MétaCan
Menu
Back to cohort
Record W3168673137 · doi:10.23977/jeis.2020.51001

Design of data acquisition and transmission system for BOTDA

2020· article· en· W3168673137 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Electronics and Information Science · 2020
Typearticle
Languageen
FieldEngineering
TopicEmbedded Systems and FPGA Design
Canadian institutionsnot available
Fundersnot available
KeywordsData acquisitionComputer scienceUSBComputer hardwareDebuggingField-programmable gate arrayInterface (matter)Data transmissionTransmission (telecommunications)Embedded systemReal-time computingSoftwareOperating system

Abstract

fetched live from OpenAlex

According to the demand of BOTDA optical fibre sensor for real-time application, a high-speed data acquisition system with graphical operation interface is designed by using FPGA and USB. In this paper, hardware architecture and logic design are carried out for data acquisition with FPGA as the control device, and the upper computer with functions of data display and graphic demonstration is designed by using C# language on the PC terminal. Finally, joint debugging is carried out for the lower computer and the upper computer, and the experimental results show that the high-speed data acquisition and transmission functions are successfully realized, which meets the design requirements of the data acquisition system in BOTDA optical fibre sensor.

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.

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 score0.979
Threshold uncertainty score0.258

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 communication0.0000.004
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 head0.031
GPT teacher head0.250
Teacher spread0.218 · 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