EM Wave Scattering by Random Surfaces With Different Contrast and Large Roughness Heights
Bibliographic record
Abstract
A solution for electromagnetic (EM) scattering over a two-dimensional random rough surface (three-dimensional scattering problem) with large roughness height using the generalized functions approach is proposed in this paper. The EM field derivation incorporates rough surface profile with small-slope, a radiation source and involves all scattering orders of the scattered electric field (E-field) for high and moderate contrast media. Subsequently, the first-order scattered E-field is calculated using the Neumann series solution for transverse magnetic (TM) polarization. By considering pulsed dipole antenna and a two-dimensional Gaussian rough surface distribution with different root mean square heights and correlation lengths, the scattered E-field along with the radar cross-section is calculated. Using the result of the method of moments (MoM) as reference, a numerical evaluation of the solution for different roughness heights and contrast media demonstrates that the proposed solution is better than those of the small perturbation method (SPM), Kirchhoff approximation (KA) and small-slope approximation (SSA).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".