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Record W3047654580 · doi:10.3390/electronics9081278

Reduction of the Line-of-Sight Equivalence Principle

2020· article· en· W3047654580 on OpenAlexaff
Nagula Sangary, Natalia K. Nikolova

Bibliographic record

VenueElectronics · 2020
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Measurements
Canadian institutionsMcMaster UniversityUniversity of Waterloo
Fundersnot available
KeywordsEquivalence (formal languages)MathematicsMathematical analysisLine integralSurface (topology)ComputationSurface integralIntegral equationGeometryAlgorithmPure mathematics

Abstract

fetched live from OpenAlex

An improvement to the line-of-sight (LoS) approximation of the equivalence principle used in far-field computations is presented. In the original LoS approximation of the equivalence principle, the integral equation uses only the surface currents on the LoS surface, as well as the edge currents on the contour of the LoS surface, which is the replacement of the surface integrals over the shadow part of the surface. Here, we show that the integration over one type of surface current on the LoS surface and edge currents is sufficient, which reduces the resources required for the LoS radiation pattern computations by half. The proposed theory is a rigorous analysis of Love’s Equivalence theory with an introduction of the point-of-symmetry concept. The proposed method makes use of the vector-potential field representation to derive the improved LoS equivalence principle. The proposed approach is validated with the calculation of the far-field radiation pattern of a patch antenna using the Finite Difference Time Domain (FDTD) simulations.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.025
GPT teacher head0.233
Teacher spread0.208 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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