Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Javad Shabanpour"'
Autor:
Javad Shabanpour
Publikováno v:
Advanced Photonics Research, Vol 5, Iss 10, Pp n/a-n/a (2024)
Analog computing based on miniaturized surfaces has gained attention for its high‐speed and low‐power mathematical operations. Building on recent advances, an anisotropic space‐time digital metasurface for parallel and programmable wave‐based
Externí odkaz:
https://doaj.org/article/a2549a29a8ae4dee87fd28b610ece881
Autor:
Sina Beyraghi, Fardin Ghorbani, Javad Shabanpour, Mir Emad Lajevardi, Vahid Nayyeri, Pai-Yen Chen, Omar M. Ramahi
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract This paper studies the feasibility of a deep neural network (DNN) approach for bone fracture diagnosis based on the non-invasive propagation of radio frequency waves. In contrast to previous “semi-automated” techniques, where X-ray image
Externí odkaz:
https://doaj.org/article/35ce103be7b5476e9501aadd26269462
Publikováno v:
IEEE Access, Vol 10, Pp 126253-126268 (2022)
Recently, reconfigurable intelligent surfaces (RISs) gained notable consideration due to their ability to provide efficient and cost-effective wireless communication networks. However, this powerful concept often suffers from simplistic modeling whic
Externí odkaz:
https://doaj.org/article/c8e45d7e07b74f38bcf91ce9bd5acfdf
Autor:
Fardin Ghorbani, Sina Beyraghi, Javad Shabanpour, Homayoon Oraizi, Hossein Soleimani, Mohammad Soleimani
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
Abstract Beyond the scope of conventional metasurface, which necessitates plenty of computational resources and time, an inverse design approach using machine learning algorithms promises an effective way for metasurface design. In this paper, benefi
Externí odkaz:
https://doaj.org/article/6ddb4d8fd4794af39fa08837cff13b83
Publikováno v:
ACS Omega, Vol 4, Iss 10, Pp 14340-14352 (2019)
Externí odkaz:
https://doaj.org/article/30b905e8c07b4462b9834243de429134
Autor:
Javad Shabanpour
Publikováno v:
Journal of Materials Chemistry C. 8:7189-7199
Programmable metasurfaces incorporated with tunable materials controlled by external stimuli can provide an unprecedented degree of freedom in dynamical wave manipulation in real-time. Beyond the scope of isotropic reconfigurable metasurfaces that on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::88d27c52743d93f685019599b72bc6e1
https://doi.org/10.1039/d0tc00689k
https://doi.org/10.1039/d0tc00689k
Autor:
Constantin Simovski, Javad Shabanpour
Publikováno v:
IEEE Access
Publisher Copyright: Author Recently, reconfigurable intelligent surfaces (RISs) gained notable consideration due to their ability to provide efficient and cost-effective wireless communication networks. However, this powerful concept often suffers f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b20c4d59fc6fb0d617391d4aa9e3826
Publikováno v:
ACS Omega
ACS Omega, Vol 4, Iss 10, Pp 14340-14352 (2019)
ACS Omega, Vol 4, Iss 10, Pp 14340-14352 (2019)
Recent years have witnessed an extraordinary spurt in attention toward the wave-manipulating strategies revealed by phase-amplitude metasurfaces. Recently, it has been shown that, when two different phase-encoded metasurfaces responsible for doing se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c94474f15525b507feb881c795544722
http://europepmc.org/articles/PMC6733224
http://europepmc.org/articles/PMC6733224
Publikováno v:
Optics express. 29(10)
We propose a new generation of reprogrammable multi-functional bias encoded metasurfaces for dynamic wave manipulation using liquid crystals (LC). This metadevice is an array of unit-cells based on LCs to provide the desired phase steps based on its
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5417ce9a4d9d4f1e630fa5f2a8ebfc58
https://pubmed.ncbi.nlm.nih.gov/33985174
https://pubmed.ncbi.nlm.nih.gov/33985174
Autor:
Javad Shabanpour, Fardin Ghorbani, Sina Beyraghi, Hossein Soleimani, Mohammad Soleimani, Homayoon Oraizi
Compared to the conventional metasurface design, machine learning-based methods have recently created an inspiring platform for an inverse realization of the metasurfaces. Here, we have used the Deep Neural Network (DNN) for the generation of desired
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4dfea4250dee14f23424c783eea1705d
http://arxiv.org/abs/2105.08508
http://arxiv.org/abs/2105.08508
