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Record W2136452825 · doi:10.1109/mwsym.2002.1012235

Simulation of resonant modes of rectangular DR in MIC environment using MPIE-MoM with combined entire-domain and sub-domain basis functions

2003· article· en· W2136452825 on OpenAlexaff
Y. Liu, Safieddin Safavi‐Naeini, S.K. Chaudhuri, Ramin Sabry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBasis functionBasis (linear algebra)Method of moments (probability theory)Domain (mathematical analysis)Integral equationFunction (biology)Mathematical analysisTetrahedronMathematicsRepresentation (politics)Time domainAlgorithmComputer scienceGeometry

Abstract

fetched live from OpenAlex

An efficient method-of-moments volume integral formulation using combined entire-domain and subdomain basis functions is proposed for simulating the resonant modes of a rectangular DR in an MIC environment. The formulation is based on the mixed-potential integral equation using Michalski's formulation-C Green's functions. The spatial-domain Green's functions are calculated by using the complex image method. Different from the simple sinusoidal entire-domain basis functions used by previous methods, an approximate solution for the resonant modes of rectangular DR in MIC environment based on Marcatili's method is used as the entire-domain basis function, while a set of tetrahedral basis functions are used as sub-domain basis functions. Since the main profile of the resonant mode can be represented well by the entire-domain basis function, only a small number of sub-domain basis functions are needed for further refinement of the representation. Compared with the method-of-moments formulations using only sub-domain or entire-domain basis functions, this method is much faster for the same accuracy. Numerical results are given and compared with other methods.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.366

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 head0.007
GPT teacher head0.207
Teacher spread0.200 · 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

Citations7
Published2003
Admission routes1
Has abstractyes

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