Abstract

Abstract has many advantages as has historically been one of the regions leading cultural centers . for centuries , it has been a center of commertial and financial operations in Iraq. it is also rich in archeological sites and natural resources, but because of its wars and implementation of urban development strategies are effective and sustainable , so contracted the secretariat of Baghdad with the company (khatib and scirntiffic) for the preparation of the comprehensive development plan for the city of Baghdad in 2030 and funded by the world bank and the fact that the plan was approved ( three stages of it ) and only one phase remains the fourth stage, which is under discussion the aim of the

Abstract\

In this research, estimated the reliability of water system network in Baghdad was done. to assess its performance during a specific period. a fault tree through static and dynamic gates was belt and these gates represent logical relationships between the main events in the network and analyzed using dynamic Bayesian networks . As it has been applied Dynamic Bayesian networks estimate reliability by translating dynamic fault tree to Dynamic Bayesian networks and reliability of the system appreciated. As was the potential for the expense of each phase of the network for each gate . Because there are two parts to the Dynamic Bayesian networks and two part of gate (AND), which includes the three basic units of the

Objectives: To determine the (QoL) for patients with permanent pacemaker and to find-out the relationship between
these patients’ (QoL) and their sociodemographic characteristics such as age, gender, level of education, and
occupation.
Methodology: ٨ purposive non-probability” sample of (62) patient with permanent pacemaker was involved in this
study. The developed questionnaire consists of (4) parts which include !.demographic data form, 2.disease-related
information form, 3.socioeconomic data form, and 4.Permanent pacemaker patient’s quality of life questionnaire data
form. The validity and reliability of the questionnaire were determined through the application of a pilot study. ٨
descriptive statistical a

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% respectively. For

The aim of this research is to use robust technique by trimming, as the analysis of maximum likelihood (ML) often fails in the case of outliers in the studied phenomenon. Where the (MLE) will lose its advantages because of the bad influence caused by the Outliers. In order to address this problem, new statistical methods have been developed so as not to be affected by the outliers. These methods have robustness or resistance. Therefore, maximum trimmed likelihood: (MTL) is a good alternative to achieve more results. Acceptability and analogies, but weights can be used to increase the efficiency of the resulting capacities and to increase the strength of the estimate using the maximum weighted trimmed likelihood (MWTL). In order to perform t

     The sunrise, sunset, and day length times for Baghdad (Latitude =33.34º N, Longitude =44.43º E) were calculated with high accuracy on a daily basis during 2019. The results showed that the earliest time of sunrise in Baghdad was at 4h: 53m from 5 Jun. to 20 Jun while the latest was at 7h: 07m from 5 Jan. to 11 Jan. The earliest time of sunset in Baghdad was at16 h: 55m from 30 Nov. to 10 Dec. whereas the latest was at 19h: 16m from 25 Jun. to 5 Jul. The minimum period of day length in Baghdad was 9h: 57m) in 17 Dec. whereas the maximum period was 14h: 22m) in 20 Jun. Day length was calculated and compared among regions of different latitudes(0, 15, 30, 45 and 60 north).