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Record W2754768267 · doi:10.1049/iet-map.2017.0135

RWG MoM‐via‐locally corrected Nyström method in near‐field to far‐field transformation using very‐near‐field measurement

2017· article· en· W2754768267 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2017
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Measurements
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNear and far fieldTransformation (genetics)Field (mathematics)MathematicsMethod of moments (probability theory)PhysicsOpticsStatisticsChemistryPure mathematics

Abstract

fetched live from OpenAlex

Locally corrected Nyström (LCN) method is used to solve electric field integral equations (EFIE) of the equivalent current method in the planar very‐near‐field measurement of antennas and RF circuits. The exact relationship between the Rao–Wilton–Glisson (RWG) method of moments and first‐order and zero‐order LCN is established for both magnetic and electric currents to ensure normal current continuity between adjacent triangular patches. The proposed method is a point‐based RWG discretisation of EFIE and causes a noticeable decrease in the degree of freedom. It consequently eliminates spurious charges and significantly lowers the condition number of the impedance matrix. Moreover, it is more efficient to be accelerated by fast algorithms such as multi‐level fast multipole method. In what follows, the detailed explanation of the proposed method, along with the examples of current reconstruction and antenna far‐field calculation, is presented.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.030
GPT teacher head0.271
Teacher spread0.241 · 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