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Record W2346385517 · doi:10.4071/2016cicmt-tha22

A comparative study on four different transmission lines in LTCC for 60 GHz applications

2016· article· en· W2346385517 on OpenAlexaff
Aria Isapour, Dorra Bahloul, Ammar B. Kouki

Bibliographic record

VenueAdditional Conferences (Device Packaging HiTEC HiTEN & CICMT) · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsStriplineMicrostripBandwidth (computing)WirelessTelecommunicationsTransmission lineElectronic engineeringElectrical engineeringCoplanar waveguideFabricationCeramicInsertion lossComputer scienceEngineeringMaterials scienceMicrowave

Abstract

fetched live from OpenAlex

Abstract The wireless telecommunication systems have an undeniable role in today's society. The rapid progress of wireless services and applications accelerates demands for high data-rate reliable systems. The 60 GHz band with its 5 GHz globally unlicensed available spectrum, provides a great opportunity for the next generation of high data-rate wireless communication. Despite this attractive bandwidth surrounding 60 GHz, there are still many challenges to be addressed such as the loss performance and the integration with other systems. Low Temperature Cofired Ceramic (LTCC) technology, with its unique and mature multilayer fabrication process, has excellent capability of realizing miniaturized 3D low loss structures to overcome these challenges. Since, one of the key components in any communication system for both interconnecting and designing components is Low loss transmission lines, in this article we overview the performances and challenges for four different most practical transmission lines at 60 GHz in LTCC: Microstrip, Stripline, Coplanar Waveguide (CPW), and LTCC Integrated Waveguide (LIW).

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
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)0.0010.000

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 head0.045
GPT teacher head0.279
Teacher spread0.235 · 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 designNot applicable
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

Citations2
Published2016
Admission routes1
Has abstractyes

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