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Record W1977547975 · doi:10.1109/map.2011.6097321

The Design of an Economical Antenna-Gain and Radiation-Pattern Measurement System

2011· article· en· W1977547975 on OpenAlexaff
Brandon Brown, Frédéric G. Goora, Chris D. Rouse

Bibliographic record

VenueIEEE Antennas and Propagation Magazine · 2011
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Measurements
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsAnechoic chamberAntenna (radio)Radiation patternAntenna measurementMicrowaveAntenna gainElectronic engineeringAntenna efficiencyRadiationSystem of measurementComputer scienceElectrical engineeringEngineeringAcousticsOpticsTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

The design of a system capable of making antenna-gain and radiation-pattern measurements at 2.4 GHz is presented. System performance based on component specifications is summarized and compared to measured data. Antenna measurements taken using the system were compared to those obtained using commercially available test equipment in an anechoic test chamber. The accuracy of the system was found to be ±0.5 dB within a dynamic range of 13 dB plus the gains of the antennas in use. The system was shown to be capable of making high quality antenna radiation-pattern measurements in an anechoic test chamber. For a total cost of less than $1300, the system presents an economical alternative to more-sophisticated microwave measurement systems, and is well suited for use in a learning environment.

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)0.002
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0040.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.039
GPT teacher head0.205
Teacher spread0.166 · 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
GenreMethods

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

Citations5
Published2011
Admission routes1
Has abstractyes

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