Evidence map›Paper›PMID 35632280›Full record

ArticleSensors (Basel, Switzerland)2022

On the Possibility of Designing an Advanced Sensor with Particle Sizing Using Dynamic Light Scattering Time Series Spectral Entropy and Artificial Neural Network.

Dan Chicea, Aleksandr S Doroshkevich, Andriy Lyubchyk

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Dan ChiceaResearch Center for Complex Physical Systems, Faculty of Sciences, Lucian Blaga University of Sibiu, 550024 Sibiu, Romania.ORCID 0000-0001-8074-9107
Aleksandr S DoroshkevichDonetsk Institute for Physics and Engineering Named After O.O. Galkin, NAS of Ukraine, 46 Prospect Nauky, 03028 Kyiv, Ukraine.
Andriy LyubchykNanotechcenter LLC, Krzhizhanovsky Str. 3, 03680 Kyiv, Ukraine.

Funding

Lucian Blaga University of Sibiu & Hasso Plattner Foundation LBUS-IRG-2019-05 and LBUS-IRG-2020-06
6 · The paper itself

Abstract

Dynamic Light Scattering is a well-established technique used in particle sizing. An alternative procedure for Dynamic Light Scattering time series processing based on spectral entropy computation and Artificial Neural Networks is described. An error analysis of the proposed method was carried out and the results on both the simulated and on the experimental DLS time series are presented in detail. The results reveal the possibility of designing an advanced sensor capable of detecting particles with a size bigger than a threshold using this alternative for processing the DLS time series.

Indexed as

Neural Networks, ComputerDynamic Light ScatteringEntropyParticle SizeTime Factorsadvanced sensorArtificial Neural NetworkDynamic Light Scatteringparticle sizingspectral entropytime series

Identifiers

PMID35632280
PMCPMC9145617

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.