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Title: Securing threat detection : synergy of technological and neuropsychological factors
Author: Rusconi, E.
ISNI:       0000 0004 5363 5907
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2014
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The success of some current national and international security strategies depends on the accuracy of visual inspections, often achieved via transmission x-ray imaging. Human screeners face the difficulties of complex image interpretation as the resulting images consist of a cluster of superimposed shapes often seen from an unusual perspective. Object detection in transmission x-ray images appears to share challenges analogous to those entailed by the Embedded Figures Test (EFT), as both require disembedding a target from several distracters in a visual Gestalt. It is well documented that individuals diagnosed with Autism Spectrum Disorder (ASD) may show enhanced abilities at the EFT. Their abilities are attributed to a baseline individual aptitude, namely heightened attention to visual detail and sensitivity to trivial changes in the visual environment, of possible genetic origin. Although such aptitude may be emphasised in ASD, it is not necessarily associated with it and it is possible to identify individuals with high attention to detail in the general population. Here we demonstrate for the first time that self-reported Attention to Detail and EFT performance can predict detection abilities with transmission security x-ray images. Further, we develop a novel self-report scale for the security industry, the XRIndex. We validate this scale against Attention to Detail, EFT and aviation security x-ray images, with both untrained participants and professional security screeners. We show that the XRIndex may become a reliable aid-to-selection tool, it can be administered under supervision or remotely and its validity is not undermined by repetition or expertise with the x-ray screening task. Behavioural tasks – namely EFT and mental rotation - may prove valuable too, however their use in a digital version may not be advisable when applicants lack familiarity with computers. Stable personality traits with a significant association to threat detection performance are also identified and may usefully complement information provided by the XRIndex.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available