Bibliographic record
Abstract
The Asian Aerospace and Astronautics Conference (AAAC 2023) will take place in Wuhan, Hubei, China from September 15-17, 2023, where participants will gain detailed insights into the state of the art of aerospace and astronautics, and enjoy the exchange with other enthusiasts from all over the world who are interested in this highly relevant and constantly growing area. The conference is sponsored by Science and Engineering Institute (SCIEI), Huazhong University of Science and Technology, co-sponsored by The Hong Kong Polytechnic University, Nanjing University of Science and Technology, York University, etc. This international conference was over three-days and provided a forum for discussion of aerospace and astronautics. Submitted papers were received and sent for preliminary and peer review conducted by the technical committees. Professional comments are given according to the aspects of originality, innovation, applicability, technical merit, organizing and writing, relevance to conference. After several rounds of review procedure, some excellent papers have been received to get published in the conference proceedings. The proceedings contains a collection of research papers, organized with 6 chapters: aircraft structural design and wing aerodynamic analysis, automation control and visualization technology for flight systems, system design and safety analysis in aerospace engineering, aviation system and engine performance simulation and evaluation, new propulsion technology based on combustion mode, engineering material mechanics analysis and performance simulation and so on. The conference invited four internationally recognised experts in their fields of aerospace and astronautics to deliver keynote and invite speeches, including Prof. Zheng Hong Zhu, York University, Canada; Prof. Chih-Yung Wen, The Hong Kong Polytechnic University, Hong Kong, China; Prof. Yan Wang, Nanjing University of Aeronautics and Astronautics, China; Prof. Lei Shi, Northwestern Polytechnical University, China. Each speaker has delivered the speech more than 30 minutes. In addition, around 50 experts and scholars and listeners from the world’s top research institutes of aerospace technology, including Northwestern Polytechnical University, Nanjing University of Aeronautics and Astronautics, Beihang University, Nanjing University of Science and Technology. We would especially like to thank the organization committees, the members of the program committees and technical committees. They have worked very hard in reviewing papers and making valuable suggestions for the authors to improve their work. We also would like to express our gratitude to the external reviewers, for providing extra helps in the review process, and the authors for contributing their research result to the conference. Without such support a conference cannot maintain quality or add real original contributions to knowledge. It goes without saying, it is core to success, but here we re-iterate that point. On behalf of organizing committees, we would like to express our sincere gratitude to all participants and speakers who contribute to make this event a great success. Conference Organizing Committee AAAC 2023 List of Organizing Committees, Statement of Peer Review are available in this Pdf.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 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) | 0.582 | 0.429 |
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".