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Record W2129518873 · doi:10.1109/fbw.2011.5965563

Transmission delay in wireless sensing, command and control applications for aircraft

2011· article· en· W2129518873 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsWirelessPrognosticsComputer scienceTransmission (telecommunications)Resilience (materials science)Fixed wirelessWireless networkJammingInterference (communication)UpgradeWi-Fi arrayComputer networkReliability engineeringEngineeringTelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

Wireless sensing, command, control and prognostics health monitoring (PHM) solutions provide the promise of ease of system maintenance and upgrade, reduced life-cycle cost and could significantly improve system safety, security and overall comfort On the contrary, utilizing wireless connectivity introduces a number of challenges such as resilience against anti jamming and interference avoidance. In this paper, we particularly discuss the problem of varying time delays for a wireless link. An exemplary application is elaborated as case study for wireless transmission of PHM for a more-electric aircraft (MEA) where transmission delay has to be extremely small. The discussion is continued with some delay measurements to highlight the current limitation of some of the existing wireless solutions. It is concluded that existing commercial off-the-shelf (COTS) wireless solutions are not suitable for direct use in this type of applications, and specialized solutions need to be developed.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.250

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.013
GPT teacher head0.217
Teacher spread0.203 · 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