Results 181 to 190 of about 790,770 (385)
The different tiling of 12-fold rosettes in Moroccan geometric art [PDF]
Youssef Aboufadil +5 more
openalex +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri +6 more
wiley +1 more source
A new mathematical model for tiling finite regions of the plane with polyominoes
Marcus R. Garvie, John Burkardt
openalex +2 more sources
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source
Torque‐Transmitting Architected Metamaterials for Flexible and Extendable Tubular Robotics
Soft and continuum robots commonly rely on fluid, tendon, or rod‐based power transmissions, to control robotic form and actuation. This study presents an architected structure, based on patterned straight‐line mechanisms, that enables simultaneous bending, extending, and torsionally rigid (BETR) transmission.
Sawyer Thomas, Aman Garg, Jeffery Lipton
wiley +1 more source
Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +1 more source
Flippable tilings of constant curvature surfaces
François Fillastre +1 more
openalex +2 more sources

