During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

The study area is located within the Hit area, western Iraq. The measurements of Graphical Bristow’s method were carried out by using Pole-dipole array, to delineate the anomaly of apparent resistivity caused by a known cavity target. The survey was applied along two traverses: traverse in W-E direction and traverse in S-N direction above Um El-Githoaa cavity. Data interpretation of the traverse trending W-E, with a-spacing equal to(2m)identified the anomaly of the cavity at a depth of (2.6m), (1.6m) height, and( 9.5m) width, while the actual dimensions of depth, height, and width were (3.80m),( 2.2m), and (12.30m) respectively, with variations of depth equal to (1.2m), high (0.8m), and width( 2.8m). The data interpretation with a-spac

The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

Abstract. In this research, the uranium concentration in (16) water samples collected from some agricultural areas surrounded with AlTuwitha nuclear site in Baghdad-Iraq was measured by using a CR-39 detector. The concentration of uranium in this study was from (0.6 ± 0.33mg/l) to (2.51 ± 0.49 mg/l), and the weighted average for the concentrations (1.262 ± 0.402 mg/l). The results showed it is a concentration of uranium level in water samples studied is higher than the allowed limit recommended by WHO and ICRP.

The average concentration of radionuclide’s in the various banana samples were collected from being the most popular markets in Baghdad city - Iraq were measured by use Sodium Iodide Thallium [NaI(Tl)] detector. The radionuclide’s observed with reliable regularity belonged to the series-decay naturally occurring radionuclide’s headed by 232U and 232Th as well as the non-series nuclide, 40K and 137Cs. The average concentration of 40K was found the least average concentration value recorded as876.74625Bq kg-1.The average concentration of 238U was 28.6425Bqkg-1for ²³²Th, it was found to have the average concentration 14.1805 Bqkg-1. The cesium concentration in the sample was found in the healthy range.

ABSTRACT                

The multi-drug resistant efflux pump is a glycoprotein pump whose function is to push foreign substances. The efflux pump is found in humans, animals. It also has wide-ranging properties in  bacteria and fungi. They are found in all species of bacteria, and efflux pump genes can be found in bacterial chromosomes or mobile genetic elements, such as plasmids. The most sensitive function that leads to a global problem is its resistance to antibiotics in bacterial cells, which increases the ability to bacteria from becoming strong virulence factors that most or all antibiotics cannot kill. It also has othe