Humanitarian logistics: the establishment of the nimbusdroid pluviometric monitoring system to rainfall spates, floods and overflows in the rochdale neighborhood
Bibliographic record
Abstract
Spates, floods and overflows are natural disasters and anthropogenic character responsible for strong impact on society. The fact that they have difficult prognosis makes the means of providing for them is uncertain, passing the condition of hostages to the populations of the areas affected by these events. Therefore, it is necessary the intervention of the Humanitarian Logistics in order to ensure emergency aid to victims. One of the factors responsible for the complexity of acting Humanitarian Logistics is the prevention of disasters through the flow of information and communications. As a possible solution, are used the rainfall monitoring systems to control water levels. Thus, the aim of this paper was to develop a rainfall monitoring system called Nimbusdroid the Rochdale neighborhood, which emphasizes the high number of incidence of these disasters. In metodological terms, bibliographical research had been used for the constitution of the theoretical basement, followed of a study of case in the quarter of the Rochdale. . As its focus, it is a qualitative and quantitative research .According to the method of approach is deductive research. Not only used in the monitoring water levels, the Nimbusdroid system forwards messages and supplies information to the applicatory site and of the same in form of alert in real time. When compared with the ALERT SMS – rainfall monitoring installed in the Osasco city - Nimbusdroid system has advantages in its functionality, a time that the ALERT SMS is unknown and requires a prior registration, different of Nimbusdroid.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".