Results 131 to 140 of about 144,902 (310)
Natural fliers achieve remarkable aerial performance through diverse wing neuromechanical systems integrating actuation, sensing, and control. This study synthesizes neuromechanical architectures in insects and hummingbirds, identifying two key functional types‐Dual Neural‐Mechanical Oscillator and Neurally‐modulated Mechanical Oscillator‐ and ...
Suyash Agrawal +4 more
wiley +1 more source
Learning Generalized Relational Heuristic Networks for Model-Agnostic Planning
Rushang Karia, Siddharth Srivastava
openalex +2 more sources
Heuristic Algorithms for Placing Geomagnetically Induced Current Blocking Devices [PDF]
Minseok Ryu +5 more
openalex +1 more source
This study introduces a biomarker‐agnostic diagnostic strategy for ovarian cancer, utilizing a machine learning‐enhanced electronic nose to analyze volatile organic compound signatures from blood plasma. By overcoming the dependence on specific biomarkers, this approach enables accurate detection, staging, and cancer type differentiation, offering a ...
Ivan Shtepliuk +4 more
wiley +1 more source
The Jump‐Enhancing Textile Suit integrates the Pneumatic Energy‐Storing Propulsion Actuator (PESPA) and the Triarticular Kinetic‐Chained Structure (TKiCS). PESPA stores elastic energy under pneumatic pressure and releases it during the propulsive phase to augment movement.
Sunghun Kim +5 more
wiley +1 more source
A computational framework for optimizing strain sensor placement in wearable motion tracking systems is presented. By combining dense strain mapping with a genetic algorithm, the method discovers counterintuitive yet highly effective configurations that reduce joint angle error by 32%.
Minu Kim +4 more
wiley +1 more source
Metalearning‐based inverse optimization enables precise microscale three‐dimensional printing using a DLP system. Distorted structures from conventional printing are analyzed via neural network regression, which predicts optimal exposure time and mask design.
Jae Won Choi +3 more
wiley +1 more source
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
Interactive Tool for Customizing Hydrogel Properties in Practical Applications
This research provides an open‐access tool that enables the scientific community to optimally synthesize hydrogels without requiring expert knowledge, thereby reducing experimental costs. Soft materials represent an interdisciplinary frontier in modern science, combining theoretical and experimental knowledge from diverse fields in both fundamental ...
Ricardo Negrete‐Gallego +5 more
wiley +1 more source

