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

One of the important units in Sharq Dijla Water Treatment Plant (WTP) first and second extensions are the alum solution preparation and dosing unit. The existing operation of this unit accomplished manually starting from unloading the powder alum in the preparation basin and ending by controlling the alum dosage addition through the dosing pumps to the flash mix chambers. Because of the modern trend of monitoring and control the automatic operation of WTPs due to the great benefits that could be gain from optimum equipment operation, reducing the operating costs and human errors. This study deals with how to transform the conventional operation to an automatic monitoring and controlling system depending on a Programmable

The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

  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.

In recent years, various methods have been developed to enhance the characteristics of asphalt pavement in order to face the continuous challenges of increasing traffic loads and changing climate conditions. One of the most popular and successful methods is modifying the asphalt mixtures or asphalt binder with the addition of polymers. Therefore, two types of Polyethylene (PE) polymer, High-Density PE (HDPE) and Low-Density PE (LDPE), are used in this research. Two methods were applied to prepare PE-modified asphalt mixtures: Semi-Wet Method (S-WM) and Dry Method (DM). The findings of the investigation indicated that the addition of PE polymer can reduce the wear loss of aggregate. In general, the experimental results revealed that asphalt

A pulsed (TEA-0O2) laser was used to dissociate molecules of silane ethylene (C2I-14) and ammonia (NH3) gases, through collision assisted multiple photon dissociation (MPD) to deposit(SiC i_xNx) thin films, where the X-values are 0, 0.13 and 0.33, on glass substrate at T,----648 K. deposition rate of (0.416-0.833) nm/pulse and thickness of (500-1000)nm .Fourier transform infrared spectrometry (FT-IR) was used to study the nature of the chemical bonds that exist in the films. Results revealed that these films contain complex networks of the atomic (Si, C, and N), other a quantity of atomic hydrogen and chemical bonds such as (Si-N, C-N, C-14 and N-H).Absorbance and Transmittance spectra in the wavelength range (400-1100) nm were used to stud