Rugged Linear Array for IoT Applications
Bibliographic record
Abstract
In this article, a rugged linear array is proposed for covering both the LTE and 5G bands with an intermediate gain. The antenna is composed of a driven element, a set of directors, and a set of reflectors, where the excited element is a wideband high-efficiency electromagnetic structure (WHEMS) and the parasitic elements consist of metal rods. To achieve a rugged design, similar to the classic Yagi antenna, all of the elements should be conductively connected, so that it can be welded. The weldable mechanism is started on the driven radiating element. In addition, a balun is introduced in the antenna to reduce the influence of unbalanced common-mode currents. A wind resistance analysis is also presented, where the drag force of the proposed antenna is approximately a quarter of that for an antenna with a metal plate. The antenna exhibits a gain of 10.8-13.3 dBi for a 78% fractional bandwidth (1.7-3.7 GHz), which is a sevenfold increase from that of the Yagi antenna, without sacrificing the gain or rugged design. The proposed antenna has the advantages of a simple feeding arrangement, low cost, lightweight, low-wind resistance, and rugged structure; and is suitable for all-weather large-scale Internet-of-Things (IoT) deployment at a rural site or in a harsh networking environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".