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Record W2153818665 · doi:10.1109/iscas.2008.4541860

MEMS automotive collision avoidence radar beamformer

2008· article· en· W2153818665 on OpenAlexaff
Ahmad Sinjari, Sazzadur Chowdhury

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsLens (geology)Microelectromechanical systemsBeam steeringRadarMicrostripOpticsLuneburg lensMaterials scienceFootprintBeam (structure)EngineeringElectrical engineeringOptoelectronicsAntenna (radio)PhysicsAerospace engineering

Abstract

fetched live from OpenAlex

The design of a MEMS-based Rotman lens beamformer that uses a high dielectric constant lead zirconium titanate (PZT) thick film as the insulating material inside the lens cavity has been presented. The 56 mum thick Rotman lens has a footprint area of 5.5 times 7.1 mm , incorporates 3 beam ports, 5 array ports, and operates at 77 GHz. The lens has been designed to have a mainlobe gain of 35 dB with a scan angle of 4 degrees. The small size of the Rotman lens beamformer enables to stack it vertically or horizontally to realize a compact MEMS-based radar when used in conjunction with microstrip antennas and necessary microelectronics circuits. The device could be used for an automotive collision avoidance system to detect the proximity of other vehicles or obstacles.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.013
GPT teacher head0.199
Teacher spread0.186 · 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
Published2008
Admission routes1
Has abstractyes

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