Bibliographic record
Abstract
High speed Internet access is becoming an essential service in the workplace which often includes hotels. This paper investigates short-range Internet access methods suitable for hotels, hospitals, and historic office buildings where pervasive telephone service exists and there is a need for "always on" high speed Internet access. It is desirable to avoid the costly installation of new wires to provide this service. While digital subscriber line technologies have matured over the last decade, and these are more than capable of providing the required service, their cost is excessive, and when transmission distances are very short there is an opportunity to apply lower-cost data-over-voice solutions. This paper evaluates the suitability of various baseband line coding techniques for data transmission in a simultaneous voice and data environment. Through computer simulation, a number of potential line coding methods were characterized by their power spectral density and eye diagram. These characterizations were used to evaluate data transmission capacity, error performance and potential interference with voice communication. The paper shows that bipolar-return to zero (BPRZ) and bipolar-non return to zero (BPNRZ) ternary coding provide the greatest potential improvement in data transmission rate while sacrificing the least in transmission performance. Quaternary and pentary methods are shown to be poor, and 2B1Q coding (widely used in ISDN and HDSL) is not applicable for data-over-voice since low frequency data transmission is required.
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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".