Analysis of instantaneous availability of communication system based on the influence of support equipment
Bibliographic record
Abstract
Summary Taking into account the influence of support equipment, in this paper, we propose an instantaneous availability (IA) model based on the Markov process and queuing theory. Using big data technique, we analyze the massive data of a communication system and generate its main features. We propose a new method to design system, by using these features in the proposed IA model. Two typical fault modes in communication system are studied. Firstly, an IA model considering repair equipment failure in the maintenance of one electronic unit is proposed. Then, we further enhance the IA model by exploring the queuing problem of multiple electronic units. M/G/1 queuing system is used to analyze the distribution function of waiting and service time. Simulations are performed to illustrate the validity of the model when parameters are under exponential distribution. In addition, we investigate the effect of parameters on IA. As a case study, we analyze the proposed IA model on an optical fiber transmission system and show the validity and applicability of the 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".