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Record W2971744234 · doi:10.1109/tap.2019.2938675

An Analytical Solution of Electromagnetic Radiation of a Vertical Dipole Over a Layered Half-Space

2019· article· en· W2971744234 on OpenAlexafffund
Mohsen Eslami Nazari, Weimin Huang

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectromagnetic radiationPhysicsDipole antennaSpace (punctuation)RadiationDipoleOpticsComputational physicsAntenna (radio)Computer scienceTelecommunicationsQuantum mechanics

Abstract

fetched live from OpenAlex

An analytical solution for the wave scattering generated by a vertical dipole above horizontally stratified media is proposed. The solution to the problem is given in terms of 2-D Fourier transforms, which leads to Sommerfeld-type integrals. The solution is decomposed into three terms and an analytical closed-form solution as a function of physical layers specification for the electric field intensity is deduced from the results. Two terms are expressed with hyperbolic functions and the third term is presented using the Gauss error function. A numerical evaluation of the integrals that constitute the formal result of the problem validates the accuracy and efficiency of the proposed solution at various frequencies as well as at different distances from the source. The presented solution is also implemented for the particular case of surface ocean scattering in the high frequency (HF) band and the overall behavior of the solution, which consists of three terms, is evaluated by their distance from the antenna in the near field and far-field regions.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.238
Teacher spread0.231 · 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 designTheoretical or conceptual
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

Citations12
Published2019
Admission routes2
Has abstractyes

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