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Record W1924419635 · doi:10.15439/2015f298

Analysis of Inductively Coupled RFID Marker Localization Methods

2015· article· en· W1924419635 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnals of Computer Science and Information Systems · 2015
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsUniversity of Regina
FundersKultúrna a Edukacná Grantová Agentúra MŠVVaŠ SR
KeywordsSIGNAL (programming language)Computer scienceExcitationAmplitudeProcess (computing)Identification (biology)TRACE (psycholinguistics)AcousticsElectronic engineeringPhysicsEngineeringOptics

Abstract

fetched live from OpenAlex

The presented paper is focused on analysis of two methods of marker localization. The markers are passive RFID transponders (without or with identification chip) consisting of tuned LC circuit and being used to mark and trace underground networks such as cables and pipes. Localization of the marker is based on evaluation of signal amplitude received from the excited marker, i. e. it is RSSI based localization method. The excitation of marker can be periodically repeated or continuous. In the first case the localization process consists of two stagesexcitation and receiving of marker damped oscillations, in the second case the amplitude of continuously generated excitation signal is decreased by vicinity of the marker. Both localization methods are mathematically analyzed by modeling of their circuits using differential equations. The results of analysis are used to compare both methods and to evaluate their suitability for practical utilization.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.852
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.049
GPT teacher head0.330
Teacher spread0.281 · 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