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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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Ossenkoppele, B.W. (author), Luijten, Ben (author), Bera, Deep (author), de Jong, N. (author), Verweij, M.A. (author), van Sloun, Ruud J.G. (author)
There is an increased desire for miniature ultrasound probes with small apertures to provide volumetric images at high frame rates for in-body applications. Satisfying these increased requirements makes simultaneous achievement of a good lateral resolution a challenge. As micro-beamforming is often employed to reduce data rate and cable count...
journal article 2023
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Nastos Konstantopoulos, C. (author), Komninos, P. (author), Zarouchas, D. (author)
A hybrid methodology based on numerical and non-destructive experimental schemes, which is able to predict the structural level strength of composite laminates is proposed on the current work. The main objective is to predict the strength by substituting the up to failure experiments with non-destructive experiments where the investigated...
journal article 2023
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Song, Yang (author), Wang, H. (author), Frøseth, Gunnstein (author), Nåvik, Petter (author), Liu, Zhigang (author), Rønnquist, Anders (author)
The interaction performance of the pantograph-catenary is of great importance as it directly determines the current collection quality and operational safety of trains. The finite element method (FEM) is dominantly used for simulating pantograph-catenary interaction, which is normally computationally heavy. In this work, addressing the...
journal article 2023
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Madadi, B. (author), Correia, Gonçalo (author)
This study proposes a hybrid deep-learning-metaheuristic framework with a bi-level architecture for road network design problems (NDPs). We train a graph neural network (GNN) to approximate the solution of the user equilibrium (UE) traffic assignment problem and use inferences made by the trained model to calculate fitness function...
journal article 2023
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Abdellatif, Alaa Awad (author), Mhaisen, N. (author), Mohamed, Amr (author), Erbad, Aiman (author), Guizani, Mohsen (author)
The rise of chronic disease patients and the pandemic pose immediate threats to healthcare expenditure and mortality rates. This calls for transforming healthcare systems away from one-on-one patient treatment into intelligent health systems, leveraging the recent advances of Internet of Things and smart sensors. Meanwhile, reinforcement...
journal article 2023
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Tabatabaeian, A. (author), Jerkovic, Bruno (author), Harrison, Philip (author), Marchiori, Elena (author), Fotouhi, M. (author)
Visual inspection is one of the most common non-destructive testing (NDT) methods that offers a fast evaluation of surface damage in aerospace composite structures. However, it is highly dependent on human-related factors and may not detect barely visible impact damage (BVID). In this research, low velocity impact tests with different energy...
journal article 2023
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Huang, Y. (author), Yu, S. Suihuai (author), Chu, J. Jianjie (author), Fan, H. Hao (author), Du, B. Bin (author)
Cultural heritage management poses significant challenges for museums due to fragmented data, limited intelligent frameworks, and insufficient applications. In response, a digital cultural heritage management approach based on knowledge graphs and deep learning algorithms is proposed to address the above challenges. A joint entity-relation...
journal article 2023
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Abolfazli, Amir (author), Spiegelberg, Jakob (author), Anand, A. (author), Palmer, Gregory (author)
Configurable software systems have become increasingly popular as they enable customized software variants. The main challenge in dealing with configuration problems is that the number of possible configurations grows exponentially as the number of features increases. Therefore, algorithms for testing customized software have to deal with the...
conference paper 2023
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Sharma, Bhawana (author), Sharma, Lokesh (author), Lal, C. (author), Roy, Satyabrata (author)
Internet of Things (IoT) applications are growing in popularity for being widely used in many real-world services. In an IoT ecosystem, many devices are connected with each other via internet, making IoT networks more vulnerable to various types of cyber attacks, thus a major concern in its deployment is network security and user privacy. To...
journal article 2023
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Glynis, K.G. (author), Kapelan, Z. (author), Bakker, Martijn (author), Taormina, R. (author)
Researchers and engineers employ machine learning (ML) tools to detect pipe bursts and prevent significant non-revenue water losses in water distribution systems (WDS). Nonetheless, many approaches developed so far consider a fixed number of sensors, which requires the ML model redevelopment and collection of sufficient data with the new...
journal article 2023
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Cardaioli, Matteo (author), Conti, M. (author), Orazi, Gabriele (author), Tricomi, Pier Paolo (author), Tsudik, Gene (author)
Authentication and de-authentication phases should occur at the beginning and end of secure user sessions, respectively. A secure session requires the user to pass the former, but the latter is often underestimated or ignored. Unattended or dangling sessions expose users to well-known Lunchtime Attacks. To mitigate this threat, researchers...
journal article 2023
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Esmi, Nima (author), Golshan, Yasaman (author), Asadi, Sara (author), Shahbahrami, A. (author), Gaydadjiev, G. (author)
The COVID-19 disease pandemic spread rapidly worldwide and caused extensive human death and financial losses. Therefore, finding accurate, accessible, and inexpensive methods for diagnosing the disease has challenged researchers. To automate the process of diagnosing COVID-19 disease through images, several strategies based on deep learning,...
journal article 2023
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Yin, Xilin (author), Wang, H. (author), Pisano, F. (author), Gavin, Kenneth (author), Askarinejad, A. (author), Zhou, Hongpeng (author)
Predicting the non-linear loading response is the key to the design of suction caissons. This paper presents a systematic study to explore the applicability of deep learning techniques in foundation design. Firstly, a series of three-dimensional finite element simulations was performed, covering a wide range of embedment ratios and different...
journal article 2023
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Nasri, Maedeh (author), Fang, Zhizhou (author), Baratchi, Mitra (author), Englebienne, Gwenn (author), Wang, Shenghui (author), Koutamanis, A. (author), Rieffe, Carolien (author)
Detecting and analyzing group behavior from spatio-temporal trajectories is an interesting topic in various domains, such as autonomous driving, urban computing, and social sciences. This paper revisits the group detection problem from spatio-temporal trajectories and proposes “WavenetNRI”, a graph neural network (GNN) based method. The...
conference paper 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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de Boer, Jurrian (author)
Recent advancements in quantification of repair outcomes of CRISPR-Cas9 mediated double-stranded DNA breaks (DSBs) have allowed for the use of machine learning for predicting the frequencies of these repair outcomes. Local DNA sequence context influences the frequencies of mutations that arise when DNA gets repaired after it is targeted by...
master thesis 2022
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de Wolf, Tijmen (author)
Heart failure is a leading cause of death and forms a growing health concern. The development of novel drugs is however hampered by the absence of adequate screening methods and disease models. Cardiomyocytes derived from patients could assist in the development of a patient specific drug screen method to test the efficacy and safety of putative...
master thesis 2022
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Wang, Zhiyi (author)
Deep-learning models are commonly used in short-term precipitation forecasting. However, most deep-learning models are likely to produce blurry output problems. In order to get realistic and accurate results, AENN, a variant of Generative Adversarial Networks (GANs), has been developed. The AENN implements an additional temporal discriminator to...
master thesis 2022
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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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