The steel jetty selected for strengthening is in Baghdad city, over Tigris River, consists of 55 short spans, each of approximately 4 meters and one naviga-tional opening of 12 m. The bridge is 224 meters length and 8 meters in width. The strengthening system was designed to remove overstresses that occurred when the bridge was subjected to abnormal loads of 380 tons. A strengthening system which installed in spring 2008 was used where the main concept is to depend on added side supporting elements which impose reversal forces on the bridge to counteract most of the loads expected from the abnormal heavy loads. The bridge was load tested before and after the strengthening system was activated. The load test results indicate that the strengt

<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In

The social networking sites have become one of the most important promotional instruments for their characteristic of facilitation of communication and the creation of public platform for discussion and formation of new points of view. These sites were used in the political marketing process where politicians use Facebook pages to promote their ideologies and spread their programs for the purpose of an influencing public opinion.
This research deals with the way by which political products are the Iraqi parliament. We adopt the methodology for analyzing the contents of these pages during three months starting from September,12 2016 to March 1, 2017 characterized by a lot of changes and events, in particular the beginning of the war o

We aimed to examine the effect of amoxicillin and azithromycin suspensions on the microhardness of sliver-reinforced glass ionomer and nano-resin modified glass ionomer (GI). Method: Thirty discs (2mm height x 4mm diameter) of each type of GI were prepared, which were randomly assigned to amoxicillin, azithromycin, and artificial saliva groups. Microhardness was evaluated by Vickers hardness test before and after three immersion cycles. Results: The overall model (P < 0.001), before/after intervention (P < 0.001), intervention group (type of antibiotic) (P=0.013), and type of glass ionomer (P < 0.001) showed significant differences among study groups (P < 0.001). Post hoc test showed only non-significant before/after difference for Azithrom

Purpose: To determine the impact of service encounter in stimulating voluntary customer behaviors.

• Approach / methodology: It was selected a sample of customers Bank Iraqi Trade (TBI) was (105) individual, using a questionnaire designed in the light of previous studies, was drafted scale and tested in the light of a group of statistical methods developed (reliability coefficient, reliability coefficient composite, convergence). Then test hypotheses through structural equation modeling.
• Results: The behaviors and characteristics of the service provider in effect urged bank customers to perform voluntary extra, as the service environment service encounter

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The Invar effect in 3D transition metal such as Ni and Mn, were prepared on a series composition of binary Ni_1-xMn_x system with x=0.3, 0.5, 0.8 by using powder metallurgy technique. In this work, the characterization of structural and thermal properties have been investigated experimentally by X-ray diffraction, thermal expansion coefficient and vibrating sample magnetometer (VSM) techniques. The results show that anonymously negative thermal expansion coefficient are changeable in the structure. The results were explained due to the instability relation between magnetic spins with lattice distortion on some of ferromagnetic metals.    

This study reports the fabrication of tin oxide (SnO₂) thin films using pulsed laser deposition (PLD). The effect of ⁶⁰Co (300, 900, and 1200 Gy) gamma radiation on the structural, morphological, and optical features is systematically demonstrated using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), atomic force microscopy (AFM), and ultraviolet-visible light analysis (UV-Vis), respectively In XRD tests, the size of the crystallites decreased from 45.5 to 40.8 nm for the control samples and from 1200 Gy to 60Co for the irradiated samples. Using FESEM analysis, the particle diameter revealed a similar trend to that attained using XRD; in particular, the average diameters were 93.8 and