Remote Sensing of 3-D Conducting Objects in a Layered Medium Using Electromagnetic Surface Waves
Bibliographic record
Abstract
Antennas that are located on or near the boundary between two electrically different media, such as air and earth, or seawater and rock, are used as prospective tools for remote sensing and geophysical exploration. As an example, this letter examines the electromagnetic (EM) response of a metallic object that is submerged in a conducting layer of seawater that is situated between an infinite half-space of air and a seabed of lower electrical conductivity. When the source and the object are at some distance away in the water, the primary EM propagation mode is on the interfaces because the surface waves are less attenuated than those following the direct or reflected propagation paths. The simulation tool that predicts the performances of the EM detection system uses the method-of-moments integral equation technique. The method is validated and applied to calculate the scattered fields from a submerged perfectly conducting cylinder. The numerical results are then compared with experimental data that are obtained by towing a steel cylinder through an impressed field that is produced by a horizontal electric source.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".