Adaptive Power Controllable Retrodirective Array System for Portable Battery-Operated Applications
Bibliographic record
Abstract
An adaptive power controllable retrodirective array system is presented for a portable applications. The proposed system is able to turn on only when it needs to operate so that it can avoid wasting battery power in idle mode. This power management is accomplished by employing a rectenna and an analog switch into a battery-operated system. When an RF signal is received by an antenna, it is divided into a rectenna and a receiver, where most power is sent to a rectenna through a 15-dB coupler. The converted DC power from a rectenna wakes up the system by activating a switch connected to a battery and the receiver. When there is no interrogation, a switch becomes off. An output voltage is twice increased by a voltage doubler and added up by connecting in series. The 2nd and 3rd harmonic rejection characteristic of a circular sector antenna is introduced so that it makes the system simpler by eliminating a low-pass filter (LPF) in the rectenna. For the phase-conjugation retrodirective array, 2nd sub-harmonic mixers are used by employing anti-parallel diode pairs (APDP's), which enables to avoid the expensive high frequency oscillators. It is experimentally demonstrated that the retrodirective array system with the proposed power management can retransmit the received signal toward the source when the received power density is over 0.057 mW/cm2•
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".