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Record W2537358599

Signal propagation analysis for near-field intra-body communication systems

2013· article· en· W2537358599 on OpenAlexaff
Ajay Babu Guntupalli, Ke Wu

Bibliographic record

VenueInternational Symposium on Antennas and Propagation · 2013
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsUniversité de MontréalPolytechnique Montréal
Fundersnot available
KeywordsCoaxial antennaOpticsAntenna factorAntenna (radio)Antenna measurementTurnstile antennaPhysicsMonopole antennaAntenna apertureRadiation patternAntenna efficiencyTelecommunicationsEngineering
DOInot available

Abstract

fetched live from OpenAlex

This article presents and discusses some of the recent developments on 60 GHz antenna arrays in substrate integrated waveguide (SIW) technology. They include planar linearly polarized (LP) antenna, three dimensional (3-D) high gain LP antenna, multi-layer single circularly polarized (CP) antenna, and 3-D dual circularly polarized antenna (DCP) over 60 GHz frequency range. Single LP antenna is realized by loading antipodal linearly tapered slot antenna (ALTSA) with dielectric rod antenna. The dielectric rod antenna is used as a radiating element to construct 4 × 4 antenna array. Single right-hand circularly polarized (RHCP) antenna is constructed by using SIW as feeding network and CP patch as radiating element. 2 × 2 RHCP array makes use of an aperture coupling method to excite each antenna element. In the final prototype, DCP antenna is constructed by using multi-layer E-plane coupler and rod radiating element. All the proposed antenna arrays are experimentally validated and compared with the simulated counterparts.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.221
Teacher spread0.213 · 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 designSimulation or modeling
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

Citations8
Published2013
Admission routes1
Has abstractyes

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