Proceedings of the 2nd ACM international workshop on Wireless multimedia networking and performance modeling
Bibliographic record
Abstract
Welcome to the 2nd ACM Workshop on Wireless Multimedia Networking and Performance Modeling. The demand for wireless multimedia communications thrives in today's consumer and corporate market. The need to evolve multimedia applications and services, and their associated protocols for emerging networks is at a critical point given the proliferation and integration of wireless systems to intelligent and broadband networks, mobility of people, data/voice convergence and the integration of computing and communication in mobile devicesThe workshop will provide a forum for researchers and practitioners to share and exchange their experience, discuss challenges, and report the state of-the-art and in progress research related to different aspects of wireless multimedia networking and performance modeling for WLANs, WPANs, WMANs, WWANs, MANETs and sensor networks such as wireless video and wireless streaming, systematic design methodologies, algorithms, synchronization, analysis and performance modeling.The workshop is held in conjunction with the 9th ACM/IEEE International Symposium on Modeling, Analysis, and Simulation of Wireless and Mobile Systems (MSWiM), and takes place in the beautiful city of Torremolinos, Malaga, in Spain.This year we have received 28 papers from research groups worldwide. After a careful review process, 10 papers were selected for regular presentation at the workshop.
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 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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".