Results 201 to 210 of about 1,903,201 (339)

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks

, 2019
Ekaterina Tolstaya, Fernando Gama, James Paulos, George J. Pappas, Vijay Kumar, Alejandro Ribeiro   +5 more
openalex   +1 more source

Reducing Personalization Time and Energy Cost While Walking Outdoors with a Portable Exosuit

Advanced Robotics Research, EarlyView.
Rapid Real‐World Optimization! An AF‐based human‐in‐the‐loop optimization strategy rapidly personalizes a portable hip extension exosuit for incline walking. Real‐time Bayesian optimization of assistive force significantly reduces metabolic energy—up to 16.2%—while converging in just 3 min 24 s.
Kimoon Nam, Saikat Sahoo, Yoosun Kim, Dongmin Go, Jeongho Choo, Cheonkyu Park, Seungtae Yang, Giuk Lee   +7 more
wiley   +1 more source

Dual path fairness optimization for graph neural network based recommendation. [PDF]

Sci Rep
Yang C, Lu K, He J, Huang S, Cheng J.
europepmc   +1 more source

Scalable Quantum Message Passing Graph Neural Networks for Next-Generation Wireless Communications: Architectures, Use Cases, and Future Directions

Le Tung Giang, Nguyen Xuan Tung, Trinh Van Chien, Lajos Hanzo, Won-Joo Hwang   +4 more
openalex   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

Advanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari, Zhaoting Li, Robert Babuška, Jens Kober, Cosimo Della Santina   +4 more
wiley   +1 more source

Multi-Solvent Graph Neural Network for Reduction Potential Prediction Across the Chemical Space. [PDF]

J Chem Inf Model
Fedorov R, Nihei A, Gryn'ova G.
europepmc   +1 more source

Do androids dream of electric sorghum?: Predicting Phenotypes from Multi-Scale Genomic and Environmental Data using Neural Networks and Knowledge Graphs

, 2020
Ryan P. Bartelme, Michael Behrisch, Emily Jean Cain, Remco Chang, Ishita Debnath, Bryan Heidorn, Pankaj Jaiswal, David LeBauer, Ab Mosca, Mónica Muñoz-Torres, Arun Ross, Kent Shefchek, Tyson L. Swetnam, Anne Thessen   +13 more
openalex   +1 more source

Integration of Soft‐Robotics and Deep Learning to Assess the Coordinated Biosonar Emission and Reception Dynamics in Hipposiderid Bats

Advanced Robotics Research, EarlyView.
Combining a biomimetic soft‐robot with deep‐learning data analytics sheds light on a unique peripheral dynamics seen in the biosonar system of bats: Bats modulate their ultrasonic biosonar signals upon emission as well as reception with variable, yet highly coordinated motion patterns of their noseleaves and pinnae.
Shuxin Zhang, Ruihao Wang, Xiaoyan Yin, Luhui Yang, Rolf Müller   +4 more
wiley   +1 more source

Recent Advances in Variable‐Stiffness Robotic Systems Enabled by Phase‐Change Materials

Advanced Robotics Research, EarlyView.
Phase‐change materials (PCMs), such as shape memory alloys, hydrogels, shape memory polymers, liquid crystal elastomers, and low‐melting‐point alloys, are driving advancements in stiffness‐tunable robotic systems across a wide range of applications. This review highlights recent progress in PCM‐enabled robotics, focusing on their underlying mechanisms,
Sukrit Gaira, Liao Wu, Ming Li, Priyank Kumar, Xiaopeng Li, Shi‐Yang Tang   +5 more
wiley   +1 more source