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Record W2133582051 · doi:10.1109/aps.2010.5561663

Optimized patch array antenna for 60 GHz wireless applications

2010· article· en· W2133582051 on OpenAlexafffund
Behzad Biglarbegian, Mohammad Fakharzadeh, Mohammad‐Reza Nezhad‐Ahmadi, S. Safavi‐Naeini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Waterloo
FundersNational Research Council Canada
KeywordsWirelessComputer scienceGigabitDirectional antennaBroadbandConformal antennaAntenna (radio)Wireless broadbandPersonal area networkElectronic engineeringElectrical engineeringTelecommunicationsWireless networkComputer networkSlot antennaEngineering

Abstract

fetched live from OpenAlex

The recently developed 60 GHz standard provides a 7 GHz license-free band around 60 GHz for high data-rate wireless communications at the rate of gigabits per second. Due to huge interest in broadband Wireless Personal Area Network (WPAN) applications, a low cost, miniaturized and high performance radio technology at 60 GHz is on high demand. Antenna is a key element and several antennas have been introduced for an increasing number of applications. Patch antennas are among the best candidates for implementing in mmwave band due to their low profile and cost. In this paper, considering system requirements of an indoor wireless link to comply with IEEE 802.15.3c and ECMA 60GHz standards, a 2x2 array of patch antennas has been optimized, fabricated and measured.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.219
Teacher spread0.211 · 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 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

Citations13
Published2010
Admission routes2
Has abstractyes

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