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Record W2076548085 · doi:10.1109/oceans.2014.7003139

Power source management and electrical fault mitigation in seafloor networks

2014· article· en· W2076548085 on OpenAlexaff
Bob Brant, Erin Martin-Serrano, Richard Pomerleau

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsOceanWorks International (Canada)
Fundersnot available
KeywordsSeafloor spreadingShoreRedundancy (engineering)Computer scienceTelecommunicationsBackupElectrical engineeringEngineeringGeologyOceanography

Abstract

fetched live from OpenAlex

Initially deployed in 2010, the CSnet Offshore Communication Backbone (OCB) located in the Mediterranean Sea approximately 100km off the south coast of Cyprus contains oceanographic sensors and an array of seismometers providing scientists with valuable real time data for analysis. Recently, it was decided to transition the power and communications feed to the OCB seafloor network from a buoy located directly above the network to a shore-based supply utilizing two telecommunication cables (known as Poseidon, owned and operated by Radius Oceanic Communications, Inc.) connected to shore. To maintain redundancy after a potential electrical shunt fault occurs on one of the telecommunication cables, resulting in a power short to seawater, the OCB requires load-sharing diodes between the power feeding cables and the nodes. The seafloor network nodes, designed and built by OceanWorks, can be expensive to recover, so an alternative approach to adding load-sharing diodes had to be developed. This paper discusses the migration of a seafloor network to a redundant power feed architecture without the recovery of the seafloor network nodes and successful mitigation of a potential electrical shunt fault.

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 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: Empirical · Consensus signal: none
Teacher disagreement score0.624
Threshold uncertainty score0.198

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 head0.004
GPT teacher head0.178
Teacher spread0.175 · 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 teacher head, 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

Citations1
Published2014
Admission routes1
Has abstractyes

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