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Record W1641767697 · doi:10.1109/ccece.2004.1347651

Integrated optical/wireless networking

2004· article· en· W1641767697 on OpenAlexaff
Shafiq U. Hashmi, Hussein T. Mouftah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBroadbandComputer scienceTelecommunicationsComputer networkPassive optical networkOptical wirelessBandwidth (computing)Access network10G-PONWirelessWireless broadbandBroadband networksRadio over fiberWireless networkWavelength-division multiplexing

Abstract

fetched live from OpenAlex

The explosive growth of fiber bandwidth is revolutionizing telecommunications throughout the world. The end-user bandwidth demand is also increasing concurrently. To run fiber to each end user is impossible. To cope with this situation, hybrid fiber radio (HFR) and hybrid free space optics (FSO)/RF are viable solutions to provide survivable access networks for the end-users and business access. It provides the solutions for the vital challenges under diverse atmospheric conditions by offering "all weather survivable" links, pushing the high bandwidth backbone network towards the distribution access point. This case study presents the HFR concepts and its various networking scenarios. Here we want to study the synergy effect based on the integration of broadband wireless and optical networks that will lead to a flexible access network structure, capable of offering broadband mobility functions to the telecommunication users. This time frame allows us to consider some quite promising state-of-the-art technologies and enables us to evaluate the possible implementation of the integrated optical/wireless access networks.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.002

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.

Opus teacher head0.015
GPT teacher head0.228
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2004
Admission routes1
Has abstractyes

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