MétaCan
Menu
Back to cohort
Record W2162656810 · doi:10.1109/mwsym.2012.6259698

MEMS multiport switches and switch matrices for satellite applications

2012· article· en· W2162656810 on OpenAlexaff
Mojgan Daneshmand, Arash A. Fomani, Mohamed M. Fahmi, Jorge A. Ruiz‐Cruz, Raafat R. Mansour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of WaterlooUniversity of Alberta
Fundersnot available
KeywordsInterconnectivityMicroelectromechanical systemsPayload (computing)Redundancy (engineering)Communications satelliteSatelliteComputer scienceSpace technologyElectronic engineeringElectrical engineeringEngineeringAerospace engineeringComputer networkMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

Mass and volume of the payload electronics are significant contributors to the overall cost of space systems. Satellite systems rely on switch matrices to provide system redundancy and to enhance capacity by providing flexible interconnectivity. The RF-MEMS technology offers the potential of large reductions in the mass and volume of satellite switch matrices leading to a significant cost reduction of satellite systems. The technology has also the potential of accelerating the development and implementation of new advanced satellite systems. This paper presents various configurations for highly miniature RF MEMS switch matrices. It also presents novel configurations for high power multiport waveguide switches that eliminate the need to use bulky motors.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.014
GPT teacher head0.243
Teacher spread0.229 · 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 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

Citations4
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced MEMS and NEMS TechnologiesFrench-language works237,207