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Record W4392640853 · doi:10.1117/12.3001100

Mitigating the effects of water vapour absorption within terahertz wireless communication systems

2024· article· en· W4392640853 on OpenAlexaff
Ahmed Adel Nasreldin Mohamed, Alexis N. Guidi, Jonathan F. Holzman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTerahertz technology and applications
Canadian institutionsUniversity of Northern British ColumbiaUniversity of British Columbia
Fundersnot available
KeywordsTerahertz radiationWirelessWater vaporAbsorption (acoustics)Communications systemComputer scienceAbsorption of waterMaterials scienceElectronic engineeringOptoelectronicsRemote sensingTelecommunicationsEngineeringPhysicsGeographyMeteorology

Abstract

fetched live from OpenAlex

Communication technology has shown trends towards wireless systems (for improved mobility) and broader bandwidths (for high data rates). This has led to growing interest in terahertz (THz) wireless communication systems—for which there are great benefits and equally great challenges. Arguably, the single greatest challenge for THz wireless communication systems is the susceptibility of the THz spectrum to water vapour absorption in the free-space/air environment. Our study recognizes this challenge and introduces a physical model through which the water vapour characteristics can be fit and then removed from measured signal characteristics. We show the physical foundations of our model and demonstrate its effectiveness in fitting the water vapour characteristics in measured signals from a THz time-domain spectroscopy system. The theoretical and experimental results show strong agreement, suggesting that the model can be an effective tool for characterizing and mitigating the effects of water vapour absorption in future THz wireless communication systems.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.004
GPT teacher head0.200
Teacher spread0.196 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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