Results 191 to 200 of about 497,650 (327)

On approximation and energy estimates for delta 6-convex functions. [PDF]

J Inequal Appl, 2018
Saleem MS, Pečarić J, Rehman N, Khan MW, Zahoor MS.   +4 more
europepmc   +1 more source

Design and Fabrication of High Dielectric GRIN Lens for a Directive Antenna Using a Hybrid Filled Voxel Additive Manufacturing Technique

Advanced Materials Technologies, EarlyView.
Hybrid‐filled voxel AM enables integration of high‐permittivity materials into additively manufactured devices. Using this approach, a graded refractive index (GRIN) lens is demonstrated, achieving a 50% antenna size reduction with enhanced directivity.
Qianfang Zheng, Anna Radkovskaya, Kailun Xu, Ekaterina Shamonina, Patrick S. Grant   +4 more
wiley   +1 more source

Boundary values of Hankel and Toeplitz determinants for q -convex functions. [PDF]

MethodsX
Hadi SH, Shaba TG, Madhi ZS, Darus M, Lupaş AA, Tchier F.   +5 more
europepmc   +1 more source

Integral inequalities for some convex functions via generalized fractional integrals. [PDF]

J Inequal Appl, 2018
Mehreen N, Anwar M.
europepmc   +1 more source

On norm sub-additivity and super-additivity inequalities for concave and\n convex functions [PDF]

, 2010
Koenraad M. R. Audenaert, Jaspal Singh Aujla   +1 more
openalex   +1 more source

Advanced Emissivity Tuning Via Femtosecond Laser Surface Engineering

Advanced Optical Materials, EarlyView.
Femtosecond laser surface processing (FLSP) is employed to fabricate titanium‐based metamaterials with engineered micro/nano‐scale features that exhibit spectrally selective and omnidirectional thermal emissivity. By integrating advanced ellipsometry, electromagnetic modeling, and compositional analysis, the work reveals resonance‐driven emissivity ...
Zahra Kamali Khanghah, Andrew Butler, Andrew Reicks, Juveriya Parmar, Eva Schubert, Craig Zuhlke, Mathias Schubert, Ufuk Kilic, Mohammad Ghashami   +8 more
wiley   +1 more source

Canonical Models on Strongly Convex Domains via the Squeezing Function [PDF]

, 2020
Amedeo Altavilla, Leandro Arosio, Lorenzo Guerini   +2 more
openalex   +1 more source

Inverse Design in Nanophotonics via Representation Learning

Advanced Optical Materials, EarlyView.
This review frames machine learning (ML) in nanophotonics through a classification based on where ML is applied. We categorize methods as either output‐side, which create differentiable surrogates for solving Maxwell's partial differential equations (PDEs), or input‐side, which learn compact representations of device geometry.
Reza Marzban, Ali Adibi, Raphaël Pestourie   +2 more
wiley   +1 more source

Janowski type close-to-convex functions associated with conic regions. [PDF]

J Inequal Appl, 2017
Mahmood S, Arif M, Malik SN.
europepmc   +1 more source

New Hermite-Hadamard Type Inequalities for Twice Differentiable\n Composite $(h-s)_2$-Convex Functions [PDF]

, 2016
Peter Olamide Olanipekun, Adesanmi Alao Mogbademu   +1 more
openalex   +1 more source