Two-stage security screening strategies in the face of strategic applicants, congestions and screening errors

2015 ◽  
Vol 258 (2) ◽  
pp. 237-262 ◽  
Author(s):  
Cen Song ◽  
Jun Zhuang
Keyword(s):  
Two Stage ◽  
Security Screening ◽  
Screening Strategies ◽  
The Face ◽  
Screening Errors

Two-Stage Precession Type Gear: Design, Geometric and Kinematic Analysis

2017 ◽  
Author(s):  
Łukasz Macyszyn ◽  
Adam Myszkowski ◽  
Roman Staniek ◽  
Stanisław Pabiszczak
Keyword(s):  
Gear Ratio ◽  
Original Method ◽  
Two Stage ◽  
Precession Angle ◽  
Gear Design ◽  
The Face ◽  
Gear Efficiency ◽  
Rotary Speed ◽  
Gear Wheels ◽  
Neodymium Magnets

The paper presents the theoretical bases, design and the principle of operation of two-stage precession type transmission with face meshing. Description and the principle of forming the face meshing which is modified by the original method have been shown as well. Dimensional relations between particular components of the gears are established and the analysis of optimal gear ratio, depending on the number of teeth or magnets on the circumferences of meshing gear wheels is also provided in the paper. For further analysis four prototypes of mechanical precession transmission with face meshing were designed, built and investigated. Those prototypes present different sizes, reduction ratio and precession angle. Investigations, described in the paper, helped to determine the gear efficiency rate as well as the maximal torque that could be transferred for the given rotary speed. This paper presents also the conception of the design of a novel double stage precession magnetic gear with face neodymium magnets. The results of the initial studies are the background of the further research in the field of magnetic precession type transmission.

Dynamic Simulation and Optimization of Two-Stage Extractive Alcoholic Fermentation Process: Design Impact on Controllability

2006 ◽  
Vol 1 (1) ◽  
Author(s):  
Jobrun Nandong ◽  
Yudi Samyudia ◽  
Moses O Tadé
Keyword(s):  
Fermentation Process ◽  
Dynamic Performance ◽  
Operating Conditions ◽  
Single Stage ◽  
Extractive Fermentation ◽  
Two Stage ◽  
Stage Design ◽  
Simulation And Optimization ◽  
The Face ◽  
Two Stage Design

In this paper, we address dynamic controllability of the two different designs of extractive fermentation process, namely one-stage and two-stage designs. The operating conditions that maximize yields and productivity for both designs are determined by optimization using the method of factorial design and response surface analysis. The results show that in terms of the achievable yield and productivity, the performance of the two-stage design is comparable to that of the single-stage, but the former design leads to a significant reduction in the fermentor size required. Furthermore, we analyze the dynamic controllability of the two designs of extractive fermentation process using a so-called control relevant metrics to examine their closed-loop dynamic performance in the face of uncertainty. This analysis reveals that the single-stage design has more favorable dynamic controllability than the two-stage design.

scholarly journals A Web-Based Knowledge Elicitation System (GISEL) for Planning and Assessing Group Screening Experiments for Product Development

2004 ◽  
Vol 4 (3) ◽  
pp. 218-225 ◽  
Author(s):  
David P. Dupplaw ◽  
David Brunson ◽  
Anna-Jane E. Vine ◽  
Colin P. Please ◽  
Susan M. Lewis ◽  
...  
Keyword(s):  
Probability Distributions ◽  
Screening Method ◽  
Two Stage ◽  
Web Based ◽  
Expert Opinions ◽  
Screening Experiments ◽  
Number Of Factors ◽  
Screening Strategies ◽  
Main Effects ◽  
Complete Investigation

When planning experiments to examine how product performance depends on the design, manufacture and environment of use, there are invariably too few resources to enable a complete investigation of all possible variables (factors). We have developed new algorithms for generating and assessing efficient two-stage group screening strategies which are implemented through a web-based system called GISEL. This system elicits company knowledge which is used to guide the formulation of competing two-stage strategies and, via the algorithms, to provide quantitative assessment of their efficiencies. The two-stage group screening method investigates the effect of a large number of factors by grouping them in a first stage experiment whose results identify factors to be further investigated in a second stage. Central to the success of the procedure is ensuring that the factors considered, and their grouping, are based on the best available knowledge of the product. The web-based software system allows information and ideas to be contributed by engineers at different sites and allows the experiment organizer to use these expert opinions to guide decisions on the planning of group screening experiments. The new group screening algorithms implemented within the software give probability distributions and indications of the total resource needed for the experiment. In addition, the algorithms simulate results from the experiment and estimate the percentage of important or active main effects and interactions that fail to be detected. The approach is illustrated through the planning of an experiment on engine cold start optimization at Jaguar Cars.

scholarly journals Two-stage surgery for the treatment of nonmelanoma skin cancer of the face: change of surgical strategy during COVID-19 pandemic

Oral Oncology ◽  
2021 ◽  
pp. 105622
Author(s):  
Giulio Pagliuca ◽  
Valentina Terenzi ◽  
Salvatore Martellucci ◽  
Veronica Clemenzi ◽  
Andrea Stolfa ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Nonmelanoma Skin Cancer ◽  
Surgical Strategy ◽  
Two Stage ◽  
The Face

scholarly journals Efficient Two Stage Identification for Face mask detection using Multiclass Deep Learning Approach

2021 ◽  
Vol 3 (2) ◽  
pp. 107-121
Author(s):  
R Dhaya
Keyword(s):  
Deep Learning ◽  
Binary Classification ◽  
Face Mask ◽  
World Health ◽  
Survey Study ◽  
Identification System ◽  
Two Stage ◽  
Public Places ◽  
The World ◽  
The Face

The World Health Organization (WHO) considers the COVID-19 Coronavirus to be a global pandemic. The most effective form of protection is to wear a face mask in public places. Moreover, the COVID-19 pandemic prompted all the countries to set up a lockdown to prevent viral transmission. According to a survey study, the use of facemasks at work decreases the chances of fast transmission. If the facemasks are not used or are worn incorrectly, it contributes to the third and fourth waves of the corona virus spreading throughout the world. This motivates us to conduct an efficient investigation of the face mask identification system and monitor people, who use suitable face mask in public places. Deep learning is the most effective approach for detecting whether or not a person is wearing a face mask in a crowded area. Using a multiclass deep learning technique, this research study proposes an efficient two stage identification (ETSI) for face mask detection. Whereas, the binary classification does not offer information about face mask detection and error. The proposed approach employs CNN's "ReLU" activation function to detect the face mask. Furthermore, in the current pandemic crisis, this research article offers a very efficient and precise approach for identifying COVID-19. Precision has increased as a result of the employment of a multi-class abbreviation in the final output.

Designing Optimal Aviation Baggage Screening Strategies Using Evolutionary Algorithms

2013 ◽  
Vol 4 (1) ◽  
pp. 1-16
Author(s):  
Anuar Aguirre ◽  
Jose F. Espiritu ◽  
Salvador Hernández
Keyword(s):  
Evolutionary Algorithms ◽  
Optimization Problems ◽  
Aviation Security ◽  
Screening Strategy ◽  
Hierarchical Level ◽  
False Alarms ◽  
Mathematical Methods ◽  
Security Screening ◽  
Screening Strategies ◽  
Baggage Screening

Various mathematical methods and metaheuristic approaches have been developed in the past to address optimization problems related to aviation security. One such problem deals with a key component of an aviation security system, baggage and passenger screening devices. The decision process to determine which devices to procure by aviation and security officials, and how and where to deploy them can be quite challenging. In this study, two evolutionary algorithms are developed to obtain optimal baggage screening strategies, which minimize the expected annual total cost. Here, the expected annual cost function is composed of the purchasing and operating costs, as well as the costs associated to false alarms and false clears. A baggage screening strategy consists of various hierarchical levels of security screening devices through which a checked bag may pass through. A solution to the aviation baggage screening problem entails the number and type of devices to be installed at each hierarchical level. Solutions obtained from a comparison of a Genetic and a Memetic algorithm are presented. In addition, to illustrate the performance of both algorithms, different computational experiments utilizing the developed algorithms are also presented.

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