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Lei Yang, Mengxue Xu and Yunan He
Convolutional Neural Networks (CNNs) have become essential in deep learning applications, especially in computer vision, yet their complex internal mechanisms pose significant challenges to interpretability, crucial for ethical applications. Addressing t...
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Athanasios Bakalis, Triantafyllos Makarios and Vassilis Lekidis
The seismic damage in reinforced concrete bridges is identified in this study using the ?M and P? hybrid technique initially developed for planar frames, where M signifies ?Monitoring? and P denotes ?Pushover analysis?. The proposed methodology involves ...
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Sheng Zhang, Yuguang Bai, Youwei Zhang and Dan Zhao
Hypersonic vehicles or engines usually employ complex thermal protecting shells. This sometimes brings multi-physics difficulties, e.g., thermal-aeroelastic problems like panel flutter etc. This paper aims to propose a novel optimization method versus th...
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Gleice Kelly Barbosa Souza, Samara Oliveira Silva Santos, André Luiz Carvalho Ottoni, Marcos Santos Oliveira, Daniela Carine Ramires Oliveira and Erivelton Geraldo Nepomuceno
Reinforcement learning is an important technique in various fields, particularly in automated machine learning for reinforcement learning (AutoRL). The integration of transfer learning (TL) with AutoRL in combinatorial optimization is an area that requir...
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Shweta More, Moad Idrissi, Haitham Mahmoud and A. Taufiq Asyhari
The rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As a result, it is crucial for compani...
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