Centralized remote monitoring of electrostatic precipitators to enforce proper usage
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
Electrostatic Precipitators (ESPs) are widely used by industries to minimize the ash content and particulate matters present in the exhaust of boilers or furnaces. It reduces atmospheric air pollution which causes environmental hazards on Earth. Mindful of the increasing concerns about the effects of air pollution, regulatory bodies such as Pollution Control Boards of most countries have taken steps to enforce the installation of ESPs in industries to control the particulate matter and ash content in exhaust gases. Keeping in view the health hazards, the pollution control norms and the continuous vigilance of pollution control boards, ESPs have now been installed in a wide scale across the world. But a standing issue with the ESPs has been their relatively high power consumption which has often induced unscrupulous industries to limit their usage in order to reduce their electricity expenses towards the ESPs continuous operation. The limited operation of the ESPs causes high air particulates, ash content and poisonous gases in the environment which are directly responsible for several health hazards. In this paper, an Information Communication Technology (ICT) enabled electronic tool is presented for centralized monitoring of installed ESPs in different locations from a remotely placed monitoring centre. It is a cost effective and an efficient tool for E-Governance and will fulfill the dream of a pollution controlled environment.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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