Special issue on systems reliability and safety
Bibliographic record
Abstract
This special issue comprises 19 extended papers presented at the 4th International Conference on System Reliability and Safety Engineering (SRSE 2022) in December 2022. The conference was co-organized by the School of Intelligent Systems Engineering, Sun Yat-Sen University. The conference was also supported by Beijing Institute of Technology, City University of Hong Kong, Guangdong University of Technology, Harbin Institute of Technology, Nanjing University of Science and Technology, National University of Singapore, Northwestern Polytechnical University, Qingdao University, Shanghai Jiao Tong University, Shanghai University, University of Alberta, Zhejiang Industrial & Commerce University, and the Fifth Electronics Research Institute of Ministry of Industry and Information Technology, China. About 110 papers were received and about 50 of them were accepted for presentation in Guangzhou, China. Unfortunately, there was another wave of COVID-19 outbreak and the conference was forced to be held online. More than 140 delegates from China, USA, Canada, UK, Korea, and Japan attended the online conference. Authors were encouraged to prepare extended papers based on the questions and discussions during their presentations and these papers went through another round of review with the help of three guest editors. They are Dr Weiwen Peng of Sun Yat-sen University, Dr Ancha Xu of Zhejiang Industrial & Commerce University, and Dr Jiawen Hu of University of Electronic Science and Technology, China. We would like to thank them and the reviewers for bringing the special issue to fruition. As the General Chair of the conference series, I would also like to take this opportunity to convey our deep appreciation to all individuals who have contributed to the conference in various ways. Special thanks are extended to our colleagues in the conference committees for their thorough review of all the submissions, their time and efforts in planning, promoting and organizing the conference. In fact, the 5th SRSE 2023 which was organized by the Institute for Quality and Reliability, Tsinghua University had just been concluded in Beijing recently in October 2023. There were 182 submissions of which 90 full papers had been accepted for presentation. We look forward to receiving more extended papers for the special issue next year. Happy reading! Co-Editor-in-Chief, Loon Ching Tang
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.148 | 0.056 |
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".