Special Issue on the 9th International Conference on Thermal Engineering: Theory and Applications, March 24–26, 2016, Abu Dhabi, UAE
Bibliographic record
Abstract
The ICTEA conference series was inspired by the need to help provide an opportunity for professional development of scientists and engineers in the Middle East, including the Gulf region and North Africa. The need for such development persists, despite the strong commitment of regional governments for improving undergraduate education and for building research capabilities in institutions of higher learning. Until recently, attracting highly motivated academic staff to advance research agendas and to make significant contributions to GDP growth was not among the top priorities. But, thanks to the foresight of regional leaders, higher education in this part of the world is starting to change. However, the fact remains that highly skilled scientists and engineers in the region who are dedicated to research often must seek work abroad in academic and research institutions in order to develop themselves professionally.Well-defined and focused high-quality scientific/technical meetings dedicated to contacts between the academics and researchers in regional institutions of higher learning and their counterparts abroad are scarce. The purpose of starting a biannual international conference ideally to be rotated around the Middle East, Gulf, and North African region countries was and still is to meet this need and to provide a well-structured platform to boost research activity and productivity in the region as well as provide a point of contact and networking. Such a conference can serve as a focal point for the gathering of scientists and engineers who hail from this region and who are working abroad in Europe, North America, and other industrialized parts of the world. Thermal Engineering was selected as an umbrella title for the Conference series because of its encompassing meaning and because this research area is of great importance to the region. Topics related to environment, energy, petroleum, and construction are obvious examples of thermal engineering applications which are crucial to the economic development of the region.The ICTEA conference series was held since 2004 in different countries in the MENA region. The growing success of the conference series and the rapid recognition it gained and continues to gain are quite gratifying to its organizers. This special issue covers a wide range of thermal problems in engineering.In closing, I would like to express our appreciation to the authors and the anonymous reviewers and to the Editor of the Journal of Thermal Science and Engineering Applications who made this special issue possible.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.222 | 0.091 |
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".