MétaCan
Menu
Back to cohort
Record W2801720148 · doi:10.1109/dinwc.2018.8356990

On performance study of TWR UWB ranging in underground mine

2018· article· en· W2801720148 on OpenAlexaff
Biki Barua, Nahi Kandil, Nadir Hakem

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIndoor and Outdoor Localization Technologies
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsRangingComputer scienceUltra-widebandDistance measurementEngineeringElectronic engineeringTelecommunicationsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper evaluated the performance of ultrawide band (UWB) technology for underground localization. As UWB is featured up with several advantages, this performance analysis can be exploited for designing a better adaptive communication system in harsh environments like underground mine. Besides, we have used two way ranging (TWR) technique with UWB for ranging. To this end, we have performed measurements using TWR UWB mechanism in underground mine and compared the distances with reference distance. The results were promising for UWB technology in the underground mine along with shows the effectivity with TWR ranging technique in harsh environment.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.257
Threshold uncertainty score0.225

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 head0.010
GPT teacher head0.217
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 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

Citations27
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicIndoor and Outdoor Localization TechnologiesFrench-language works237,207