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Record W2179625061 · doi:10.5539/esr.v5n1p10

Polarization Tracking Study of Earth Station in Satellite Communications

2015· article· en· W2179625061 on OpenAlexvenueno aff
Lihua Ma, Chao Hu, Jun Pei

Bibliographic record

VenueEarth Science Research · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsGeostationary orbitCommunications satelliteTransmitterRemote sensingSatelliteAzimuthPolarization (electrochemistry)Computer scienceTelecommunicationsEngineeringPhysicsGeographyOpticsAerospace engineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

Satellite communications, in telecommunications, the use of satellite can provide communications links between various points on the earth. Typical satellite communication is composed of a communication satellite, a signal transmitter and a signal receiver. As the signal transmitter or the signal receiver, an earth station plays a vital role in the satellite communications. Accurately adjustment of antenna azimuth, elevation and polarization angles on the earth station is the key to satellite communications. In the present paper, a study of polarization tracking of earth station is presented, and a detailed adjustment procession of the polarization angle is given. Combing with observation series of MEASAT-2 satellite in geostationary orbit, the polarization tracking accuracy is verified. The method can be embeded into computer program of antenna polarization adjustment in earth station.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.278
GPT teacher head0.401
Teacher spread0.123 · 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 designObservational
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

Citations2
Published2015
Admission routes1
Has abstractyes

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