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

Diarrhea is a real disease in childhood which could cause death. Therefore, this study was conducted to isolate Salmonella from 350 stool samples taken from children under five years in age, suffering from diarrhea during the period from March 2019 to March 2020 in Tikrit city / Iraq. The results showed the possibility to isolate ten isolates of Salmonella enterica subsp. Enterica, an infection rate, represents 2.875% of the total rate of patients who suffer from diarrhea. The virulence genes were investigated for ten isolates of S. enterica subsp. enterica, the result is that all isolates possessed the genes stn, invA, lpfA with an appearance percentage of 100%, whi

<p>The popularity, great influence and huge importance made wireless indoor localization has a unique touch, as well its wide successful on positioning and tracking systems for both human and assists also contributing to take the lead from outdoor systems in the scope of the recent research works. In this work, we will attempt to provide a survey of the existing indoor positioning solutions and attempt to classify different its techniques and systems. Five typical location predication approaches (triangulation, fingerprinting, proximity, vision analysis and trilateration) are considered here in order to analysis and provide the reader a review of the recent advances in wireless indoor localization techniques and systems to hav

The present study includs the isolation and identification of Keratinophilic fungi in fresh water samples collected from Tigris river in Baghdad, Iraq. Samples were collected from different districts of Baghdad (Al-Rustumia, Madina Al-Teb, Al-Azamia, Al-Kadimia, Al-Dorha and Al-Kanah). The water samples were examined for keratinophilic fungi by the plating method culturing and Hair Baiting Technique. A total number of 18 genera are recorded, in which the Tigris water indicates an impressive diversity of fungi. A variety of fungal strains were isolated from river water, out of 814 fungal colonies, Aspergillus terrus (5.5%) was the most frequent species, followed by Asperg

In the present investigation, 24 adult dipteran species with forensic importance belonging to 13 genera and 8 families that were collected from different localities of Iraq. The specimens were identified by different taxonomical keys; in addition the date and localities of collecting specimens were recorded.

􀀑􀀃Pure Cu (CZTSe) and Ag dopant CZTSe (CAZTSe) thin films with Ag content of 0.1 and 0.2 were fabricated on coring glass substrate at R.T with thickness of 800nm by thermal evaporation method. Comparison between the optical characteristics of pure Cu and Ag alloying thin films was done by measuring and analyzing the absorbance and transmittance spectra in the range of (400-1100)nm. Also, the effect of annealing temperature at 373K and 473K on these characteristics was studied. The results indicated that all films had high absorbance and low transmittance in visible region, and the direct bang gap of films decreases with increasing Ag content and annealing temperature. Optical parameters like extinction coefficientrefractive index, and