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Record W2131727629 · doi:10.1155/2014/213012

iAMCTD: Improved Adaptive Mobility of Courier Nodes in Threshold-Optimized DBR Protocol for Underwater Wireless Sensor Networks

2014· article· en· W2131727629 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

VenueInternational Journal of Distributed Sensor Networks · 2014
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsUniversity of AlbertaDalhousie University
Fundersnot available
KeywordsComputer scienceRouting protocolLatency (audio)Flooding (psychology)Routing (electronic design automation)Energy (signal processing)Computer networkTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

We propose forwarding-function ([Formula: see text]) based routing protocol for underwater sensor networks (UWSNs): improved adaptive mobility of courier nodes in threshold-optimized depth-based-routing (iAMCTD). Unlike existing depth-based acoustic protocols, the proposed protocol exploits network density for time-critical applications. In order to tackle flooding, path loss, and propagation latency, we calculate optimal holding time ([Formula: see text]) and use routing metrics: localization-free signal-to-noise ratio (LSNR), signal quality index (SQI), energy cost function (ECF), and depth-dependent function (DDF). Our proposal provides on-demand routing by formulating hard threshold ([Formula: see text]), soft threshold ([Formula: see text]), and prime energy limit ([Formula: see text]). Simulation results verify effectiveness and efficiency of the proposed iAMCTD.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.952
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.019
GPT teacher head0.267
Teacher spread0.248 · 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