The Effect of a Printed Gap Waveguide Antenna at 60 GHz on the Human Body
Bibliographic record
Abstract
Millimetre-wave (mm-Wave) bands are becoming increasingly relevant for modern communication standards due to their large bandwidth and enhanced security. This development in communications standards has inspired the emergence of innovative antenna configurations within these bands. Moreover, a growing concern over the possible adverse consequences of mm-Wave frequency exposure on human health motivates investigations into mm-Wave frequency's impacts on the human body. This paper investigates the impact of a Printed Gap Waveguide (PGW) antenna on the hu-man body at 60 GHz. A Magneto-Electric (ME) dipole antenna with broadband operation and identical radiation characteristics in the mm-Wave band is proposed. PGW technology is utilized to implement a ME dipole antenna for studying human body exposure to 60 GHz Electromagnetic (EM) radiation. ME-dipole elements have been developed and examined, and EM exposure is calculated in terms of Specific Absorption Rate (SAR). The antenna is made up of a cross-shaped ME-dipole that is supported by an Artificial Magnetic Conductor (AMC) side wall cavity. The antenna with the proposed design achieves 23.4% relative impedance bandwidth at 60 GHz over the entire operating frequency range. Simulations were performed to investigate and validate the performance of the structure using Computer Simulation Technology (CST) and a high-frequency structure simulator (ANSYS HFSS). On the basis of the presented results, there is a clear advantage in evaluating the Specific Absorption Rate (SAR) according to this state-of-the-art guiding structure and meeting the global standards.
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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) | 0.000 | 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) | 0.001 | 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".