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Monte Carlo Simulations for the Detection of Buried Objects Using Single Sided Backscattered Radiation

Overview of attention for article published in PLOS ONE, September 2015
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Article details
Title
Monte Carlo Simulations for the Detection of Buried Objects Using Single Sided Backscattered Radiation
Published in
PLOS ONE, September 2015
DOI 10.1371/journal.pone.0135769
Pubmed ID
Authors
Abstract

Detection of buried improvised explosive devices (IEDs) is a delicate task, leading to a need to develop sensitive stand-off detection technology. The shape, composition and size of the IEDs can be expected to be revised over time in an effort to overcome increasingly sophisticated detection methods. As an example, for the most part, landmines are found through metal detection which has led to increasing use of non-ferrous materials such as wood or plastic containers for chemical based explosives being developed. Monte Carlo simulations have been undertaken considering three different commercially available detector materials (hyperpure-Ge (HPGe), lanthanum(III) bromide (LaBr) and thallium activated sodium iodide (NaI(Tl)), applied at a stand-off distance of 50 cm from the surface and burial depths of 0, 5 and 10 cm, with sand as the obfuscating medium. Target materials representing medium density wood and mild steel have been considered. Each detector has been modelled as a 10 cm thick cylinder with a 20 cm diameter. It appears that HPGe represents the most promising detector for this application. Although it was not the highest density material studied, its excellent energy resolving capability leads to the highest quality spectra from which detection decisions can be inferred. The simulation work undertaken here suggests that a vehicle-born threat detection system could be envisaged using a single betatron and a series of detectors operating in parallel observing the space directly in front of the vehicle path. Furthermore, results show that non-ferrous materials such as wood can be effectively discerned in such remote-operated detection system, with the potential to apply a signature analysis template matching technique for real-time analysis of such data.

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The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 5 23%
Student > Bachelor 3 14%
Student > Ph. D. Student 2 9%
Student > Master 2 9%
Professor > Associate Professor 2 9%
Other 2 9%
Unknown 6 27%
Readers by discipline
Readers by discipline Count As %
Physics and Astronomy 6 27%
Arts and Humanities 2 9%
Chemical Engineering 1 5%
Agricultural and Biological Sciences 1 5%
Computer Science 1 5%
Other 4 18%
Unknown 7 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 September 2015.
All research outputs
#18,425,370
of 22,826,360 outputs
Outputs from PLOS ONE
#154,936
of 194,766 outputs
Outputs of similar age
#192,820
of 267,498 outputs
Outputs of similar age from PLOS ONE
#4,481
of 5,806 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,766 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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We're also able to compare this research output to 5,806 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.