Evidence map›Paper›PMID 35336290›Full record

ReviewSensors (Basel, Switzerland)2022

Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection.

Dmytro Mamchur, Janis Peksa, Soledad Le Clainche, Ricardo Vinuesa

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

4 authors.

Dmytro MamchurInformation Technologies Department, Turiba University, Graudu Street 68, LV-1058 Riga, Latvia.
Janis PeksaInstitute of Information Technology, Riga Technical University, Kalku Street 1, LV-1658 Riga, Latvia.ORCID 0000-0003-4125-494X
Soledad Le ClaincheSchool of Aerospace Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain.ORCID 0000-0003-3605-7351
Ricardo VinuesaFLOW, Engineering Mechanics, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden.ORCID 0000-0001-6570-5499

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increase in trading and travelling flows has resulted in the need for non-intrusive object inspection and identification methods. Traditional techniques proved to be effective for decades; however, with the latest advances in technology, the intruder can implement more sophisticated methods to bypass inspection points control techniques. The present study provides an overview of the existing and developing techniques for non-intrusive inspection control, current research trends, and future challenges in the field. Both traditional and developing methods, techniques, and technologies were analyzed with the use of traditional and novel sensor types. Finally, it was concluded that the improvement of non-intrusive inspection experience could be gained with the additional use of novel types of sensors (such as biosensors) combined with traditional techniques (X-ray inspection).

Indexed as

Biosensing TechniquesTechnologyRadiographyartificial intelligencebiosensorclassificationnon-intrusive inspectionX-ray

Identifiers

PMID35336290
PMCPMC8954081

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.