ArticleScientific reports2024
Resonance frequency prediction of dielectric antennas for liquid sensing via support vector regression.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents a slot antenna integrated with a split ring resonator (SRR) and feed line, designed to achieve a high Q-factor while maximizing channel capacity utilization. By incorporating a lens into the dielectric resonator antenna (DRA), we enhance both bandwidth and directivity, with the dielectric material's permittivity serving as a key control parameter for radiation characteristics. We explore water and ethanol as controllable dielectrics within the terahertz (THz) frequency range (0.5-1 THz), implementing these liquids through microfluidic techniques. This novel design serves two purposes, functioning as both an antenna system and a highly sensitive material sensing device. The antenna's performance is evaluated using the Debye model for pure water and ethanol, with electromagnetic full-wave simulations employing the Finite Integration Technique (FIT) to model both the antenna and microchannel structures. For predicting resonant frequencies based on antenna dimensions, we implement a Support Vector Regression (SVR) algorithm, comparing its performance against various models including Linear Regression, Regression Trees, Ensemble Bagged Trees, Ensemble Boosted Trees, and Three-layered Neural Network Models. The SVR demonstrates superior prediction accuracy by effectively capturing non-linear relationships between antenna dimensions and resonant frequencies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.