Guest Editorial Localisation, Communication and Networking With VLC
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We are at the dawn of an era in information and communication technology with unprecedented demand for connected and automated everything. Both Shannon theories and industrial advances have clearly evidenced that more densely packed networks and a much wider operating bandwidth are key drivers for meeting the escalating wireless network demands. Recently, there have been substantial research efforts on the exploitation of higher frequency bands, in particular the millimetre wave and optical wireless bands. After a decade of active research and development, and along with the maturity of device technology, Visible Light Communications (VLC) has emerged as a very promising technology to enable next generation digital innovations and support wide range of applications. This special issue on VLC focuses on three core thrusts of the discipline: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Localisation, Communication</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Networking</i> . The overall aim of the special issue is to inspire multi-disciplinary international communities to work together in order to achieve further research advances. Indeed, a total of 96 high quality papers were received from both academia and industry. After a careful peer-reviewing process, 17 papers were selected based on their combined novelty, rigour, and impact. Owing to the highly selective nature of JSAC, many other interesting papers were not selected for the special issue, but we hope that these papers might appear elsewhere.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 it