Defining Breast Tumor Location Using a Four-Element Wearable Circular UWB MIMO Antenna Array
Bibliographic record
Abstract
The objective of this paper is to develop a wearable circular UWB MIMO antenna array, consisting of four elements, that is capable of detecting and locating tumor cells within a heterogeneous breast phantom. The antenna element operates within a bandwidth from 2.4 GHz to 10.6 GHz when FR4 is used as the substrate, and extends from 2.57 GHz to 12.6 GHz when a Dacron fabric is used instead. The antenna is fabricated and measured, yielding highly similar results to the simulated outcomes. In the suggested detection system, one antenna is used for transmission, while the other antennas receive the transmitted signal. The employed antenna demonstrates gains of 5.49 dBi, 9.87 dBi, 11.9 dBi, and 14.7 dBi at resonant frequencies of 2.84 GHz, 3.87 GHz, 5.83 GHz, and 8.24 GHz, respectively, when a Dacron fabric is used as the substrate. Moreover, the proposed antenna exhibits a flexible shape with minimal vertical and horizontal bending effects across the entire operating frequency band. The antenna has a compact size of 42.85 × 42.85 mm2 and is printed on an FR4 substrate with a dielectric constant of 4.5 and a thickness of 1.6 mm for testing purposes. The S-parameters of the suggested system can effectively identify and precisely locate small tumors. Furthermore, the SAR findings indicate that the amount of power absorbed by the breast phantom tissues complies with the IEEE standards, thus confirming the suitability of the recommended antenna for the early detection and localization of breast cancer.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".