Results 151 to 160 of about 533,476 (267)

Universal Gripper for Industrial Manipulation With Enhanced Rigid Mechanics and Self‐Adaptable Fingers

open access: yesAdvanced Robotics Research, EarlyView.
An enhanced universal gripper combining rigid mechanics with self‐adaptable fingers is presented for industrial automation. The novel six‐bar linkage with integrated compliant pad eliminates mechanical interference while enabling passive shape adaptation.
Muhammad Usman Khalid   +7 more
wiley   +1 more source

Characterization of the heterogeneity in SARS-CoV-2 fitness dynamics via graph representation learning. [PDF]

open access: yesPLoS Comput Biol
Wang Z   +14 more
europepmc   +1 more source

Signed graph representation learning for functional-to-structural brain network mapping. [PDF]

open access: yesMed Image Anal, 2023
Tang H   +9 more
europepmc   +1 more source

A Multidirectional Textile Interface for Remote Control Using Dynamic Area‐Based Capacitance Modulation

open access: yesAdvanced Robotics Research, EarlyView.
Here, we present a textile, wearable capacitive interface enabling multidirectional remote control by dynamically modulating electrode overlap and spacing via a freely gliding upper electrode. A forearm‐mounted prototype drives robotic and media tasks with 12–15 ms latency, maintains < 0.8% drift after 500 cycles, and remains stably functional at 90 ...
Cagatay Gumus   +8 more
wiley   +1 more source

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

open access: yesAdvanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang   +5 more
wiley   +1 more source

Multi‐Site Transfer Classification of Major Depressive Disorder: An fMRI Study in 3335 Subjects

open access: yesAdvanced Science, EarlyView.
The study proposes graph convolution network with sparse pooling to learn the hierarchical features of brain graph for MDD classification. Experiment is done on multi‐site fMRI samples (3335 subjects, the largest functional dataset of MDD to date) and transfer learning is applied, achieving an average accuracy of 70.14%.
Jianpo Su   +14 more
wiley   +1 more source

Identifying nutraceutical targets to treat polycystic ovary syndrome using graph representation learning. [PDF]

open access: yesNPJ Womens Health
Hanassab S   +10 more
europepmc   +1 more source

Home - About - Disclaimer - Privacy