Stability Analysis and Optimization of Airport Security System
Bibliographic record
Abstract
In this paper, we have established a composite queuing network model on the basis of the queuing theory and combining with the current security system of the airport. We have made division of the whole security system into different processes which include ID check process, x-ray scanning process, and millimeter scanning process, and find out the unit of security system according to the proportion of different security lanes, what’s more, these processes were distinguished into different kinds of queuing system, and then, we established the queuing network using these different queuing model into the unit. We applied the method of computer simulation to analyze the bottleneck, and we find that ID check process in pre-check system is unstable based on the current proportion of pre-check lane. Meanwhile, we optimized the number of each unit using the system design model and prove the effectiveness by computer simulation, then, we optimized the service rate of the baggage and body screening in pre-check lane follow the above process. Finally, we further discussed development direction of this model.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".