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Record W7127416744 · doi:10.56220/uwjst.v5i0.81

Steering Mechanism for an IC engine powered tracked firefighting UGV

2021· article· W7127416744 on OpenAlexaff
Muhammad Mohsin Dar, Dr Nasir Rahman, Rizwan Alim Mufti

Bibliographic record

VenueUniversity of Wah Journal of Science and Technology (UWJST) · 2021
Typearticle
Language
FieldEngineering
TopicFire Detection and Safety Systems
Canadian institutionsThe Journal of Student Science and Technology
Fundersnot available
KeywordsFirefightingTeleoperationRobotRescue robotMechanism (biology)TeleroboticsSearch and rescueFocus (optics)Transmission (telecommunications)

Abstract

fetched live from OpenAlex

Rescue and hazard management operations are susceptible to damages related to workers, working inside the installation in addition to workers part of a rescue and disaster management team. In order to minimize this damage, it is needed to incorporate robots with telepresence equipment. Unmanned ground vehicles (UGV) with the capability of reaching different layers of urban structures like buildings play a very vital role in minimizing the damage. The designed robot for the said operations has the capability of climbing stairs, ramps etc in addition to maneuvering or navigating without colliding the obstacles, taking sharp right/left turns and pivoting around, carrying and connecting capability with the fire tender in supervisory teleoperated controlled paradigm. The focus of this research is to design, develop and demonstrate a transmission and steering mechanism for an IC engine powered firefighting UGV.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.192
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes1
Has abstractyes

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