Bibliographic record
Abstract
The entire world is still under the influence of the virulent pandemic COVID-19. Unfortunately, each of us is affected one way or another. Our conference, the 6th International Conference on Mechanical and Aeronautical Engineering (ICMAE 2020) was not an exception. In December we held our conference online and although the same it was a great success and we, as other conferences, continued in our sharing research success. This change to virtual was achieved by using Tencent VooV software. Each keynote speech lasted 40 minutes, invited speech 30 minutes and authors presentation 15 minutes. Each presentation was included with questions and answers. that offered a chat function though the software used to increase participation. The success and prosperity of the conference is reflected high level of the papers received. ICMAE 2020 became an effective communication platform for all the participants over the world and unlike some that claim international reach this conference was truly international. ICMAE 2020 was organized by Hong Kong Society of Mechanical Engineers. This conference aims to provide a platform for researchers and engineers to share their ideas, recent developments, and successful practices in Mechanical and Aeronautical Engineering. More than 40 participants attended the conference, they were from USA, UK, Italy, Russia, Colombia, Canada, India, Malaysia, Japan, China and more. Three renowned speakers given speeches about their latest research and reports. They are: Prof. Dan Zhang from York University, Canada; Prof. Ian McAndrew from Capitol Technology University, USA; Prof. Andrew Rae from University of the Highlands and Islands, UK. The conference also had 2 technical session and 1 poster sessions. The conference proceeding is a compilation of the accepted papers and represent an interesting outcome of the conference. This book covers 2 chapters: 1. Aeronautical Engineering; 2. Mechanical Engineering. We would like to acknowledge all of those who supported ICMAE 2020. Each individual and institutional help were very important for the success of this conference. Especially we would like to thank the committee chairs, committee members and reviewers, for their tremendous contribution in conference organization and peer review of the papers. We sincerely hope that ICMAE 2020 will be a forum for excellent discussions that will put forward new ideas and promote collaborative research and support researchers as they take their work forward. We are sure that the proceedings will serve as an important research source of references and the knowledge, which will lead to not only scientific and engineering progress but also other new products and processes. Finally, we hope to meet you all in person at our next conference in 2021. Editors: Dan Zhang, York University, Canada Ian McAndrew, Capitol Technology University, USA List of COMMITTEES LIST are available in this pdf.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.528 | 0.370 |
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".