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Record W2514348042 · doi:10.1109/tmtt.2016.2601910

Mode Composite Waveguide

2016· article· en· W2514348042 on OpenAlexafffund
Jiapin Guo, Tarek Djerafi, Ke Wu

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsInstitut National de la Recherche ScientifiquePolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWaveguideMicrostripMaterials scienceMicrowaveOpticsElectronic circuitPrinted circuit boardComposite numberCoplanar waveguideInsertion lossOptoelectronicsElectrical engineeringPhysicsEngineeringTelecommunicationsComposite material

Abstract

fetched live from OpenAlex

In this paper, mode composite waveguide (MCW) is proposed, which consists of inner and outer wave-guiding duo structures. The outer structure acts as a rectangular coaxial line suitable for lower frequency operation for its compact size, while the inner structure works as a rectangular waveguide suitable for higher frequency operation thanks to its simple structure and low loss. The MCW can propagate signals in the inner waveguide with TE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10</sub> mode and/or the outer waveguide with TEM mode depending on frequency to achieve optimal performance for both low- and high-frequency operations. In this paper, the fundamental waveguide parameters and higher order modes of the duo waveguides are examined. The proposed MCW prototypes are fabricated on a triple-layer PCB structure using the emerging substrate integration techniques. The MCW is fabricated and measured through the proposed microstrip line to the inner and outer waveguide transitions, and an MCW simultaneous feeding circuit is also presented. For this simultaneous feeding circuit, the good matching is achieved from 7.5 to 10.5 GHz for the low-frequency operation and from 25 to 39 GHz for the high-frequency operation, respectively.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.894
Threshold uncertainty score0.775

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 head0.007
GPT teacher head0.217
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 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

Citations44
Published2016
Admission routes2
Has abstractyes

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