A Step toward Ending Long Airport Security Lines: The Modified Boarding Pass

Anyone who has traveled by air has most likely experienced long airport security lines. Yet not much is known about its cause because few have considered if passengers have created this problem for themselves. The present study attempts to fill this research gap by suggesting that when passengers are not well-prepared for security screening, they delay the process by making mistakes and not complying with procedures. This lack of preparedness can be attributed to several shortcomings of security signposts. This study proposes the use of a modified boarding pass as an alternative form of signage to help passengers better prepare for security screening. In a recall evaluation of the items to remove prior to security screening, the combination of the modified boarding pass and security signposts led to greater recall than when either stimuli were used alone. In an airport survey to gather public sentiment, three-quarters of the respondents saw value in the idea of the modified boarding pass. Although the majority of the respondents were receptive to it becoming an option for future travel, many also felt that the modified boarding pass would be more useful than security signposts or announcements at conveying helpful security screening information

Microwave imaging for security applications

Microwave imaging technologies have been widely researched in the biomedical field where they rely on the imaging of dielectric properties of tissues. Healthy and malignant tissue have different dielectric properties in the microwave frequency region, therefore, the dielectric properties of a human body’s tissues are generally different from other contraband materials. Consequently, dielectric data analysis techniques using microwave signals can be used to distinguish between different types of materials that could be hidden in the human body, such as explosives or drugs. Other concerns raised about these particular imaging systems were how to build them cost effectively, with less radiation emissions, and to overcome the disadvantages of X-ray imaging systems. The key challenge in security applications using microwave imaging is the image reconstruction methods adopted in order to gain a clear image of illuminated objects inside the human body or underneath clothing. This thesis will discuss in detail how microwave tomography scanning could overcome the challenge of imaging objects concealed in the human body, and prove the concept of imaging inside a human body using image reconstruction algorithms such as Radon transformation image reconstruction. Also, this thesis presents subspace based TR-MUSIC algorithms for point targets and extended targets. The algorithm is based on the collection of the dominant response matrix reflected by targets at the transducers in homogenous backgrounds, and uses the MUSIC function to image it. Lumerical FDTD solution is used to model the transducers and the objects to process its response matrix data in Matlab. Clear images of metal dielectric properties have been clearly detected. Security management understanding in airports is also discussed to use new scanning technologies such as microwave imaging in the future.The main contribution of this reseach is that microwave was proved to be able to image and detect illegal objects embedded or implanted inside human body

Human factors in X-ray image inspection of passenger Baggage – Basic and applied perspectives

The X-ray image inspection of passenger baggage contributes substantially to aviation security and is best understood as a search and decision task: Trained security officers – so called screeners – search the images for threats among many harmless everyday objects, but the recognition of objects in X-ray images and therefore the decision between threats and harmless objects can be difficult. Because performance in this task depends on often difficult recognition, it is not clear to what extent basic research on visual search can be generalized to X-ray image inspection. Manuscript 1 of this thesis investigated whether X-ray image inspection and a traditional visual search task depend on the same visual-cognitive abilities. The results indicate that traditional visual search tasks and X-ray image inspection depend on different aspects of common visual-cognitive abilities. Another gap between basic research on visual search and applied research on X-ray image inspection is that the former is typically conducted with students and the latter with professional screeners. Therefore, these two populations were compared, revealing that professionals performed better in X-ray image inspection, but not the visual search task. However, there was no difference between students and professionals regarding the importance of the visual-cognitive abilities for either task. Because there is some freedom in the decision whether a suspicious object should be declared as a threat or as harmless, the results of X-ray image inspection in terms of hit and false alarm rate depend on the screeners’ response tendency. Manuscript 2 evaluated whether three commonly used detection measures – ${d}'$, ${A}'$, and ${d}_{a}$ – are a valid representation of detection performance that is independent from response tendency. The results were consistently in favor of da with a slope parameter of around 0.6. In Manuscript 3 it was further shown that screeners can change their response tendency to increase the detection of novel threats. Also, screeners with a high ability to recognize everyday objects detected more novel threats when their response tendency was manipulated. The thesis further addressed changes that screeners face due to technological developments. Manuscript 4 showed that screeners can inspect X-ray images for one hour straight without a decrease in performance under conditions of remote cabin baggage screening, which means that X-ray image inspection is performed in a quiet room remote from the checkpoint. These screeners did not show a lower performance, but reported more distress, compared to screeners who took a 10 min break after every 20 min of screening. Manuscript 5 evaluated detection systems for cabin baggage screening (EDSCB). EDSCB only increased the detection of improvised explosive devices (IEDs) for inexperienced screeners if alarms by the EDSCB were indicated on the image and the screeners had to decide whether a threat was present or not. The detection of mere explosives, which lack the triggering device of IEDs, was only increased if the screeners could not decide against an alarm by the EDSCB. Manuscript 6 used discrete event simulation to evaluate how EDSCB impacts the throughput of passenger baggage screening. Throughput decreased with increasing false alarm rate of the EDSCB. However, fast alarm resolution processes and screeners with a low false alarm rate increased throughput. Taken together, the present findings contribute to understanding X-ray image inspection as a task with a search and decision component. The findings provide insights into basic aspects like the required visual-cognitive abilities and valid measures of detection performance, but also into applied research questions like for how long X-ray image inspection can be performed and how automation can assist with the detection of explosives

Novel multi-objective affinity approach allows to identify pH-specific μ-opioid receptor agonists

Opioids are essential pharmaceuticals due to their analgesic properties, however, lethal side effects, addiction, and opioid tolerance are extremely challenging. The development of novel molecules targeting the -opioid receptor (MOR) in inflamed, but not in healthy tissue, could significantly reduce these unwanted effects. Finding such novel molecules can be achieved by maximizing the binding affinity to the MOR at acidic pH while minimizing it at neutral pH, thus combining two conflicting objectives. Here, this multi-objective optimal affinity approach is presented, together with a virtual drug discovery pipeline for its practical implementation. When applied to finding pH-specific drug candidates, it combines protonation state-dependent structure and ligand preparation with high-throughput virtual screening. We employ this pipeline to characterize a set of MOR agonists identifying a morphine-like opioid derivative with higher predicted binding affinities to the MOR at low pH compared to neutral pH. Our results also confirm existing experimental evidence that NFEPP, a previously described fentanyl derivative with reduced side effects, and recently reported -fluorofentanyls and -morphines show an increased specificity for the MOR at acidic pH when compared to fentanyl and morphine. We further applied our approach to screen a >50K ligand library identifying novel molecules with pH-specific predicted binding affinities to the MOR. The presented differential docking pipeline can be applied to perform multi-objective affinity optimization to identify safer and more specific drug candidates at large scale

Towards Real-Time Anomaly Detection within X-ray Security Imagery: Self-Supervised Adversarial Training Approach

Automatic threat detection is an increasingly important area in X-ray security imaging since it is critical to aid screening operators to identify concealed threats. Due to the cluttered and occluded nature of X-ray baggage imagery and limited dataset availability, few studies in the literature have systematically evaluated the automated X-ray security screening. This thesis provides an exhaustive evaluation of the use of deep Convolutional Neural Networks (CNN) for the image classification and detection problems posed within the field. The use of transfer learning overcomes the limited availability of the object of interest data examples. A thorough evaluation reveals the superiority of the CNN features over conventional hand-crafted features. Further experimentation also demonstrates the capability of the supervised deep object detection techniques as object localization strategies within cluttered X-ray security imagery. By addressing the limitations of the current X-ray datasets such as annotation and class-imbalance, the thesis subsequently transitions the scope to- wards deep unsupervised techniques for the detection of anomalies based on the training on normal (benign) X-ray samples only. The proposed anomaly detection models within the thesis employ a conditional encoder-decoder generative adversarial network that jointly learns the generation of high-dimensional image space and the inference of latent space — minimizing the distance between these images and the latent vectors during training aids in learning the data distribution for the normal samples. As a result, a larger distance metric from this learned data distribution at inference time is indicative of an outlier from that distribution — an anomaly. Experimentation over several benchmark datasets, from varying domains, shows the model efficacy and superiority over previous state-of-the-art approaches. Based on the current approaches and open problems in deep learning, the thesis finally provides discussion and future directions for X-ray security imagery

Performance and Evaluation in Computed Tomographic Colonography Screening for Colorectal Cancer

Each year over 20,000 people die from colorectal cancer (CRC). However, despite causing the second highest number of cancer deaths, CRC is not only curable if detected early but can be prevented by population screening. The detection and removal of pre-malignant polyps in the colon prevents cancer from ever developing. As such, screening of the at-risk population (those over 45-50 years) confers protection against CRC incidence and mortality. Although the principles and benefit of screening are well established, the adequate provision of screening is a complex process requiring robust healthcare infrastructure, evidence-based quality assurance and resources. The success of any screening programme is dependent on the accuracy of the screening investigations deployed and sufficiently high uptake by the target population. In England, the Bowel Cancer Screening Programme (BCSP) delivers screening via initial stool testing to triage patients for the endoscopic procedure, colonoscopy, or the radiological investigation CT colonography (CTC) in some patients. There has been considerable investment in colonoscopy accreditation processes which contribute to high quality services, suitable access for patients and a competent endoscopy workforce. The performance of colonoscopists in the BCSP is tightly monitored and regulated; however, the same is not true for CTC. Comparatively, there has been little investment in CTC services, and in fact there is no mandatory accreditation or centralised training. Instead, CTC reporting radiologists must learn ad hoc on the job, or at self-funded commercial workshops. This inevitably leads to variability in quality and expertise, inequity in service provision, and could negatively impact patient outcomes. To address this disparity and develop evidence-based training, one must determine what factors affect the performance of CTC reporting radiologists, what CTC training is necessary, and what training works. This thesis investigates these topics and is structured as follows: Section A reviews the background literature, describing the public health burden of CRC and the role of screening. Aspects of CTC screening and its role in the BCSP are explored. The importance of performance monitoring and value of accreditation are examined and the disparity between CTC, colonoscopy and other imaging-based screening programmes is discussed. Section B expands on radiologist performance by determining the post-imaging CRC (or interval cancer) rate through systematic review and meta-analysis. Factors contributing to the interval cancer rate are evaluated, and an observational study assessing factors affecting CTC accuracy is presented. The impact of CTC training is assessed via a structured review and best principles for training delivery are discussed. Section C presents a multicentre, cluster-randomised control trial developed from the data and understanding described in Sections A and B. Section D summarises the thesis and discusses future recommendations and research

Airport code/spaces

Nearly all aspects of passenger air travel from booking a ticket to checking-in, passing through security screening, buying goods in duty free, baggage-handling, flying, air traffic control, customs and immigration checks are now mediated by software and multiple information systems. Airports, as we have previously argued (Dodge and Kitchin 2004), presently consist of complex, over-lapping assemblages to varying degrees dependent on a myriad of software systems to function, designed to smooth and increase passenger flows through various ‘contact’ points in the airport (as illustrated in Figure 1) and to enable pervasive surveillance to monitor potential security threats. Airport spaces – the check-in areas, security check-points, shopping areas, departure lounges, baggage reclaim, the immigration hall, air traffic control room, even the plane itself - constitute coded space or code/space. Coded space is a space that uses software in its production, but where code is not essential to its production (code simply makes the production more efficient or productive). Code/space, in contrast, is a space dependent on software for its production – without code that space will not function as intended, with processes failing as there are no manual alternatives (or the legacy ‘fall-back’ procedures are unable to handle material flows which means the process then fails due to congestion). Air travel increasingly consists of transit through code/spaces, wherein if the code ‘fails’ passage is halted. For example, if the check-in computers crash there is no other way of checking passengers in; manual check-in has been discontinued, in part, due to new security procedures. Check-in areas then are dependent on code to operate and without it they are simply waiting rooms with no hope of onward passage until the problem is resolved. In these cases, a dyadic relationship exists between software and space (hence the slash conjoining code/space) so that spatiality is the product of code, and code exists in order to produce spatiality

A Randomized Waitlist-controlled Trial of Voice Over Internet Protocol-delivered Behavior Therapy for Chronic Tic Disorders

Videoconferencing is efficacious, acceptable and equivalent to face to face for a range of psychotherapies, including a Comprehensive Behavioral Interventions for Tics (CBIT), but limited due to lack of portability, and restricted accessibility. An alternative is Voice over Internet Protocol (VoIP) transmission, allowing home delivery of treatment. The present study examined the preliminary efficacy, feasibility, and acceptability of CBIT-VoIP. Twenty youth (8-17) with CTDs participated in a randomized, waitlist-controlled trial of CBIT. Assessments were conducted via VoIP and internet surveys. Significantly greater reductions in total clinician-rated and parent-reported tic severity were found in the CBIT relative to the waitlist-control group, with 33.3% of those in CBIT considered treatment responders. Treatment satisfaction and the therapeutic alliance were high. Higher parent satisfaction with videoconferencing was associated with higher decreases in clinician-rated tic severity. Positive relationships were found between child computer usage at baseline and satisfaction with videoconferencing at post-assessment. VoIP was generally feasible, with some challenges due to audio and visual disruptions

From Multiple Scale Modeling to Multiscale-Modeling

To power a sustainable future, interest in battery research and technology is at an all time high. In order to enable a transition to green tech many applications, such as the automotive industry, is in need of higher power densities, energy densities, longer life-times, and safer batteries.\\One crucial component of batteries is the electrolyte, which for lithium-ion batteries (LIBs) have not developed as much as one would expect since its introduction in the 1990s. Through the use of novel electrolyte concepts such as highly concentrated electrolytes (HCE) and localized highly concentrated electrolytes (LHCE) desired qualities such as an increased energy density could be achieved. The effects of local properties on macroscopic behaviour within these systems are much more striking than conventional LIB electrolytes, constraining the use of common simulation techniques used in battery research.This thesis studies these novel electrolyte concepts using an array of different computational methods, such as DFT, AIMD, and classical MD. Based on these techniques, as well as on the CHAMPION method, the work done in this thesis attempts to develop a method for tying together understanding of materials physics at the different scales represented by AIMD and classical MD through force sampling. This force sampling is presented as an alternative to commonplace MD force fields such as AMBER, CHARMM and GROMACS. Finding the local structure important for explaining global transport phenomenon by showing that local HCE structure is retained when going from HCE to LHCE as well as showing the possibility for these new types of FFs, even though more work is needed on the accuracy of these FFs