Pasca energy system / Azeezul Fadzlee Mohd Farid, Azwan Zakaria and Haszrol Mohd Zain
Bibliographic record
Abstract
As demand for energy usage increased, the quality of the electricity provided to commercials and industrials sectors need to be upgraded. The quality of the electrical energy supplied has not been improved in recent years although the demand has grown tremendously with the increase in the Malaysian economy from the industrial manufacturing sector. In view of the electrical energy wastage with high transient current, problems had already occurred as examples given below:- Non productive work due to machine stoppage and idling- Higher electricity bill due to unnecessary energy usage- Low machine performance and efficiencies due to power supply interruptions- Reduced life span of electrical equipment due to equipment failureswith respect to power surges The above problems had affected the smooth running of the industrial operational activities. The organisations that are directly affected and had a serious consequence either in terms of losses in income or revenue and services provided by them to the customers resultant to electrical energy interruptions are namely industrial buildings, manufacturers, offices, hospitals, supermarkets and otliers that are too many to mentioned here. Take an example in USA the power disruptions already cost them more than $ 50billion annually. And a case in Montreal in 1989 left six million people without power. Recently, in Malaysia the electricity power waste has increased due tour banisation and economic progressing. As reported by TNB, industry that uses a lot ofelectrical motors had contributed to these problems. Steps and measures had been taken to effectively overcome the problem. Hence, to have more efficient electricity energy usage and to improve the quality of the electricity supplied, a new power supply
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.143 | 0.044 |
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".