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Record W1538953764

77 GHz compact multi-port radar sensor for automotive applications

2011· article· en· W1538953764 on OpenAlexaff
E. Moldovan, Bouraima Boukari, Serioja Ovidiu Tatu, R.G. Bosisio, Ke Wu

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrowave and Dielectric Measurement Techniques
Canadian institutionsPolytechnique MontréalInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsRadarAutomotive industryTransmitterPort (circuit theory)Extremely high frequencyMillimeterElectronic engineeringComputer scienceWaveguideAutomotive electronicsRange (aeronautics)EngineeringElectrical engineeringMaterials scienceOpticsTelecommunicationsPhysicsAerospace engineeringOptoelectronics
DOInot available

Abstract

fetched live from OpenAlex

A compact millimeter wave radar sensor, suitable for automotive applications, is presented in this paper. The work is focused on the design of a multi-port receiver, integrated on a thin ceramic substrate. A multi-port computer model for advanced system simulations is implemented using S-parameter measurements. A test bench is built using standard laboratory equipment, a waveguide transmitter, and the prototype receiver. Simulated and experimental results show a very good relative speed and range measurement precision.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.621
Threshold uncertainty score1.000

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 head0.030
GPT teacher head0.237
Teacher spread0.207 · 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.

Study designBench or experimental
Domainnot available
GenreMethods

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

Citations3
Published2011
Admission routes1
Has abstractyes

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