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Record W2792399305 · doi:10.1109/tap.2018.2804668

Solutions for General-Purpose Electromagnetic Problems Using the Random Auxiliary Sources Method

2018· article· en· W2792399305 on OpenAlex
Mohamed A. Moharram Hassan, Ahmed A. Kishk

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 · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

A 3-D general-purpose implementation of the random auxiliary sources (RASs) method is proposed, benefiting from the Rao-Wilton-Glisson (RWG) testing functions. The testing procedure is presented in terms of the RWG function parameters. The performance of the proposed RAS with the RWG testing function is compared with point matching. Also, a simple treatment for mixed boundary problems is introduced to enable solving the complex electromagnetic problems. Furthermore, a waveport formulation is proposed that is better suited for the iterative approach of the RAS method to facilitate the modular analysis of components. A gradient-based testing formulation for the transmitting port is exploited to enforce the matching to the forward wave only on a waveport. Nevertheless, several test cases are presented to evaluate the accuracy and performance of the proposed method in comparison to the commercial full-wave solvers showing a reasonable agreement.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score0.794

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 studies0.0010.000
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 head0.022
GPT teacher head0.273
Teacher spread0.251 · 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