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Record W1542812612

Redundant reader elimination for directional antenna in RFID systems

2011· article· en· W1542812612 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

VenueInternational Conference for Internet Technology and Secured Transactions · 2011
Typearticle
Languageen
FieldEngineering
TopicRFID technology advancements
Canadian institutionsCommunications Research Centre CanadaUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceRadio-frequency identificationMultipath propagationAntenna (radio)Software deploymentCover (algebra)TelecommunicationsEngineeringComputer securityChannel (broadcasting)
DOInot available

Abstract

fetched live from OpenAlex

Radio Frequency Identification (RFID) systems, due to recent technological advances, have been used for various advantages in industries like production facilities, supply chain management etc. However, this can require a dense deployment of readers to cover the working area. Without optimizing reader's location and number, many of them can be redundant, reducing the efficiency of the whole RFID system. There are many algorithms proposed by researchers to solve redundant reader problem, but all these algorithms are based on omni-directional reader antenna patterns, which is not practical. In this paper we present an algorithm for redundant reader elimination for directional antenna. It uses a radio propagation model and also accounts for loss due to multipath fading to model communication between a reader and a tag. The efficiency of the proposed approach was demonstrated while preserving the tag coverage.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.036
GPT teacher head0.253
Teacher spread0.217 · 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