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Analysis of unbounded and bounded circuits considering finite substrate extent and inhomogeneous dielectric layer

2000· article· en· W2053244477 on OpenAlexaff
Xiaohong Jiang, Ke Wu

Bibliographic record

VenueInternational Journal of Numerical Modelling Electronic Networks Devices and Fields · 2000
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsClassification of discontinuitiesFinite thicknessDielectricMicrostripLossy compressionResonatorBounded functionBoundary value problemMaterials scienceLeakage (economics)RadiationPhysicsMathematical analysisOpticsMathematicsOptoelectronicsMechanics

Abstract

fetched live from OpenAlex

A generalized method of lines algorithm is presented for characterizing unbounded and bounded circuits. Finite substrate extent and inhomogeneous dielectric layers are rigorously considered in this field-based model. Radiating properties of unbounded regular and irregular microstrip patch resonators and arrays are studied with emphasis on effects of mutual coupling and finite dielectric extent on complex resonant frequencies. In addition, unbounded loss effects for microstrip open-end and 90° angular bend deposited on finite substrate as well as chip-to-chip discontinuities are also investigated. Our developed algorithm incorporates an absorbing boundary condition using the Padé approximation to simulate any potential radiation and leakage losses for resonator structures while an improved lossy absorbing boundary condition (LABC) that can handle both propagating and evanescent waves is used to determine the unbounded effects for waveguiding structures. Results indicate interesting properties of the finite extent of dielectric substrate on resonance and radiation characteristics, and also on unbounded radiation and leakage losses. Copyright © 2000 John Wiley & Sons, Ltd.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.553
Threshold uncertainty score0.525

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 head0.012
GPT teacher head0.219
Teacher spread0.208 · 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 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

Citations0
Published2000
Admission routes1
Has abstractyes

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