Analysis and design of the periodic structure based low-profile planar high-gain antennas
Bibliographic record
Abstract
Recently, some classes of periodic structures have been revisited in the electromagnetic area.A lot of attention is being paid to periodic structures, whose electromagnetic characteristics a,re not found in natural materials.They are called metamaterials.Among these periodic structures are artificial'm,aqneti,c conductors (AMCs) Ntlagnetic condnctors do not exist in nature.I-Iowever, using periodic structures they can be synthesized to some extent.In particular, using periodic patches or metallic gratings on a grounded dielectric slab, one can artificially produce synthesized surfaces.Their svnthesis and application are investigaüed in this thesis.The transverse equivalent netrvork (TEN) model will be extended to analyze cavity resonance antennas with artificial ground pianes in this thesis.Emploving this CAD-tool, a comprehensive study is done on the far-field properties of cavity resonance antennas witìr artificial ground planes.One of the best thing that happened to rle cluring my studies at the University of \¡lanitoba rvas the friendship with Dr. À,f alcolm Ng N4ou Kehn.I am indebted to him fbr all discussions we had on different topics of electromag- netics.His help and colla,boration in developing the Nfol\tl code used in this thesis is g-ratefulh, acknorvledged and appreciated.Prof's.Lot
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".