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Record W2510991278 · doi:10.1109/antem.2016.7550210

Textile-based wideband flexible wearable dielectric resonator antennas for WLAN-band

2016· article· en· W2510991278 on OpenAlexaff
Muhammad M. Tahseen, Ahmed A. Kishk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsGround planeWidebandDielectric resonator antennaAcousticsSlot antennaBandwidth (computing)Electrical engineeringOmnidirectional antennaMaterials scienceDielectricComputer scienceElectronic engineeringAntenna (radio)OptoelectronicsEngineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Flexible wideband dielectric resonator antennas (DRA) are designed using textile materials for wearable application at the wireless local area network (WLAN) band. The antennas are designed with different possible feeding technique e.g. coaxial probe feeding, and the aperture coupled method when feed transmission line is embroidered using conductive thread. Before using textile materials in antenna design, the material parameters are extracted using resonance technique, which are validated with measurements. A solid ground (GND) plane is replaced with shielded fabric GND plane, for more flexibility. To counter the fabrication problems, a fabric (with dielectric constant close to air) covering the DRA and holding it to its accurate position, will be stitched around at the upper layer, that will resolve the possible DRA movement. The proposed DRA antennas provide more than 25 % matching bandwidth, 1-dB gain bandwidth of more than 20 % and the maximum radiation efficiency of 97 % (at 5.8 GHz).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.534

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)0.0000.000

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 head0.013
GPT teacher head0.217
Teacher spread0.203 · 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.

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

Citations10
Published2016
Admission routes1
Has abstractyes

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