The thermodynamic constanting of “crude and partially purified” Paraxonase(PON) was evaluated in the sera of “healthy and ectopic” pregnant women in order to characterize the reaction of PON with diethyl para-nitro phenyl phosphate as substrate.This study was performed on (17) women with ectopic pregnancy (EP) whose age between (25-55) years  and (25) normal pregnant women with  a mean age of (25 -55) years as  a control group . Samples were collected from the Medical City, AL-Yarmook and Fatema AL-Zahraa hospitals during the period from Sep.2011 to April 2012.The study included the evaluation  of “paraxonase activity, specific activity and total protein” in the (crude and partially purified) sera of EP pa

هدفت الدراسة لالقاء الضوء على وضع المرأة في التعليم العالي في العراق خلال الاعوام الدراسية: 2008 - 2009, 2010 – 2011 و2011- 2012. تتيح القوانين والتعليمات في التعليم العالي في العراق فرص متكافئة للاناث والذكور للتسجيل في الدراسات الاولية والعليا، وكذلك عدم التمييز في الرواتب الشهرية للمنتسبين وفقا لنوع الجنس (الجندر ). بلغ متوسط عدد الاناث في مرحلة الدراسة الاولية في مؤسسات التعليم العالي في العراق لثلا

Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Although text document images authentication is difficult due to the binary nature and clear separation between the background and foreground but it is getting higher demand for many applications. Most previous researches in this field depend on insertion watermark in the document, the drawback in these techniques lie in the fact that changing pixel values in a binary document could introduce irregularities that are very visually noticeable. In this paper, a new method is proposed for object-based text document authentication, in which I propose a different approach where a text document is signed by shifting individual words slightly left or right from their original positions to make the center of gravity for each line fall in with the m

In this work a fragile watermarking scheme is presented. This scheme is applied to digital color images in spatial domain. The image is divided into blocks, and each block has its authentication mark embedded in it, we would be able to insure which parts of the image are authentic and which parts have been modified. This authentication carries out without need to exist the original image. The results show the quality of the watermarked image is remaining very good and the watermark survived some type of unintended modification such as familiar compression software like WINRAR and ZIP

Wireless networks and communications have witnessed tremendous development and growth in recent periods and up until now, as there is a group of diverse networks such as the well-known wireless communication networks and others that are not linked to an infrastructure such as telephone networks, sensors and wireless networks, especially in important applications that work to send and receive important data and information in relatively unsafe environments, cybersecurity technologies pose an important challenge in protecting unsafe networks in terms of their impact on reducing crime. Detecting hacking in electronic networks and penetration testing. Therefore, these environments must be monitored and protected from hacking and malicio

With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.