Objectives: To assess the premenstrual syndrome among the working women in Baghdad City.
Methodology: A cross-sectional analytic study, using probability sampling cluster (multi-stage) sampling of
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designed and consisted of (4) parts, including demographic, reproductive, menstrual cycle characteristics, and
premeustmual syndrome symptoms. Content validity and reliability of the questionnaire were detemined by
conducting a pilot study. Descriptive and inferential statistical procedures were used to analyze the data.
Results: The results of the study revealed that the age of women ranged betwee

Background: Animal bites in humans are an important public health problem. Most of these bites are dog bites. Dog bites in humans are a complex problem embracing public health and animal welfare, both in developed and developing nations. .
Al-kindy Col Med J Vol.8 No.2 2012 P: 149
Objectives: in order to estimate the magnitude of the problem and to understand the epidemiological characteristics of dog bite victims registered in Baghdad city regarding their age, sex, number of registered dog bite victims per month and year along the studied period ( 2006-2010) and also to sniff out any seasonal variation in dog bite attacks .
Methods: A across-sectional study was carried out during January (2011), in the Anti-Rabies clinic of (Pa

The objective of this study was to assess the nutritional status of childs of nurseries in Baghdad city so that an early detection of malnutrition cases could be carried out. The results revealed that the daily consumption of food calories, protein, fat and carbohydrate were 1180.5 calories, 27.2gm, 38gm and 180gm, respectively, which were less than the RDA values and the percentages of these nutrients supplied by the food intake were 90.8, 83.7, 87.3 and 90.3%, respectively. It was also demonstrated that the highest percentages of stunting, underweight and wasting, which amounted to 32, 22.7 and 1.5%, respectively, were among those childs who obtained inadequate calories, while the percentages of the forementioned malnutrition cases amon

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost