Detection of terrorist threats in air passenger luggage: expertise development

Currently, detecting potential threats in air passenger baggage heavily depends on the human examination of X-ray images of individual luggage items. In order to improve the performance of airport security personnel in searching images of air passenger luggage it is important first to understand fully the requirements of the demanding task. Here, an experiment is reported where eye movements of naive observers and screeners were recorded when they searched 30 X-ray images of air passenger luggage for potential terrorist threat items such as guns, knives and improvised explosive devices. Compared with novices, the advantages of the screeners were speed and accuracy in detecting threats. Eye position data revealed that screeners were faster to fixate on target areas and once they fixated on targets their hit rate was significantly higher. Most of the IEDs were missed by both naive observers and screeners due to interpretation errors which indicated the importance of training. Stimulus salience at the first fixation locations of naive observers and screeners was compared to investigate expertise development. It was found that experience did not change attention preference on stimuli properties at the beginning of the observers visual search. The implications and further studies are discussed

Detection of terrorist threats in air passenger luggage: expertise development

Currently, detecting potential threats in air passenger baggage heavily depends on the human examination of X-ray images of individual luggage items. In order to improve the performance of airport security personnel in searching images of air passenger luggage it is important first to understand fully the requirements of the demanding task. Here, an experiment is reported where eye movements of naive observers and screeners were recorded when they searched 30 X-ray images of air passenger luggage for potential terrorist threat items such as guns, knives and improvised explosive devices. Compared with novices, the advantages of the screeners were speed and accuracy in detecting threats. Eye position data revealed that screeners were faster to fixate on target areas and once they fixated on targets their hit rate was significantly higher. Most of the lEDs were missed by both naive observers and screeners due to interpretation errors which indicated the importance of training. Stimulus salience at the first fixation locations of naive observers and screeners was compared to investigate expertise development. It was found that experience did not change attention preference on stimuli properties at the beginning of the observers visual search. The implications and further studies are discussed

Is that a gun? The influence and features of bags and threat items on detection performance

An experiment is reported where naïve observers searched 50 X-ray images of air passenger luggage for potential terrorist threat items. For each image their eye movements were recorded remotely and they had to rate their confidence in whether or not a potential threat item was present. The images were separately rated by other naïve observers in terms of; visual complexity of bags, the familiarity and visual conspicuity of threat items. The visual angle subtended by guns and the familiarity of threat items influenced the detection rate. Eye movement data revealed that the complexity of bags and the conspicuity of threat items also influenced visual search and attention

Detection of Terrorist Threats in Air Passenger Luggage: Expertise Development

Currently, detecting potential threats in air passenger baggage heavily depends on the human examination of X-ray images of individual luggage items. In order to improve the performance of airport security personnel in searching images of air passenger luggage it is important first to understand fully the requirements of the demanding task. Here, an experiment is reported where eye movements of naive observers and screeners were recorded when they searched 30 X-ray images of air passenger luggage for potential terrorist threat items such as guns, knives and improvised explosive devices. Compared with novices, the advantages of the screeners were speed and accuracy in detecting threats. Eye position data revealed that screeners were faster to fixate on target areas and once they fixated on targets their hit rate was significantly higher. Most of the IEDs were missed by both naive observers and screeners due to interpretation errors which indicated the importance of training. Stimulus salience at the first fixation locations of naive observers and screeners was compared to investigate expertise development. It was found that experience did not change attention preference on stimuli properties at the beginning of the observers visual search. The implications and further studies are discussed

The rates for the MIMO channel, with <i>T</i> = 4, <i>M</i> = 4, <i>P</i> = 10, <i>σ</i>² = 1, <i>ϵ</i> = 10⁻⁶.

The rates for the MIMO channel, with T = 4, M = 4, P = 10, σ2 = 1, ϵ = 10−6.</p

The rates for the MISO channel, with <i>T</i> = 4, <i>P</i> = 10, <i>σ</i>² = 1, <i>ϵ</i> = 10⁻⁶.

The rates for the MISO channel, with T = 4, P = 10, σ2 = 1, ϵ = 10−6.</p

The rates for the SISO channel, with <i>P</i> = 10, <i>σ</i>² = 1, <i>ϵ</i> = 10⁻⁶.

The rates for the SISO channel, with P = 10, σ2 = 1, ϵ = 10−6.</p

Total accuracy of predictions.

<p>Motifs are discovered by the five methods on flat and hierarchical (tree) structure respectively.</p

Notations.

Ultra-reliable low-latency communication (URLLC) is a key technology in future wireless communications, and finite blocklength (FBL) coding is the core of the URLLC. In this paper, FBL coding schemes for the wireless multi-antenna channels are proposed, which are based on the classical Schalkwijk-Kailath scheme for the point-to-point additive white Gaussian noise channel with noiseless feedback. Simulation examples show that the proposed feedback-based schemes almost approach the corresponding channel capacities.</div

Discriminative Motif Discovery via Simulated Evolution and Random Under-Sampling

<div><p>Conserved motifs in biological sequences are closely related to their structure and functions. Recently, discriminative motif discovery methods have attracted more and more attention. However, little attention has been devoted to the data imbalance problem, which is one of the main reasons affecting the performance of the discriminative models. In this article, a simulated evolution method is applied to solve the multi-class imbalance problem at the stage of data preprocessing, and at the stage of Hidden Markov Models (HMMs) training, a random under-sampling method is introduced for the imbalance between the positive and negative datasets. It is shown that, in the task of discovering targeting motifs of nine subcellular compartments, the motifs found by our method are more conserved than the methods without considering data imbalance problem and recover the most known targeting motifs from Minimotif Miner and InterPro. Meanwhile, we use the found motifs to predict protein subcellular localization and achieve higher prediction precision and recall for the minority classes.</p></div