Geomatic Assessment Of Rainwater Harvesting Potential System At Cmr College Of Engineering & Technology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CMRCET campus comprises about 10 of acres land, where water is the natural resource which is being always in high demands. If the demand is not met, then it will lead to water scarcity. Therefore, RWHS can be considered as a best solution for fighting against scarcity of water. Our present study deals with the identification of the study area boundary and marking it as a Polygon in GIS, Rooftops of various block entities, paths and pavements were digitized using the Polygon vector in GIS. GIS technique is employed for locating boundaries of the study area and for calculating the areas of various types of rooftops and paths. With the application of GIS, it is possible to assess the total potential of water that can be harvested. Potential of rainwater harvesting refers to the capacity of an individual catchment that harnesses the water falling on the catchment during a particular year considering all rainy days. This present study will enable us to identify the suitable type of water harvesting structure along with the number of structures required. Our aim is to maximize water storage and minimize the runoff through drains without making use of it. Thus, Rainwater Harvesting and Conservation aim at the optimum utilization of the rain water.
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.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it