Bibliographic record
Abstract
Abstract On the behalf of the organizing committee of the 2nd International Conference on Electronics, Electrical and Information Engineering (ICEEIE2022) held during August 12-15, 2022 in Changsha, Hunan, China. Due to the epidemic situation, there were travel restriction for every scholars who were linked with this event by using Zoom conference system, we enjoyed 3 keynote speeches and oral presentations made by the authors which lasted for 15 minutes each, a lot of inspiration sparked during the Q&A parts. The conference has provided a significant platform to encourage researchers, scholars, academician and practitioners to congregate for exchange of ideas and experiences from their work while identifying future directions of relevant areas. ICEEIE2022 promotes research and developmental activities in the field of Electronics, Electrical and Information Engineering. Researchers who have contributed their work to the conference shared their findings and experience with other researchers and attendee. Many attendees without any contribution of research paper have also been allowed to attend the conference to gain knowledge in their respective areas. With all contributions from the participants, 63 papers are final accepted from 140 submissions. Those accepted ones are well categorized into four sectors as follows:Communication engineering, Electrical engineering, Electronics, Information engineering. We wish to show our sincere appreciations to all individuals and organizations who have contributed to ICEEIE2022, especially those who did the review of all the submitted papers, dedicated their time and efforts in planning, promoting, organizing, and helping the conference. Also we must extend our thanks to our keynote speakers: Prof.Mohammad S. Obaidat from University of Sharjah, USA, who made speeches titled A New Learning Automata-Based Controller Placement Scheme for Software-Defined Network Systems, Prof. Witold Pedrycz from University of Alberta, Canada, who made speeches titled Developments in Federated Learning and Knowledge Transfer: Pursuits in Green and Granular Machine Learning, Prof. Claudio Cañizares from University of Waterloo, Canada, who made speeches titled Energy Storage Systems. We wish to show our special thanks to Hunan University of Finance and Economics, Hunan University of Technology, Hunan University of Arts and Science for support, they provided various platform to promote this conference with nice service. We are pretty sure that readers will benefit and get inspiration for their future work by using this volume, we will feel honorable to have your continuous attention and attendance for our next edition of ICEEIE. This project is funded by the scientific research project of Hunan Provincial Department of Education(21C1632). List of Committees 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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.385 | 0.255 |
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".