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Design and Performance of a Radio Frequency Identification Scanning System for Sediment Tracking in a Purpose-Built Experimental Channel

2017· article· en· W2773069446 on OpenAlexaff
John Hufnagel, Bruce MacVicar

Bibliographic record

VenueJournal of Hydraulic Engineering · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of WaterlooConestoga College
Fundersnot available
KeywordsFlumeChannel (broadcasting)Radio-frequency identificationFootprintComputer scienceWirelessMultiplexerRemote sensingEngineeringGeologyFlow (mathematics)Telecommunications

Abstract

fetched live from OpenAlex

Sediment transport studies that use radio frequency identification (RFID) tracers are now common in hydraulic studies because of the information the technique provides on the spatial and temporal variability of sediment movement. The technique has been underused relatively in laboratory studies, however, because of issues related to tag orientation and spatial resolution. The objectives of the current study were to (1) describe the design and construction of a flume and a RFID tracking system with the ability to locate tracer stones during experiments; and (2) present the results from preliminary performance tests. The design and tests were completed for vertically oriented RFID transponders, which was realistic for tracers in transport on the basis of a parallel effort to develop gyroscopic tracer stones. The constructed flume was unique because it was designed with a space under the floor of the channel that accommodated an RFID detection carriage. The carriage used three multiplexers and 12 antennae in combination with a laser rangefinder to detect and estimate the position of tracer stones. Wireless communication with a desktop computer was used. A programmable logic control system controlled the movement of the carriage. Preliminary tests conducted with vertically oriented RFID tags showed that a 23-mm RFID tag could be detected up to 21 cm above the flume floor with a streamwise position accuracy of ±1 cm. Steel cross members and multiple RFID tags locally decreased the detection range and precision of the position estimate. Zones of nondetection became larger as tags were closer together, and antennae only reliably detected the closest tag. When the antenna spacing was ∼20 cm, the system was capable of operating in a maximum tracer density of 25 particles/m2. Spatially, nonuniform distributions of tracers required lower densities for reliable detection and positioning. Continued development using different antenna array designs and anticollision RFID tracers should increase the resolution and allow higher tracer densities.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.395

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 communication0.0000.001
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 head0.018
GPT teacher head0.242
Teacher spread0.224 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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