MétaCan
Menu
Back to cohort
Record W4210464780 · doi:10.1109/tap.2022.3145463

Multifunctional Drone-Based Antenna for Satellite Communication

2022· article· en· W4210464780 on OpenAlexaff
Saman Zarbakhsh, Abdel-Razik Sebak

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2022
Typearticle
Languageen
FieldEngineering
TopicUAV Applications and Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsBeamwidthDirectivityMaterials scienceComputer scienceAntenna (radio)Communications satelliteIndium tin oxideOpticsAcousticsLayer (electronics)OptoelectronicsElectronic engineeringAerospace engineeringSatelliteEngineeringTelecommunicationsNanotechnologyPhysics

Abstract

fetched live from OpenAlex

This communication presents a drone-to-satellite beam-forming antenna with multifunctional purposes. A glass material with a gradient coating configuration is exploited to realize a transparent structure. Beam tilting is obtained by controlling the phase distribution of an antenna by means of an inexpensive and passive surface. Simultaneously, solar cells are implemented on the proposed structure for solar energy harvesting using the transparency feature of the surface. The sputtering physical vapor deposition process is used to layer a thin coat of indium tin oxide (ITO) onto the glass. A conceptual beam tilting with a multipurpose design is introduced for drone2sat communication and energy harvest. The proposed communication structure works at a frequency of 3 GHz and covers a 60° spatial beamwidth. The directivity and propagation characteristics are preserved by this configuration. To validate the design performance, a prototype has been fabricated and a satisfactory agreement between the numerical results and experimental ones is achieved. The proposed structure can enhance the multifunctional designs, which could offer advantages for real-world space drone communications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.213
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Antennas and PropagationSame topicUAV Applications and OptimizationFrench-language works237,207