Results 111 to 120 of about 1,143,945 (288)
Exploring Euclidean and Non-Euclidean Geometry
The Elements, compiled by Euclid, covers Greek plane and solid geometry and number theory using the axiomatic method. His work provided a foundation for many notable mathematicians of the time to delve deeper into the axiomatic approach in geometry.
Galvinhill, Caroline
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ABSTRACT Magnetic 2‐dimensional (2D) van der Waals (vdW) materials have garnered tremendous attention. The vdW ferromagnet Fe5Ge1Te2 has a Curie temperature Tc of ≈ 270 K, which is tailorable by tuning the stoichiometry and the Fe deficiency to reach room temperature.
Chih‐Yu Lee +7 more
wiley +1 more source
The intrinsic geometry of a convex surface in Galilean space
This paper investigates the intrinsic geometry of a convex surface in the Galilean space. The Galilean space, as a special case of a pseudo-Euclidean space, possesses a degenerate metric.
A. Artykbaev, B.M. Sultanov
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A compact passive engineered surface converts changes in microwave frequency into many distinct illumination patterns, allowing nearby objects to be imaged without mechanical scanning, active tuning, or a large antenna array. Operating from 18 to 28 GHz, the single‐port system uses measured field patterns to reconstruct metallic targets and distinguish
Mohammed H. Arif +6 more
wiley +1 more source
Physical Unclonable Functions From Microwave Metasurface Fingerprints
Nominally identical metasurfaces fabricated through standard PCB processes inevitably contain microscopic fabrication imperfections. This work demonstrates that these unavoidable electromagnetic deviations can serve as unique physical unclonable fingerprints for wireless authentication.
Guanxiong Shen +4 more
wiley +1 more source
Critical issues in the design of the school geometry curriculum
The fundamental problem in the design of the geometry component of the mathematics curriculum is simply that there is too much interesting geometry, more than can be reasonably included in the mathematics curriculum.
Jones, Keith
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Cross-subject electroencephalography (EEG) emotion recognition poses a fundamental challenge for brain-computer interfaces due to two factors: the non-Euclidean geometry of EEG spatial covariance matrices and the substantial inter-subject variability in ...
Yun Gao, Hai Deng
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Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
AI‐based tools enable rapid characterization of bacterial ultrastructure in low‐dose cryogenic transmission electron microscopy. The envelope thickness tool quantifies membrane thickness and anisotropy. The flagella module analyzes filament morphology and detects cell‐flagella contacts.
Sita Sirisha Madugula +10 more
wiley +1 more source
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia +2 more
wiley +1 more source

