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

This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

P. aeruginosa is one of the complex targets for antimicrobial chemotherapy. Also, it is intrinsically resistant to several antibiotics. It produces β-lactamases enzymes that are responsible for the widespread β-lactam antimicrobial resistance. There are three major groups of β-lactamase enzymes, MBLs and ESBLs forming Pseudomonas is a major issue for the treatment of burns victims. Methods: A total of 28 clinical isolates related to P. aeruginosa have been obtained from the burns specimens from patients attending to AL-Imam hospital/Baghdad-Iraq, through the period from October 2015 to March 2016. Also, all isolates have been recognized as P. aeruginosa via utilizing bacteriological assay and confirmed by Vitek 2. In addition, the suscep

Background: Non-small cell lung cancer (NSCLC) is caused of 85% of all lung cancers. Among the most important factors for lung tumor growth and proliferation are the tyrosine kinase receptors that coded by the epidermal growth factor recep-tor (EGFR) gene. Activation of EGFR ultimately leads to developing of lung cancer. The present study was undertaken with an objective to detect EGFR mutations in bronchial wash from Iraqi patients with NSCLC before treatment. Methods: DNA was extracted from bronchial wash samples collected from 50 patients with NSCLC by using a Qiamp DNA Mini Kit (Qiagen, Hilden, Germany). Then, EGFR mutations were determined by using real-time RCR combined with two technologies, Amplification Refractory Mutation System (

The target of this study was to study the natural phytochemical components of the head (capsule) of Cynara scolymus cultivated in Iraq. The head (capsule) of plant was extracted by maceration in70% ethanol for 72 hours, and fractioned by hexane, chloroform and ethyl acetate. Preliminary qualitative phytochemical screening was performed on the ethyl acetate fraction for capsule was revealed the presence of flavonoid and aromatic acids. These were examined by (high -performance liquid chromatography) (HPLC diodarray), (high- performance thin-layer chromatography)(HPTLC).

Flavonoids were isolated by preparative layer chromatography and aromatic acid was isolated by preparative high-

Background: Non-small cell lung cancer (NSCLC) is caused of 85% of all lung cancers. Among the most important factors for lung tumor growth and proliferation are the tyrosine kinase receptors that coded by the epidermal growth factor recep-tor (EGFR) gene. Activation of EGFR ultimately leads to developing of lung cancer. The present study was undertaken with an objective to detect EGFR mutations in bronchial wash from Iraqi patients with NSCLC before treatment. Methods: DNA was extracted from bronchial wash samples collected from 50 patients with NSCLC by using a Qiamp DNA Mini Kit (Qiagen, Hilden, Germany). Then, EGFR mutations were determined by using real-time RCR combined with two technologies, Amplification Refractory Mutation System (