Results 91 to 100 of about 135,575 (311)
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Seismic Behaviour of Cast-In-Situ Phosphogypsum-Reinforced Concrete Grid Frame Composite Walls
This paper mainly studies the effect of cast-in-situ phosphogypsum on seismic behaviour of reinforced concrete grid frame. The mechanical behaviour of three reinforced concrete grid frames and four cast-in-situ phosphogypsum-reinforced concrete grid ...
Qin Wu +6 more
doaj +1 more source
Fire responses and resistance of concrete-filled steel tubular frame structures [PDF]
This paper presents the results of dynamic responses and fire resistance of concretefilled steel tubular (CFST) frame structures in fire conditions by using non-linear finite element method.
Buchanan A. H. +8 more
core +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
StrucPy.RCFA- Object-Oriented Python Package for Structural Analysis of Reinforced Concrete Frames
StrucPy.RCFA is an open-source object-oriented Python package, capable of performing structural analysis on reinforced concrete (RC) members and 2D/3D reinforced concrete frames. With the increasing necessity of skill development among young engineers in
Tabish Izhar +3 more
doaj +1 more source
BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan +7 more
wiley +1 more source
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
Time-Dependent Seismic Fragility of RC Moment Frames in Corrosive Environment Considering Concrete Quality [PDF]
Corrosion of steel reinforcement in concrete is a common problem for reinforced concrete buildings in coastal regions. It can have significant impacts on the seismic performance of these buildings.
Mohammad Amiri +4 more
doaj +1 more source
Experimental assessment and retrofit of full-scale models of existing RC frames [PDF]
PSD tests on two full-scale models of existing non-seismic resisting RC frame structures are described. The testing program covered several aspects, namely assessment of seismic performance of existing frames without and with infill panels ...
Molina, J., Pinto, A. V., Varum, H.
core +1 more source
A novel autonomous robotic colonoscopy is introduced through supervised learning approaches. The proposed system consists of 3 degrees of freedom motorized colonoscope with an integrated navigation module that can infer a target steering point and collision probability.
Bohyun Hwang +3 more
wiley +1 more source

