Bibliographic record
Abstract
This work describes the use of the finite-difference time-domain (FDTD) method to investigate the capabilities and limitations in the use of a UWB radar system, to detect a human model target inside a realistic room. A 0.8 ns pulse at a center frequency of f0= 1.1 GHz is used. The room is modelled with all its components (water & heating pipes, windows, electrical outlets, brick walls, barred windows, etc.). The radar setup is also modelled to simulate a realistic system. The performance of the UWB radar is examined by generating 2-dimensional (2D) images of the room interior with the human body model included. This is done by considering monostatic and multistatic radar scenarios where responses are recorded and processed using the time-domain back-projection method. Images from the FDTD modelling detected the human body model at the correct location inside the room. As expected, the multistatic radar setup provided a cleaner image than that of the monostatic radar setup due to greater diversity in aspect angle.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".