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Record W2342076059 · doi:10.5539/mas.v10n5p186

Design and Testing of Radiofrequency Spherical four Coils

2016· article· en· W2342076059 on OpenAlexvenueno aff
S. M. A. Ghaly, Khalid A. Alsnaie, S. Al-Sowayan

Bibliographic record

VenueModern Applied Science · 2016
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsnot available
Fundersnot available
KeywordsHomogeneity (statistics)Helmholtz coilElectromagnetic coilHelmholtz free energyMagnetic fieldAcousticsCoaxialNuclear magnetic resonancePhysicsComputer scienceElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

<p>In this paper, we present the design and testing of a radiofrequency prototype coil with good performances in terms of B<sub>1</sub> magnetic field homogeneity and can be utilized for Magnetic Resonance Imaging. It is constituted of four coaxial separately tuned rings of wire and symmetrically located on a spherical surface. Compared to standard Helmholtz pair, which has 2nd-order magnetic field homogeneity, it yields to improvement in field homogeneity, while preserving the simplicity of design. The four coils of proposed structure are tuned to the same frequency. The proposed structure gets at 4th-order magnetic field homogeneity by optimizing the distance between rings and the diameters of outer loops. An electrical modeling of the four-coil system taking into account the coupling effects between all rings permits to determine the resonance frequency in the homogenous mode. Measurements of B1 field homogeneity were introduced in free space. Compared to the Helmholtz coil, the proposed structure presents good performances in terms of B1 homogeneity, quality factor and sensitivity. The design of proposed coil has been optimized for best SNR performances. Globally, this work claims to be a contribution to the study of the four-coil RF systems derived from the Helmholtz pairs.</p>

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.766
Threshold uncertainty score0.351

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 head0.030
GPT teacher head0.206
Teacher spread0.176 · 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 designSimulation or modeling
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

Citations8
Published2016
Admission routes1
Has abstractyes

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