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Record W3005576428 · doi:10.1049/el.2019.3559

Communication to a spinning CubeSat using a two‐mode planar circular array

2020· article· en· W3005576428 on OpenAlexfundno aff
Muhammad Ali Babar Abbasi, Vincent Fusco, Umair Naeem

Bibliographic record

VenueElectronics Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilEast China Institute of TechnologyQueen's UniversityQueen's University Belfast
KeywordsCubeSatSpinningPlanarMode (computer interface)Circular bufferMaterials scienceOpticsComputer scienceAcousticsEngineeringPhysicsAerospace engineeringMechanical engineeringComputer graphics (images)

Abstract

fetched live from OpenAlex

This Letter presents a novel technique for establishing a robust communication link to a spinning un‐stabilised small satellite such as a CubeSat. The authors propose a system that involves a multimode excited planar circular array radio combined with a 360° phase shifter that can electronically track the spinning CubeSat antenna and establish a communication link. The transmitter comprises a mode‐generating Rotman lens and a circular array of microstrip patch antennas. The authors’ proposed approach combines two spatially orthogonal modes of the circular array. They first present the system architecture, then they design and realise a proof‐of‐concept experimentally validated module operating in C‐band at 5.8 GHz.

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 score0.001
Threshold uncertainty score0.005

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.232
Teacher spread0.218 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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