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Eyad K. Sayhood, Nisreen S. Mohammed, Salam J. Hilo and Salih S. Salih
This paper presents comprehensive empirical equations to predict the shear strength capacity of reinforced concrete deep beams, with a focus on improving the accuracy of existing codes. Analyzing 198 deep beams imported from 15 existing investigations, t...
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Ali Reza Ghanizadeh, Mandana Salehi, Anna Mamou, Evangelos I. Koutras, Farhang Jalali and Panagiotis G. Asteris
This paper investigates the effect of subgrade soil stabilization on the performance and life extension of flexible pavements. Several variables affecting soil stabilization were considered, including subgrade soil type (CL or CH), additive type and cont...
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Nenad Marku? and Mirko Su?njevic
Recently, there has been renewed interest in signed distance bound representations due to their unique properties for 3D shape modelling. This is especially the case for deep learning-based bounds. However, it is beneficial to work with polygons in most ...
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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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Tushar Ganguli and Edwin K. P. Chong
We present a novel technique for pruning called activation-based pruning to effectively prune fully connected feedforward neural networks for multi-object classification. Our technique is based on the number of times each neuron is activated during model...
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