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Record W2085364378 · doi:10.1080/02726343.2013.756290

The Convergence of the Tangential Scattered Magnetic Field Based on the Vertical Improper Integral

2013· article· en· W2085364378 on OpenAlexfundno aff
Guyan Ni, Chengda Yu, Minru Bai, Yigang He

Bibliographic record

VenueElectromagnetics · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsnot available
FundersUniversité de Sherbrooke
KeywordsMathematicsIntegral equationSurface integralElectric-field integral equationMathematical analysisVolume integralLine integralImproper integralSingular integralMagnetic fieldLimit (mathematics)Multiple integralSurface (topology)Convergence (economics)Cauchy distributionField (mathematics)Daniell integralGeometryPhysicsPure mathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

The tangential scattered magnetic field of a perfectly electric conducting surface is usually expressed as an improper integral. However, the improper integral is divergent. Hence, the field is expressed as a limit of an integral in some references. In this article, the limit of the integral is called a vertical improper integral. A stronger smooth condition of the surface is added to ensure the convergence of the vertical improper integral. The relationship between the vertical improper integral and the Cauchy principle value integral is established. An example shows that the tangential scattered magnetic field is infinite at a first-order smooth point if it is assumed that the surface current density is non-zero at the point. By the boundary condition, it is obtained that the surface current density should be zero at the point. A numerical example is given to demonstrate the effectiveness of the vertical improper integral method. The numerical result also shows that singular integrals need not be calculated when the magnetic field integral equation is computed based on the method of moments.

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)0.002
metaresearch head score (Gemma)0.005
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.184
Teacher spread0.181 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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