MétaCan
Menu
Back to cohort
Record W3045385032 · doi:10.1109/tcsii.2020.3011513

Controllable Orthogonal Mode Rejection for Smart Polarization Diversity at Millimeter-Wave Frequency

2020· article· en· W3045385032 on OpenAlexafffund
Moein Noferesti, Tarek Djerafi

Bibliographic record

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInsertion lossOpticsMicrostripMaterials scienceResonatorExtremely high frequencyPolarization (electrochemistry)Orthogonal polarization spectral imagingOptoelectronicsPlanarBandwidth (computing)Transmission linePhysicsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

A ferromagnetic loaded device for controllable orthogonal mode rejection at millimeter-Wave is presented in this brief. The device is based on dual image dielectric guide (DIDG) capable of supporting both vertical (V-mode) and horizontal (H-mode) polarization. Two ferrite pillboxes are placed vertically (axis parallel to V-mode) and horizontally (axis parallel to H-mode) beside and above the DIDG, receptively. These pillboxes act as whispering gallery mode resonators interacting with the mode parallel to their axis depending on the applied magnetic DC bias, resulting in controllable mode rejection beneficial in smart antenna systems. Despite traditional magnetically tunable ferrite based components, the proposed design is mostly based on the direction of the magnetic bias requiring a small magnetic bias of 1 mT. An aperture coupling transition from Microstrip line to DIDG is used to perform orthogonal mode decomposition as well as proposing planar circuits excitation and integration. Measured polarization filtering bandwidth provided by each pillbox is 0.4 GHz having insertion loss higher than 10 dB (no transmission) and port isolation of higher than 15 dB. Insertion loss of the case, when the rejection mechanism is off, is around 3 dB.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
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 studies0.0010.000
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 head0.026
GPT teacher head0.202
Teacher spread0.176 · 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 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

Citations5
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Transactions on Circuits & Systems II Express BriefsSame topicMicrowave Engineering and WaveguidesFrench-language works237,207