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Record W6989179509

Analysis of Wet Antenna Losses on 11.843 GHz Slant Path in Nigeria and Comparison with Some Tropical Climates

2022· article· en· W6989179509 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicPrecipitation Measurement and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAttenuationAntenna (radio)SatelliteCommunications satelliteParabolic antennaAntenna height considerationsTropical climate
DOInot available

Abstract

fetched live from OpenAlex

Abstract The amount of water deposits on the receiving dish antenna can cause additional losses and consequently contaminate the actual slant-path attenuation. Only a few research works have been reported in the literature on the measurement of wet antenna attenuation (WAA) and the technique(s) of extracting the losses from the total attenuation in tropical and equatorial climates, characterized with heavy rainfall intensities of convective kind. Therefore, the adverse effects of antenna losses due to rain on a 11. 843 GHz satellite link and the methodology of extracting the losses from the measured rain-induced attenuation have been reported in this article. A vertically polarized parabolic dish with diameter and elevation of 0.3 m and 420, respectively have been used in the study. The measured results at 11.843 GHz were frequency-scaled in order to obtain their equivalents at 18.585 and 20.2 GHz; and then compared with those reported from Malaysia and Canada. The study will provide useful information in the planning and designing of an efficient and reliable Earth-satellite communication link in tropical climates. The experimental results also can further enrich the ITU-R databank.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.234
Teacher spread0.212 · 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 teacher head, 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)Same topicPrecipitation Measurement and AnalysisFrench-language works237,207