MétaCan
Menu
Back to cohort
Record W2101924208 · doi:10.1109/aps.2006.1710589

Wireless mesh access point routing for efficient communication in underground mine

2006· article· en· W2101924208 on OpenAlexaff
M. Moutairou, Hasnaâ Aniss, G.Y. Delisle

Bibliographic record

Venue2006 IEEE Antennas and Propagation Society International Symposium · 2006
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsComputer networkSurvivabilityWirelessFlooding (psychology)Computer scienceWireless networkWireless mesh networkReliability (semiconductor)Distributed computingPower (physics)Telecommunications

Abstract

fetched live from OpenAlex

The reliability and survivability of conventional communications systems in harsh mining environments has always been a problem. The extreme conditions such as falling rock, collapsing tunnels, fires, explosions and flooding, during which communications are needed most, can also render them inoperable. An emergency underground communication system needs to be very robust with respect to these and other potential hazards. This paper deals with wireless backbone positioning for mesh wireless local area (WLAN) network. The routing problem is simulated to define the best position to place the wireless access point in mine galleries. The optimization strategy applied to the network design problem is the genetic algorithm. From various criteria such as the power profile through the mining gallery and the average SNIR level, the genetic algorithm treats all the possible positions and determines the optimal one for an effective communication. Optimization results considering density effect and other parameters such as the range, the hop number, the received power variation, the connection quality between access points are present

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.889
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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

Citations11
Published2006
Admission routes1
Has abstractyes

Explore more

Same venue2006 IEEE Antennas and Propagation Society International SymposiumSame topicMobile Ad Hoc NetworksFrench-language works237,207