A Qualitative Analysis of Vehicle Positioning Requirements for Connected Vehicle Applications [PDF]
Barth, Matthew, Williams, Nigel
core
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Voice-controlled autonomous navigation for smart wheelchairs using ROS-based SLAM. [PDF]
Benayed W, Masmoudi MS.
europepmc +1 more source
The Role of the Institution of Navigation Education Regarding Safety Navigation
openaire +1 more source
Navigation System For Female Safety
Kalyanasundaram C +3 more
openaire +1 more source
Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale +6 more
wiley +1 more source
Comparison of the Accuracy of Marker Screw-Assisted Pedicle Screw Placement in Thoracic and Lumbar Spine to 3D Navigation: A Randomized Controlled Study. [PDF]
Khashab MA +3 more
europepmc +1 more source
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang +14 more
wiley +1 more source
Robotic-assisted bronchoscopy in dye localization in thoracoscopic pulmonary nodule resection: An initial experience. [PDF]
Wang X +6 more
europepmc +1 more source
MGDP: Mastering a Generalized Depth Perception Model for Quadruped Locomotion
ABSTRACT Perception‐based Deep Reinforcement Learning (DRL) controllers demonstrate impressive performance on challenging terrains. However, existing controllers still face core limitations, struggling to achieve both terrain generality and platform transferability, and are constrained by high computational overhead and sensitivity to sensor noise.
Yinzhao Dong +9 more
wiley +1 more source

