The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

Abstract

This research aims to identify the challenges faced by families of children with intellectual disabilities and to identify the impact of the challenges facing them on the mental health of their children with intellectual disabilities. Based on the following questions: What is the nature of the challenges faced by families of children with disabilities and how do these challenges affect the mental health of their children with intellectual disabilities? The study was conducted on a sample of four families of six children with intellectual disabilities, depending on the degree and type of disability. To achieve the study's objectives, the qualitative approach was used, Because of the importance of accessin

  This work discusses the beginning of fractional calculus and how the Sumudu and Elzaki transforms are applied to fractional derivatives. This approach combines a double Sumudu-Elzaki transform strategy to discover analytic solutions to space-time fractional partial differential equations in Mittag-Leffler functions subject to initial and boundary conditions. Where this method gets closer and closer to the correct answer, and the technique's efficacy is demonstrated using numerical examples performed with Matlab R2015a.