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Record W2010709573 · doi:10.1109/aiccsa.2013.6616479

Multiparty/multimedia conferencing in mobile Ad Hoc networks for improving communications between firefighters

2013· article· en· W2010709573 on OpenAlexafffund
Moayad Aloqaily, Fatna Belqasmi, Roch Glitho, Amin Hammad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsConcordia University
FundersConcordia University
KeywordsComputer scienceScalabilityMultimediaWireless ad hoc networkVideoconferencingWirelessMobile radioCommunications systemMobile telephonyComputer networkTeleconferenceTelecommunications

Abstract

fetched live from OpenAlex

In current practice, the fire-fighters communication system is verbal, using a simplex radio frequency system (walkie-talkie). This system has a flat communication structure, which prevents any private communication among groups of firefighters. In addition, only one fire-fighter is allowed to talk at a time and no other functionalities (e.g. video communications or conferencing) are supported. This paper proposes a new multimedia conferencing system for fire-fighters, which overcomes the current system limitations. The new system is based on Mobile Ad-Hoc Networks, an infrastructure-less and self-organized wireless networks that are suitable for emergency situations. The proposed system has a cluster-based architecture in order to offer more scalability. A proof-of-concept prototype has been implemented and performance have been evaluated and analysed.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.027
GPT teacher head0.265
Teacher spread0.238 · 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 designSimulation or modeling
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

Citations4
Published2013
Admission routes2
Has abstractyes

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