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Record W2944779139 · doi:10.1109/isie.2019.8781524

A Collaborative Work Cell Testbed for Industrial Wireless Communications — The Baseline Design

2019· article· en· W2944779139 on OpenAlexfundno aff
Yongkang Liu, Richard Candell, Mohamed Kashef, Karl Montgomery

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsnot available
FundersNipissing University
KeywordsTestbedBaseline (sea)Computer scienceWirelessSynchronization (alternating current)AutomationWireless networkWork (physics)Wireless sensor networkEmbedded systemComputer networkDistributed computingEngineeringTelecommunicationsChannel (broadcasting)

Abstract

fetched live from OpenAlex

A work cell is an essential industrial environment for testing wireless communication techniques in factory automation processes. A new testbed was recently designed and developed to facilitate such studies in work cells by replicating various data flows in an emulated production environment. In this paper, the testbed's baseline design is presented which characterizes deterministic and reliable communication needs between work cell components in a typical machine tending application. Special design issues are discussed regarding safety measures in collaborative robotic operations and network synchronization among distributed machines. Measurement plans in the hardwired baseline are also introduced along with further wireless extensions. The testbed can serve as a representative cyber-physical system (CPS) model to verify industrial wireless techniques in support of mission-critical data transmissions.

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.035
GPT teacher head0.250
Teacher spread0.215 · 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
GenreMethods

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

Citations9
Published2019
Admission routes1
Has abstractyes

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