The Reversed Phase High Performance Liquid Chromatography (RP-HPLC) has been used for the separation of Poly aromatic hydrocarbons(PAHs) by using column Reprosil 100 C 18 which was found to be a suitable one for this purpose. The result showed that using mobile phase of (Acetonitrile-water) Reversed Phase HPLC , flow rate of (1.2 ml/min) , column temperature (30CËš) and wave length of (254nm), give a complete separation with a good resolution . The total separation time was less than 20 min. The result of the study showed that the vegetables of Baghdad city were polluted by poly aromatic hydrocarbons(PAHs) in different places where samples taken because of drainage of the heavy water ,industrial trash and trash of oil colanders. -

  The research addresses the feminist lament and its representations in the contemporary Arab theatrical text as one of the purposes of the Arabic poetry and its images, samples, and reasons developed and its incentives multiplied through different time periods in which a dramatic image and representations have been manifested that harmonized with the art of theatre. In order to shed light on these representations, this study has come to look for the representations of lament phenomenon in the Arab theatre texts.
The study consists of an introduction in which the two researchers put forward the research problem, significance and objectives, and a theoretical framework which tackles a theoretical foundation for the research consi

Background: One of the most common and prevalent oral diseases among adolescents is periodontal disease particularly gingivitis, however enamel anomalies and dental trauma could occur. Aims of the study: This study was conducted among 14-15 years intermediate school male students in urban area of Al-Khalis city to assess the oral hygiene (dental plaque) and to estimate the prevalence and severity of gingivitis, enamel anomalies, as well as traumatic dental injuries, furthermore to show the significant difference between these two ages concerning these oral problems. Materials and methods: In this study the total sample consisted of 735 students (397 aged 15 years and 338 aged 14 years ). In present study dental plaque was recorded accord

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

<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami

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