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Record W2131790514 · doi:10.1109/tap.2002.802268

Analysis of finite-microstrip structures using surface equivalence principle and multiple network theory (SEMN)

2002· article· en· W2131790514 on OpenAlex
Farzad Tavakkol Hamedani, Ahad Tavakoli, L. Shafai

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

VenueIEEE Transactions on Antennas and Propagation · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMathematical analysisMathematicsMicrostripAdmittanceBoundary value problemElectric-field integral equationBasis functionIntegral equationElectromagnetic fieldSurface (topology)HFSSElectrical impedanceGeometryPhysicsMicrostrip antennaOpticsAntenna (radio)Computer science

Abstract

fetched live from OpenAlex

Two techniques are developed for the analysis of finite microstrip structures. They are based on electric and magnetic field integral equation (EFIE and MFIE) formulations of the surface equivalent principle and multiple network theory (SEMN) method. Using pulse surface basis functions, the surface of each homogeneous dielectric body is modeled by small flat segments of arbitrary geometry and constant electromagnetic field. Using the surface equivalence principle and the Green's functions of the homogeneous space, the admittance and impedance matrices are computed. Then, the boundary conditions and multiple network theory are applied to determine the overall characteristic of the entire space. Several radiation and scattering examples are numerically analyzed and their calculated near and far fields are presented. The numerical results of the two formulations are then compared with measurement and those of HFSS and ENSEMBLE.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.249
Teacher spread0.229 · 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