A ZERO-Power Sensor Using Multi-Port Direct-Conversion Sensing
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Bibliographic record
Abstract
This paper presents a class of zero-power microwave sensor architecture based on the direct-conversion principle to eliminate data processing at the Internet of Things sensors and provide unpowered nodes. A base station (BS) transmits a single tone signal at the frequency of f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> /2 toward the sensing node using an antenna. At the node, an antenna receives the signal, and a passive frequency doubler makes the frequency twice. Then, a multi-port structure directly modulates the sensing data at the frequency of f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> and sent back to the BS by an antenna. The multi-port circuit has one input, one output, and some loading ports. In this paper, a six-port modulator and four similar sensitive capacitive resonators are used. A pair of resonators senses the variation of a sample under test (SUT) while the other pair is covered by a reference or known material. At the BS, any quadrature receiver can be used to demodulate sensing data. Here, a similar six-port structure is used to extract data and find the SUT variations. An example one-node system is implemented at f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> = 2.45 GHz and evaluated by some standard SUTs. To support multiple nodes, a smart directional antenna is necessary at the BS, which also improves the overall efficiency of the system.
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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 | 0.001 |
| 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 it