Designing and Evaluating an Avatar for On-Person Screening

In aviation security, avatars are generic human figures that are used to display alarms provided by on-person screening systems. One critical feature of these avatars is that they provide no body detail unique to an individual traveler. However, the generic nature of these avatars leaves few landmarks that can be used to map the location of an alarm on the avatar to a passenger. We manipulated two features of an avatar, body detail and grid lines, to create 6 avatars to investigate how design influences estimation of target location. Body detail was manipulated at three levels: no joints, some joints, and direct outline of the passenger. Grid lines were manipulated at two levels: grid lines or no grid lines. The results of the study showed that security screeners were nearly 20% closer to the true target location when the avatar featured landmarks that can be found on a typical passenger.

Calculation of deception probability of netted radar based on non-central chi-square distribution

Aiming at the problems of complex factors affecting the rate of deception probability of networked of radar nets, the large amount of calculation by Monte Carlo simulation and the inability to quantitatively analyze the influence of various factors on the deception probability of networked, a calculation method of deception probability of networked is proposed. First, according to the homology measurement method based on the Mahalanobis distance, the probability density model of the deception probability of networked is calculated. Its probability density model obeys the non-central chi-square distribution. Then, a hypothesis test model is established to calculate the deception probability of networked mathematical expression. The simulation results show that the error between the calculation method of the deception probability of networked and the calculation result of 1000 times Monte Carlo is less than 2%. The method in this article can analyze the quantitative effect of false target position, interference distance interval, radar position, true target position, and other factors on the deception probability of networked, instead of Monte Carlo simulation, to provide a trade-off between the true target recognition rate and the deception probability of networked theoretical basis.

Conflict Management for Target Recognition Based on PPT Entropy and Entropy Distance

Conflicting evidence affects the final target recognition results. Thus, managing conflicting evidence efficiently can help to improve the belief degree of the true target. In current research, the existing approaches based on belief entropy use belief entropy itself to measure evidence conflict. However, it is not convincing to characterize the evidence conflict only through belief entropy itself. To solve this problem, we comprehensively consider the influences of the belief entropy itself and mutual belief entropy on conflict measurement, and propose a novel approach based on an improved belief entropy and entropy distance. The improved belief entropy based on pignistic probability transformation function is named pignistic probability transformation (PPT) entropy that measures the conflict between evidences from the perspective of self-belief entropy. Compared with the state-of-the-art belief entropy, it can measure the uncertainty of evidence more accurately, and make full use of the intersection information of evidence to estimate the degree of evidence conflict more reasonably. Entropy distance is a new distance measurement method and is used to measure the conflict between evidences from the perspective of mutual belief entropy. Two measures are mutually complementary in a sense. The results of numerical examples and target recognition applications demonstrate that our proposed approach has a faster convergence speed, and a higher belief degree of the true target compared with the existing methods.

Performance of Logistic Regression, Propensity Scores, and Instrumental Variable for Estimating Their True Target Odds Ratios in the Absence and Presence of Unmeasured Confounder

Background: A lot of studies have compared the ability of statistical methods to control for confounding. However, a majority of studies mistakenly assumed these methods estimate the same effect. The aim of this study was to use Monte Carlo simulations to compare logistic regression, propensity scores and instrumental variable analysis for estimating their true target odds ratios in terms of bias and precision in the absence and presence of unmeasured confounder. Methods: We established the formula allowing us to compute the true odds ratio of each method. We varied the instrument’s strength and the unmeasured confounder to cover a large range of scenarios in the simulation study. We then use logistic regression, propensity score matching, propensity score adjustment and two-stage residual inclusion to obtain estimated odds ratios in each scenario. Results: In the absence of unmeasured confounder, instrumental variable without direct effect on the outcome could produce unbiased estimates as propensity score did, but the mean square errors of instrumental variable were greater. When unmeasured confounder existed, no other method could produce unbiased estimation except instrumental variable, provided that the proposed instrument is not directly related to the outcome. Using the defined instrument, which affected the outcome directly, resulted in positive biased estimation of the treatment effect and this bias was greater compared to that from other methods. Conclusions: Overall, with good implementation, instrumental variable can lead to unbiased results. However, the bias caused by violating the required assumptions of instrumental variable can overweigh the positive effect of its ability to control for unmeasured confounder.

A Dual Quaternion Based Method for Estimating Margins for Planning Target Volumes in Radiotherapy

This objective of this paper is to develop a dual quaternion based method for estimating target volumes in radiation therapy for head and neck cancer. Inaccuracies in radiation targeting are responsible for incidental exposure of healthy adjacent tissues, causing significant morbidity and mortality. This paper focuses on inaccuracies incurred when a tumor is displaced during treatment. To address this problem, the clinical target must be expanded to cover the region through which the tumor might move. The resulting expanded target is known as the Planning Target Volume (PTV). In the current practice, the rotational components of displacements are neglected, producing planning target volumes that either miss the true target motion or are larger than needed to cover the target path. By using the dual quaternion based kinematic formulation, this paper represents and captures both translational and rotational inaccuracies. It then presents a framework for calculating the PTV swept out by the target as it shifts within its range of translations and rotations.

Product Lineups: The More You Search, The Less You Find

Consumers often try to visually identify a previously encountered product among a sequence of similar items, guided only by their memory and a few general search terms. What determines their success at correctly identifying the target product in such “product lineups”? The current research finds that the longer consumers search sequentially, the more conservative and—ironically—inaccurate judges they become. Consequently, the more consumers search, the more likely they are to erroneously reject the correct target when it finally appears in the lineup. This happens because each time consumers evaluate a similar item in the lineup, and determine that it is not the option for which they have been looking, they draw an implicit inference that the correct target should feel more familiar than the similar items rejected up to that point. This causes the subjective feeling of familiarity consumers expect to experience with the true target to progressively escalate, making them more conservative but also less accurate judges. The findings have practical implications for consumers and marketers, and make theoretical contributions to research on inference-making, online search, and product recognition.

On the Expansion of a Class of Open-Loop Evasion Control in the Simplest Two-Criteria Pursuit-Evasion Game of Two Purposes

The article is devoted to the formulation and solution of the two-criterion pursuit-evasion game on the plane of one pursuer against two targets, one of which is false. A false target is used to distract the pursuer, allowing the true target (in the process of diverting) to maximize the minimum possible distance to the pursuer. The specificity of the pursuer is that it has a circular classification zone of radius R, within which it has the ability to instantly classify the target as false or true. The game is that the pursuer minimizes the time required to approach one of the targets to a distance not exceeding R (R-encounter), and the targets, acting in concert, maximize the minimum distance between the pursuer and the remaining target. The game continues until the R-meeting of the pursuer with the first (false) target, i.e. until the classification of the false target. It is assumed that the first target is false a priori the persecutor is not known. The strategy of using a false target is precisely to release it to distract the pursuer from the true target. In reality, the false target is a mobile drone, which is controlled programmatically by the on-Board computer. In the class of open-loop controls the staging was investigated in 1984 by Ivanov M. N. and Maslov E. P. There is a natural question: what will give an extension of a class of open-loop controls of the false targets to the class of closed-loop controls, i.e. to the class of controls with a feedback? This question is quite appropriate in connection with the great progress in the development of microprocessor technology and improving the performance of on-Board computers, which makes it possible to use more complex algorithms for controlling Autonomous mobile objects. This article gives a negative answer to the above question, namely, it is shown that the extension of the class of open-loop controls by a false target does not improve the quality of control. It is proved that in this game there is a Nash equilibrium in the program strategies of the players.