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Using Gypsum Material as the Substrate for Inside Wall Embedded Wireless IoT Sensors

2022· article· en· W4281756461 on OpenAlexaff
Zahra Badamchi, Tarek Djerafi

Bibliographic record

Venue2021 51st European Microwave Conference (EuMC) · 2022
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsGypsumPlanarMaterials scienceSubstrate (aquarium)WirelessDielectricBandwidth (computing)Internet of ThingsAntenna (radio)Computer scienceOptoelectronicsElectronic engineeringAcousticsElectrical engineeringComposite materialTelecommunicationsEngineeringPhysicsEmbedded systemGeology

Abstract

fetched live from OpenAlex

In this paper the drywall (Gypsum material) which is the main material that is commonly used inside the buildings is directly considered as the dielectric substrate to develop two planar antennas. This makes it possible to take into account the effect of surrounding materials by integrating the radiating antenna with these materials while reducing the cost for Internet of Things (IoT) applications in smart buildings. To verify the capability of Gypsum material, two planar antennas are designed to operate at 2.4 GHz IEEE 802.15.4 standard. The measured results reveal a bandwidth of 2.37-2.53 GHz (6.5%) and a gain level of 5.83 dBi for the fabricated patch antenna, while the same characteristics for the fabricated modified high gain antenna are 2.2-2.8 GHz (24%) and 12.83 dBi, respectively. The measurements are in fine agreement with simulation predictions which verifies the usefulness of using the Gypsum material as the substrate.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
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 science0.0010.000
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 head0.040
GPT teacher head0.235
Teacher spread0.195 · 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 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
Published2022
Admission routes1
Has abstractyes

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