Results 111 to 120 of about 1,143,945 (288)

Exploring Euclidean and Non-Euclidean Geometry

open access: yes, 2018
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
core   +1 more source

Combinatorial Survey of Structural Phase Distribution and Magnetism in Fe‐Ge‐Te Composition‐Spread Thin Film Libraries

open access: yesAdvanced Electronic Materials, EarlyView.
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

open access: yesҚарағанды университетінің хабаршысы. Математика сериясы
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
doaj   +1 more source

Broadband Near‐Field Computational Microwave Imaging Enabled by Nonperiodic Dispersive Unit‐Cell Loading in a Passive Metasurface

open access: yesAdvanced Electronic Materials, EarlyView.
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

open access: yesAdvanced Electronic Materials, EarlyView.
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

open access: yes, 2000
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
core   +1 more source

Cross-subject EEG emotion recognition using Riemannian Graph Transformers with Geodesic Adversarial Adaptation

open access: yesAlexandria Engineering Journal
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
doaj   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

open access: yesAdvanced Intelligent Discovery, EarlyView.
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: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

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