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Record W3162371140 · doi:10.1002/mmce.22716

Characteristic impedance of integrated substrate gap waveguide

2021· article· en· W3162371140 on OpenAlexaff
Yuchao Sa, Dongya Shen, Xiupu Zhang

Bibliographic record

VenueInternational Journal of RF and Microwave Computer-Aided Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
FundersNational Natural Science Foundation of China
KeywordsHFSSTransmission lineWaveguideCharacteristic impedanceElectrical impedanceCapacitanceMathematical analysisTransverse planeFunction (biology)Fourier transformComputational physicsScattering parametersOpticsAcousticsMathematicsPhysicsComputer scienceEngineeringTelecommunicationsAntenna (radio)Microstrip antenna

Abstract

fetched live from OpenAlex

A theoretical method is presented by which characteristic impedance of integrated substrate gap waveguide (ISGW) is analyzed. The method is essentially based on a variational function for the transmission-line capacitance in Fourier-transformed domain with test/trial functions of charge density distribution, in which transverse transmission-line Green's function is used to facilitate the variational analysis. The presented method simplifies the determination of the potential distribution function which must satisfy the complex boundary conditions of the ISGW. Moreover, two types of ISGW, that is, two- and three-layer ISGW, working in K and E band are considered and analyzed by this method. Finally, the method is compared to the simulated using High Frequency Structure Simulator (HFSS) as well as measurements, and it is shown that the method leads to a very small inaccuracy compared to previously reported methods.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
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 head0.009
GPT teacher head0.210
Teacher spread0.200 · 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
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

Citations1
Published2021
Admission routes1
Has abstractyes

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