Bibliographic record
Abstract
The 2022 International Conference on Informatics, Networking and Computing (ICINC 2022) was successfully held on October 14-16, 2022, in Nanjing, China (online conference).ICINC 2022 provided a shared platform for the experts, scholars and researchers to show and discuss their research results, key challenges as well as research directions, promoting the development and application of theories and technologies in related fields.In the conference, we were greatly honored to have Prof. Ljiljana Trajkovic from Simon Fraser University, Canada to serve as our Conference General Chair.The conference consisted of keynote speeches, oral presentations and online Q & A discussion, bringing together 100 delegates worldwide.Firstly, the keynote speakers were each allocated 30-45 minutes to address their speeches.Then in the next part, oral presentations, the excellent papers we had selected were presented by their authors one by one.Eight distinguished professors were invited to hold keynote speeches during the conference.Among them, Prof. Ljiljana Trajkovic, our Conference General Chair, delivered a speech on Machine Learning for Detecting Internet Traffic Anomalies, in which she introduced a survey of supervised and semisupervised machine learning algorithms for detecting BGP anomalies and intrusions.Moreover, Prof. Jixin Ma from The University of Greenwich, UK performed a keynote speech on the title: Temporal Issues in Informatics.The purpose of his speech was to: (a) motivate and explain a topic of emerging importance in informatics; (b) provide an overview on some fundamental issues with respects to temporal ontology; (c) present a brief introduction to temporal representation and reasoning in informatics in terms of some illustrating examples.Last but not least, Prof. Anand Nayyar from Duy Tan University, Viet Nam shared with us his research on Internet of Vehicles: Future Envision of Smart Transportation.In this presentation, he discussed the foundational concepts of Internet of Everything, Internet of Vehicles, Architecture, Applications, and Future Case studies.Their brilliant speeches triggered heated discussion in the third part of the conference.And every participant praised this conference for disseminating useful and insightful knowledge.We are glad to share with you that we've selected a bunch of high-quality papers from the submissions and compiled them into the proceedings after rigorously reviewing them.These papers feature but are not limited to the following topics: Signal Analysis and Processing, Embedded System, Real-time System, Numerical Control Technology, Distributed Computing, etc.All the papers have been checked through rigorous review and processes to meet the requirements of publication.We would like to acknowledge all of those who supported ICINC 2022 and made it a great success.Particularly, we would like to thank the Institute of Electrical and Electronics Engineers, for the endeavor of all its colleagues in publishing this paper volume.We sincerely hope that ICINC 2022 turned out to be a forum for excellent discussions that enable new ideas to come about, promoting collaborative research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.039 | 0.000 |
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 teacher head, 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".