The Fourth International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness & Workshops
Bibliographic record
Abstract
Recent technological developments in broadband peer-to-peer and overlay networks, wireless and mobile networks, and grid computing have led to a wide variety of new challenging problems. These include the provisioning of Quality of Service (QoS), survivability, resilience, security and scalability in a wide range of emerging applications --- such as large-scale multimedia systems --- across both wired and wireless networks. The Fourth International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QShine 2007) focuses on all aspects of these challenges, including the QoS provisioning, performance optimization, cross-layer design, resilience, security, scalability and survivability of distributed applications in heterogeneous networks. It will serve as a forum for researchers from academia and industry to present the latest research results on QoS issues for both wired and wireless networks, with the hope to develop viable cross-layer design methodologies. The conference will feature prominent invited keynote speakers in the field, including (To be announced). The conference will also feature high-quality research papers, both in the main conference tracks, as well as in affiliated workshops and poster sessions. Accepted papers will be published in the ACM International Conference Proceedings Series and will be made available in ACM Digital Library, as well as indexed by EI and ISI Index. Research papers of particular merit will be selected for consideration of fast track publication in a ACM/Springer Mobile Networks and Applications (approved) or Elsevier Computer Networks (pending approval)
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.071 | 0.033 |
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".