (author), ten Veldhuis, Marie-claire (author)
West African food systems and rural socio-economics are based on rainfed agriculture, which makes society highly vulnerable to rainfall uncertainty and frequent floods and droughts. Reliable rainfall information is currently missing. There is a sparse and uneven rain gauge distribution and, despite continuous efforts, rainfall satellite products...
journal article 2023
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Stone, Emilie (author), Giani, Stefano (author), Zappalá, D. (author), Crabtree, C.J. (author)
Effective and timely health monitoring of wind turbine gearboxes and generators is essential to reduce the costs of operations and maintenance activities, especially offshore. This paper presents a scalable and lightweight convolutional neural network (CNN) framework using high-dimensional raw condition monitoring data for the automatic...
journal article 2023
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Zheng, Feifei (author), Yin, Hang (author), Ma, Yiyi (author), Duan, Huan Feng (author), Gupta, Hoshin (author), Savic, Dragan (author), Kapelan, Z. (author)
Under global climate change, urban flooding occurs frequently, leading to huge economic losses and human casualties. Extreme rainfall is one of the direct and key causes of urban flooding, and accurate rainfall estimates at high spatiotemporal resolution are of great significance for real-time urban flood forecasting. Using existing rainfall...
journal article 2023
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Zhang, Jinlei (author), Chen, Yijie (author), Krishnakumari, P.K. (author), Jin, Guangyin (author), Wang, Chengcheng (author), Yang, Lixing (author)
Accurate and reliable short- term passenger flow prediction can support operations and decision-making of the URT system from multiple perspectives. In this paper, we propose a URT multi- step short- term passenger flow prediction model at the network level based on a Transformer-based LSTM network, Depth-wise Attention Block, and CNN network...
journal article 2023
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Joseph, G. (author), Zhong, Chen (author), Gursoy, M. Cenk (author), Velipasalar, Senem (author), Varshney, Pramod (author)
We address the problem of sequentially selecting and observing processes from a given set to find the anomalies among them. The decision-maker observes a subset of the processes at any given time instant and obtains a noisy binary indicator of whether or not the corresponding process is anomalous. We develop an anomaly detection algorithm that...
journal article 2023
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Oyibo, P.O. (author), Meulah, Brice (author), Bengtson, Michel (author), Lieshout, Lisette van (author), Oyibo, Wellington (author), Diehl, J.C. (author), Vdovin, Gleb (author), Agbana, T.E. (author)
Purpose: Automated diagnosis of urogenital schistosomiasis using digital microscopy images of urine slides is an essential step toward the elimination of schistosomiasis as a disease of public health concern in Sub-Saharan African countries. We create a robust image dataset of urine samples obtained from field settings and develop a two-stage...
journal article 2023
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Hirtreiter, E.J. (author), Schulze Balhorn, L. (author), Schweidtmann, A.M. (author)
Developing Piping and Instrumentation Diagrams (P&IDs) is a crucial step during process development. We propose a data-driven method for the prediction of control structures. Our methodology is inspired by end-to-end transformer-based human language translation models. We cast the control structure prediction as a translation task where...
journal article 2023
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