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Record W1572567020

Experimental characterization of the UWB channel for an underground mining vehicle

2013· article· en· W1572567020 on OpenAlexaff
Yacouba Coulibaly, D. Gilles, Houda Nadir, A. Dodji

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2013
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsPolytechnique MontréalUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsDelay spreadPath lossChannel (broadcasting)TransmitterWidebandFrequency domainPower delay profileComputer scienceUltra-widebandElectronic engineeringFrequency bandAcousticsTelecommunicationsEngineeringFadingBandwidth (computing)PhysicsWireless
DOInot available

Abstract

fetched live from OpenAlex

In this paper, an experimental characterization of the ultra-wideband (UWB) channel for an underground mining vehicle is presented. A comparison of the results obtained inside and outside a mining environment is done. The frequency domain channel measurements have been carried out in the 2 GHz to 6 GHz frequency band. The pass loss model is extracted for the measurements inside and outside of the underground mine. The path loss exponents in both scenarios are found to be around 2. A simple statistical model is proposed for the delay spread and, in both cases, there are no relations between the delay spread and the transmitter receiver distance. Aikake information criterion is used as a goodness of fit for comparison of different statistical distributions to the delay spread of the vehicle inside the mine. The reflective nature of the vehicle environment is shown in the power delay profile and with the Ricean K-factor.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.659

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 science0.0010.000
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 head0.013
GPT teacher head0.220
Teacher spread0.207 · 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 designBench or experimental
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

Citations8
Published2013
Admission routes1
Has abstractyes

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