Results 151 to 160 of about 22,494 (297)

The Passive Film Growth Mechanism of New Corrosion-Resistant Steel Rebar in Simulated Concrete Pore Solution: Nanometer Structure and Electrochemical Study. [PDF]

Materials (Basel), 2017
Jiang JY, Wang D, Chu HY, Ma H, Liu Y, Gao Y, Shi J, Sun W.   +7 more
europepmc   +1 more source

Corrosion Resistance of Zinc Phosphated HRB400 Steel in Simulated Concrete Pore Solution

International Journal of Electrochemical Science, 2022
Guan Xiaoyan, Jiao Huili
openaire   +1 more source

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
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, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Autonomous Robotic Colonoscopy: A Supervised Learning Approach for Enhanced Navigation and Collision Detection

Advanced Intelligent Systems, EarlyView.
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, Dae Kyung Sohn, Seonggun Joe, Byungkyu Kim   +3 more
wiley   +1 more source

Physical Reservoir Computing for Smart Manufacturing of PCB Using Crystallinity‐Controlled HfO2 Memristor for Reservoir

Advanced Intelligent Systems, EarlyView.
We address multilayer PCB anomaly detection for smart manufacturing by physical reservoir computing with HfO2‐based memristors. Crystallinity‐tuned HfO2 suppresses ferroelectricity while preserving the high‐k insulating state and confers strong short‐term memory.
Yongho Lee, Wonhee Lee, Junho Shin, Noah Jang, Hyunjun Kim, Da Ye Kim, Jinkyung Kim, June Soo Kim   +7 more
wiley   +1 more source

Upsampling DINOv2 Features for Unsupervised Vision Tasks and Weakly Supervised Materials Segmentation

Advanced Intelligent Systems, EarlyView.
Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty, Antonis Vamvakeros, Samuel J. Cooper   +2 more
wiley   +1 more source

Pitting corrosion of 304 L stainless steel welds in simulated concrete pore solutions

工程科学学报, 2015
The pitting corrosion of 304 L austenitic stainless steel joints with 308 L austenitic stainless steel as welding sticks was investigated in simulated concrete pore solutions with different chloride ion concentrations by potentiodynamic polarization curves, electrochemical impedance spectroscopy and Mott-Schottky curves.
LI Li, DONG Chao-fang, GAO Shu-jun, YAO Ji-zheng, XIAO Kui, LI Xiao-gang   +5 more
openaire   +1 more source

Deep Reinforcement Learning Approaches for Sensor Data Collection by a Swarm of UAVs

Advanced Intelligent Systems, EarlyView.
This article presents four decentralized reinforcement learning algorithms for autonomous data harvesting and investigates how collaboration improves collection efficiency. It also presents strategies to minimize training times by improving model flexibility, enabling algorithms to operate with varying number of agents and sensors.
Thiago de Souza Lamenza, Bruno José Olivieri de Souza, Markus Endler   +2 more
wiley   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates

Advanced Intelligent Systems, EarlyView.
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin, Rudolf M. Füchslin, Achille Giacometti, Helmut Hauser, Marco Werner   +4 more
wiley   +1 more source