Airport Baggage Screening Research Articles

Microlocal properties of seven-dimensional lemon and apple Radon transforms with applications in Compton scattering tomography

We present a microlocal analysis of two novel Radon transforms of interest in Compton scattering tomography, which map compactly supported L 2 functions to their integrals over seven-dimensional sets of apple and lemon surfaces. Specifically, we show that the apple and lemon transforms are elliptic Fourier integral operators, which satisfy the Bolker condition. After an analysis of the full seven-dimensional case, we focus our attention on nD subsets of apple and lemon surfaces with fixed central axis, where n < 7. Such subsets of surface integrals have applications in airport baggage and security screening. When the data dimensionality is restricted, the apple transform is shown to violate the Bolker condition, and there are artifacts which occur on apple–cylinder intersections. The lemon transform is shown to satisfy the Bolker condition, when the support of the function is restricted to the strip .

The relationship between the subjective experience of real-world cognitive failures and objective target-detection performance in visual search

Visual search is a common occurrence in everyday life, such as searching for the location of keys, identifying a friend in a crowd, or scanning an upcoming intersection for hazards while driving. Visual search is also used in professional contexts, such as medical diagnostic imaging and airport baggage screening. These contexts are often characterised by low-prevalence or rare targets. Here we tested whether individual differences in the detection of targets in visual search could be predicted from variables derived from the rich informational source of participants' subjective experience of their cognitive and attentional function in everyday life. We tested this in both low-prevalence (Experiment 1) and high-prevalence (Experiment 2) visual search conditions. In both experiments, participants completed a visual search with arrays containing multiple photorealistic objects, and their task was to detect the presence of a gun. Following this, they completed the Cognitive Failures Questionnaire (CFQ) and the Attentional Control Scale (ACS). In Experiment 1, the target was present on 2% of trials, while in Experiment 2, it was present on 50%. In both experiments, participants' scores on the False Triggering component of the CFQ were negatively associated with accuracy on target-present trials, while participants' scores on the Forgetfulness component of the CFQ were positively associated with target-present accuracy. These results show that objective performance in visual search can be predicted from subjective experiences of cognitive function. They also highlight that the CFQ is not monolithic. Instead, the CFQ subfactors can have qualitatively different relationships with performance. Theoretical and practical implications are discussed.

Compressed sensing two-dimensional Bragg scatter imaging.

Here we introduce a new reconstruction technique for two-dimensional Bragg scattering tomography (BST), based on the Radon transform models of Webber and Miller [Inverse Probl. Imaging15, 683 (2021).10.3934/ipi.2021010]. Our method uses a combination of ideas from multibang control and microlocal analysis to construct an objective function which can regularize the BST artifacts; specifically the boundary artifacts due to sharp cutoff in sinogram space (as observed in [arXiv preprint, arXiv:2007.00208 (2020)]), and artifacts arising from approximations made in constructing the model used for inversion. We then test our algorithm in a variety of Monte Carlo (MC) simulated examples of practical interest in airport baggage screening and threat detection. The data used in our studies is generated with a novel Monte-Carlo code presented here. The model, which is available from the authors upon request, captures both the Bragg scatter effects described by BST as well as beam attenuation and Compton scatter.

Bragg scattering tomography

Here we introduce a new forward model and imaging modality for Bragg Scattering Tomography (BST). The model we propose is based on an X-ray portal scanner with linear detector collimation, currently being developed for use in airport baggage screening. The geometry under consideration leads us to a novel two-dimensional inverse problem, where we aim to reconstruct the Bragg scattering differential cross section function from its integrals over a set of symmetric \begin{document}$ C^2 $\end{document} curves in the plane. The integral transform which describes the forward problem in BST is a new type of Radon transform, which we introduce and denote as the Bragg transform. We provide new injectivity results for the Bragg transform here, and describe how the conditions of our theorems can be applied to assist in the machine design of the portal scanner. Further we provide an extension of our results to \begin{document}$ n $\end{document} -dimensions, where a generalization of the Bragg transform is introduced. Here we aim to reconstruct a real valued function on \begin{document}$ \mathbb{R}^{n+1} $\end{document} from its integrals over \begin{document}$ n $\end{document} -dimensional surfaces of revolution of \begin{document}$ C^2 $\end{document} curves embedded in \begin{document}$ \mathbb{R}^{n+1} $\end{document} . Injectivity proofs are provided also for the generalized Bragg transform.

A Spectrum-Adaptive Decomposition Method for Effective Atomic Number Estimation Using Dual Energy CT

Dual Energy Computed Tomography (DECT) is expected to become a significant tool for voxel-based detection of hazardous materials in airport baggage screening. The traditional approach to DECT imaging involves collecting the projection data using two different X-ray spectra and then decomposing the data thus collected into line integrals of two independent characterizations of the material properties. Typically, one of these characterizations involves the effective atomic number (Zeff) of the materials. However, with the X-ray spectral energies typically used for DECT imaging, the current best-practice approaches for dualenergy decomposition yield Zeff values whose accuracy range is limited to only a subset of the periodic-table elements, more specifically to (Z &lt; 30). Although this estimation can be improved by using a system-independent ρe — Ze (SIRZ) space, the SIRZ transformation does not efficiently model the polychromatic nature of the X-ray spectra typically used in physical CT scanners. In this paper, we present a new decomposition method, AdaSIRZ, that corrects this shortcoming by adapting the SIRZ decomposition to the entire spectrum of an X-ray source. The method reformulates the X-ray attenuation equations as direct functions of (ρe, Ze) and solves for the coefficients using bounded nonlinear least-squares optimization. Performance comparison of AdaSIRZ with other Zeff estimation methods on different sets of real DECT images shows that AdaSIRZ provides a higher output accuracy for Zeff image reconstructions for a wider range of object materials.

Compton scattering tomography in translational geometries

Here we present new L2 injectivity results for 2D and 3D Compton scattering tomography (CST) problems in translational geometries. The results are proven through the explicit inversion of a new toric section and apple Radon transform, which describe novel 2D and 3D acquisition geometries in CST. The geometry considered has potential applications in airport baggage screening and threat detection. We also present a generalization of our injectivity results in 3D to Radon transforms which describe the integrals of the charge density over the surfaces of revolution of a class of C1 curves.

More is better: Relative prevalence of multiple targets affects search accuracy.

In real-world searches such as airport baggage screening and radiological examinations, miss errors can be life threatening. Misses increase for additional targets after detecting an initial target, termed "subsequent search misses" (SSMs), and also when targets are more often absent than present, termed the low-prevalence effect. Real-world search tasks often contain more than one target, but the prevalence of these multitarget occasions varies. For example, a cancerous tumor sometimes coexists with a benign tumor and sometimes exists alone. This study aims to investigate how the relative prevalence of multiple targets affects search accuracy. Naive observers searched for all Ts (zero, one, or two) among Ls. In Experiment 1, SSMs occurred in small but not large set sizes, which may be explained by classic capacity limit effects such as the attentional blink and repetition blindness. Experiment 2 showed an interaction between SSMs and the relative prevalence of dual-target trials: Low prevalence of dual-target trials increased SSMs relative to high prevalence dual-target trials. The prevalence of dual-target trials did not affect accuracy on single-target trials. These results may provide a novel avenue for reducing misses by increasing the prevalence of instances with multiple targets. Future efforts should take into account the relative prevalence of multiple targets to effectively reduce life-threatening miss errors.

Can Radiologists Learn From Airport Baggage Screening?: A Survey About Using Fictional Patients for Quality Assurance

For both airport baggage screeners and radiologists, low target prevalence is associated with low detection rate, a phenomenon known as "prevalence effect." In airport baggage screening, the target prevalence is artificially increased with fictional weapons that are digitally superimposed on real baggage. This strategy improves the detection rate of real weapons and also allows airport supervisors to monitor screener performance. A similar strategy using fictional patients could be applied in radiology. The purpose of this study was twofold: (1) to review the psychophysics literature regarding low target prevalence and (2) to survey radiologists' attitudes toward using fictional patients as a quality assurance tool. We reviewed the psychophysics literature on low target prevalence and airport x-ray baggage screeners. An online survey was e-mailed to all members of the Association of University Radiologists to determine their attitudes toward using fictional patients in radiology. Of the 1503 Association of University Radiologists member recipients, there were 153 respondents (10% response rate). When asked whether the use of fictional patients was a good idea, the responses were as follows: disagree (44%), neutral (25%), and agree (31%). The most frequent concern was the time taken away from doing clinical work (89% of the respondents). The psychophysics literature supports the use of fictional targets to mitigate the prevalence effect. However, the use of fictional patients is not a popular idea among academic radiologists.

A fuzzy system to support the configuration of baggage screening devices at an airport

An airport is a complex engineering system; it is composed of many elements interconnected with numerous internal relations with a strongly pronounced role of the human factor. One of the specific tasks carried out by the airport managing entity (AME) is to configure the airport security system (ApSS) so that to attain the expected level of confidence in the airport safety and security. This task consists in selection of infrastructure, technical equipment, allocation of personnel and financial means that are necessary to perform all functions of the ApSS. One of the aspects of the configuration of the ApSS is the allocation of available X-ray baggage screening devices searching for items prohibited for transportation. To make this allocation, we need to know how effective these devices are (in terms of detecting prohibited items). This assessment is dependent on several factors which are treated as linguistic variables and are input to fuzzy inference system: the ability to detect explosives, the number of detection lines, the effectiveness of the TIP (Threat Image Projection) system and the age of the machine. Some of these elements are difficult to objective assessment, as they are heavily dependent on the human factor or the information is uncertain or incomplete. So fuzzy ApSS analysis is proposed. The output from the fuzzy inference system is linguistic variable Device evaluation. The meaning of this variable is the ability to protect the aircraft against prohibited items. The proposed new method of assessing the airport baggage screening system involves the construction of a hierarchical fuzzy inference system. The usefulness of the method is exemplified for Katowice–Pyrzowice International Airport, for which an assessment of devices has been performed. The results show that not only allocation of specific devices for specific control points is important for the security of passengers. Also important are the locally accepted principles of their work, which so far are not specified by international regulations. This applies for instance to the selection of the number and frequency of TIP images. Experiments show that the proposed approach can be effective as part of an expert system for supporting the airport operator in configuring ApSS.

Even in correctable search, some types of rare targets are frequently missed.

Socially important visual search tasks, such as airport baggage screening and tumor detection, place observers in situations where the targets are rare and the consequences of failed detection are substantial. Recent laboratory studies have demonstrated that low target prevalence yields substantially higher miss errors than do high-prevalence conditions, in which the same targets appear frequently (Wolfe, Horowitz, & Kenner, 2005; Wolfe et al., 2007). Under some circumstances, this "prevalence effect" can be eliminated simply by allowing observers to correct their last response (Fleck & Mitroff, 2007). However, in three experiments involving search of realistic X-ray luggage images, we found that the prevalence effect is eliminated neither by giving observers the choice to correct a previous response nor by requiring observers to confirm their responses. This prevalence effect, obtained when no trial-by-trial feedback was given, was smaller than the effect obtained when observers searched through the same stimuli but were given trial-by-trial feedback about accuracy. We suggest that low prevalence puts pressure on observers in any search task, and that the diverse symptoms of that pressure manifest themselves differently in different situations. In some relatively simple search tasks, misses may result from motor or response errors. In other, more complex tasks, shifts in decision criteria appear to be an important contributor.

Rare Targets Are Rarely Missed in Correctable Search

Failing to find a tumor in an x-ray scan or a gun in an airport baggage screening can have dire consequences, making it fundamentally important to elucidate the mechanisms that hinder performance in such visual searches. Recent laboratory work has indicated that low target prevalence can lead to disturbingly high miss rates in visual search. Here, however, we demonstrate that misses in low-prevalence searches can be readily abated. When targets are rarely present, observers adapt by responding more quickly, and miss rates are high. Critically, though, these misses are often due to response-execution errors, not perceptual or identification errors: Observers know a target was present, but just respond too quickly. When provided an opportunity to correct their last response, observers can catch their mistakes. Thus, low target prevalence may not be a generalizable cause of high miss rates in visual search.

What does airport baggage screening have to do with cervical cancer screening?

At the most obvious level, baggage screening and cervical cancer screening are both visual search tasks in which an observer searches for targets in visual displays containing distracting items. This talk will introduce you to some of the basic principles that have been uncovered in many laboratories over the last thirty years and more. More than this, however, baggage screening and cervical cancer screening share several other properties. They are both socially important, difficult tasks where ‘miss’ errors may be a matter of life and death. Of most relevance to this talk, they are both tasks involving search for rare items – what we will call low ‘target prevalence’. We have examined the effect of target prevalence on the likelihood that targets will be missed in a variety of visual search tasks including simulations of baggage screening. Miss error rates are much higher at low prevalence (targets present on 1%–2% of trials) than at high prevalence (targets present on 50% of trials). In several experiments, we have shown that this prevalence effect is very robust. It can be replicated with different types of stimuli from oriented lines to x‐ray images of luggage. I will describe a couple of ways to reduce or eliminate this effect. Finally, I will demonstrate that, even if a search task is easy, you can readily miss something that is happening right in front of your eyes.

Integer Programming Models for Deployment of Airport Baggage Screening Security Devices

Aviation security is an important problem of national interest and concern. Baggage screening security devices and operations at airports throughout the United States provide an important defense against terrorist actions targeted at commercial aircraft. Determining where to deploy such devices, and how to best use them can be quite challenging. This paper presents NP-complete decision problems concerning the deployment and utilization of baggage screening security devices. These problems incorporate three different deployment performance measures: uncovered baggage segments, uncovered flight segments, and uncovered passenger segments. Integer programming models are formulated to address optimization versions of these problems and to identify optimal baggage screening security device deployments (i.e., determine the number and type of baggage screening security devices that should be placed at different airports, and determining which baggage should be screened with such devices). The models are illustrated with an example that incorporates data extracted from the Official Airline Guide (OAG).

Weapons Detection System for Airport Baggage Screening

Weapons Detection System for Airport Baggage Screening

Watching Single Cells Pay Attention

Visual search is a task that each of us rapidly and efficiently performs a thousand times a day, from searching for a coffee cup to looking for a face in a crowd. As a society, we have created many artificial and imperfect but critically important search tasks, such as airport baggage screening and routine mammography. In his Perspective, [Wolfe][1] discusses new work ([ Bichot et al .][2]) that provides insights into how the primate brain performs complex visual search tasks, which might shed light on ways to improve the imperfect artificial search tasks on which we all depend. [1]: http://www.sciencemag.org/cgi/content/full/308/5721/503 [2]: http://www.sciencemag.org/cgi/content/short/308/5721/529

Modeling aviation baggage screening security systems: a case study

Aviation security protects vital national interests, as well as passengers and aircraft. Key components of an aviation security system include baggage and passenger screening devices and operations. Determining how and where to assign (deploy) such devices can be quite challenging. Moreover, even after such systems are in place, it can be difficult to measure their effectiveness. This paper describes how discrete optimization models can be used to address these questions, based on three performance measures that quantify the effectiveness of airport baggage screening security device systems. These models are used to solve for optimal airport baggage screening security device deployments considering the number of passengers on a set of flights who have not been cleared using a security risk assessment system in use by the Federal Aviation Administration (i.e., passengers whose baggage is subjected to screening), the number of flights in this set, and the size of the aircraft for such flights. Several examples are provided to illustrate these results, including an example that uses data available from the Official Airline Guide.

Taking on terrorism

The 11th day of September 2001 began with a tragedy beyond comprehension. It ended in a cacophony of outrage, blame, and urgent questions. How could so few terrorists create death and destruction on so massive a scale? How could US intelligence services have been caught so off guard? Can technology help prevent such attacks in the future, or at least respond to them more effectively if they do occur? A year after the strikes, answers to these questions are finally starting to take shape. The focus here is on the use of technology as a pillar of future counter-terrorism-from the advanced screening equipment now being installed at airports around the world to the robust emergency communications systems that will link workers and officials after any future calamities. Although the attacks prompted a broad array of technology initiatives, some of the most significant have been in intelligence, airport baggage screening, postal monitoring, biometric identification, radio and television broadcasting, hardened emergency communications, and personal security.