Possibilities of Increasing of Energy Efficiency in a Small Enterprises - Case Study
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
Reducing the electricity consumption is a current trend which has an economic, social and environmental impact. Measures which are outlined to increase efficiency are also supported by legislation and could be funded from the national or European funds in EU countries. In Slovakia, there are many establishments, public buildings and households built in past decades where energy is being wasted. Approximately the share one third of the consumed energy in Slovakia belongs to industry. This statistic naturally legitimizes the effort to achieve energy savings in this segment. We choose a body which is in use partially as commercial offices and partially as production facility. The matter was to identify areas with excessive energy consumption and propose appropriate measures to avoid unnecessary losses. The paper presents more aspects of building operation regarding of energy consumption, especially in relation with old buildings with more structural and operational defects and propose some ways of the improvements the energy efficiency. The work also includes experimental data and simplified economy considerations related to the proposed measures. Finally the step model is presented in order to simplify the decision making process. The model is relevant and also applicable generally for the other engineering disciplines.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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