This is a contribution to study the situation of a dwelling of previous case of kala- azar in the endemic area (AL-Mahmodiya/ AL-Rasheed district) about 25 km south of Baghdad.  In order to assess the possible ecological causes of the incidence and the prevalence of visceral leishmaniasis, in one of the well-known foci of the disease in the central region of Iraq. It was found that the human dwelling position and ecological factors affect the infection with this disease.

This research takes up address the practical side by taking case studies for construction projects that include the various Iraqi governorates, as it includes conducting a field survey to identify the impact of parametric costs on construction projects and compare them with what was reached during the analysis and the extent of their validity and accuracy, as well as adopting the approach of personal interviews to know the reality of the state of construction projects. The results showed, after comparing field data and its measurement in construction projects for the sectors (public and private), the correlation between the expected and actual cost change was (97.8%), and this means that the data can be adopted in the re

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

The method of solving volterra integral equation by using numerical solution is a simple operation but to require many memory space to compute and save the operation. The importance of this equation appeares new direction to solve the equation by using new methods to avoid obstacles. One of these methods employ neural network for obtaining the solution.

This paper presents a proposed method by using cascade-forward neural network to simulate volterra integral equations solutions. This method depends on training cascade-forward neural network by inputs which represent the mean of volterra integral equations solutions, the target of cascade-forward neural network is to get the desired output of this network. Cascade-forward neural

Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

The recent study was conducted to measure some heavy metal content in potato and corn chips in Baghdad markets. Samples were analyzed by Atomic Absorption Spectrophotometer (AAS). Four metals, Cobalt (Co), Cadmium (Cd), Cupper (Cu) and Lead (Pb) were determined. Two types belonging to two manufacturer resources and two trademarks for each resource were tested in this work. Generally, the study recorded that the potato chips were containing metals less than the corn chips. According to Iraqi criteria, all tested types of potato chips were under the allowed levels. The mean of accumulation trend for both types was: Cu>Co>Pb>Cd. The mean of accumulation trend for the corn types of chips was: Baz>Pufack> Fantasia > Snack. T

    This research involves the application of spectral indices and GIS techniques coupled with the Analytic Hierarchy Process, to assess  Baglia site, eastern Missan, as a water harvesting potential site. The AHP and pairwise comparison have been used through select four criteria including TWI, TRI, MNDWI, and NDSI, which were deemed as impact factors for this study. All these criteria have been weighted according to their significance in the water harvesting system. The findings of the AHP analysis method explained that the WH potential zones in Baglia site were divided into three zones, namely, high,  medium, and low suitability. The findings demonstrate that  Bglia site, where the highly appropriate zone is located in the deep v