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 management at international airports. The implementation of this method has shown superior performance to previous methods in terms of reducing errors, delays and associated costs
Academic Buoyancy of High School students at the Distinguished Schools
Iodine-doped polythiophene thin films are prepared by aerosol assisted plasma jet polymerization at atmospheric pressure and room temperature. The doping of iodine was carried out in situ by employing iodine crystals in thiophene monomer by weight mixing ratios of 1%, 3%, 5% and 7%. The chemical composition analyses of pure and iodine-doped and heat-treated polythiophene thin films are carried out by FTIR spectroscopy studies. The optical band gaps of the films are evaluated from absorption spectrum studies. Direct transition energy gaps are determined from Tauc plots. The structural changes of polythiophene upon doping and the reduction of optical band gap are explained on the basis of the results obtained from FTIR spectroscopy, UV–V
... Show MoreIn recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and
... Show MoreBegan the process of re-engineering processes in the private sector as a way to assist organizations in re-thinking how to run the business in order to improve production processes and reduce operational cost, to get to compete on a global level. That was a major restructuring by further evolution in the use of technology to support innovative operations.
Entered the technology in all areas of life and different regulations, This led to use as a change in all aspects The companies achieved success and progress today through the use of resources so as to ensure the wishes of the customers and their needs, and the requirements of the market primarily, Which is reflected on the basis of building strate
... Show MoreBlood samples were collected from (31) pregnant women infected with cytomegalovirus , also (15) blood samples were collected from congenitally infected infants, and (20),(15),(15) blood samples were collected from pregnant women ,non pregnant and infants, respectively, all of them were as control groups. CMV infection identified by using ELISA assay to detect specific CMV IgM & IgG in sera. The results of lymphocyte transformation showed a significant decrease when phytoheamagglutinin (PHA) used as stimulator, lymphocytes response in infected pregnant women was lower than that of non infected pregnant women as well as non pregnant women. Result also showed a significant decrease in the ability of lymphocyte division in healthy pregnant w
... Show MoreThe measurement data of the raw water quality of Tigris River were statistically analyzed to measure the salinity value in relation to the selected raw water quality parameters. The analyzed data were collected from five water treatment plants (WTPs) assembled alongside of the Tigris River in Baghdad: Al-Karkh, Al-Karama, Al-Qadisiya, Al-Dora, and Al-Wihda for the period from 2015 to 2021. The selected parameters are total dissolved solid (TDS), electrical conductivity (EC), pH and temperature. The main objective of this research is to predicate a mathematical model using SPSS software to calculate the value of salinity along the river, in addition, the effect of electrical conductivi
As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord
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