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Record W2164994143 · doi:10.1109/mwsym.1991.147093

An improved TLM full-wave analysis using a two dimensional mesh

2002· article· en· W2164994143 on OpenAlexaff
Hang Jin, R. Vahldieck, S. Xiao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsShielded cableTransmission-line matrix methodTransmission lineComputer scienceNode (physics)Transmission (telecommunications)Matrix (chemical analysis)Space (punctuation)Line (geometry)Electronic engineeringReduction (mathematics)Computational scienceElectric power transmissionTopology (electrical circuits)AlgorithmPhysicsAcousticsElectrical engineeringEngineeringMathematicsMaterials scienceTelecommunicationsGeometryComputational electromagnetics

Abstract

fetched live from OpenAlex

An improved TLM (transmission line matrix) full-wave analysis method based on a novel TLM node is described. Compared to the conventional TLM full-wave analysis, which requires a three-dimensional mesh, this method utilizes only a two-dimensional transmission line mesh to fully characterize dispersive guided structures. This leads to a significant reduction in CPU time and memory space, and makes the TLM method an even more attractive tool in the analysis of arbitrarily shaped guided structures. Numerical results are given for shielded and suspended coupled dielectric waveguides.>

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.032
GPT teacher head0.290
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations17
Published2002
Admission routes1
Has abstractyes

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