Abstract

Due to the momentum of winning in the streets of the city of Baghdad as a result of the large number of checkpoints so felt researcher to conduct a field visit to find out the main reasons that led to this congestion and to find practical solutions to mitigate wastage winning the arrival time citizen to where you want the least possible time.

This research aims to overcome the difficulties experienced by citizens to reach their places of work and reduce waste at the time of service and waiting time as well as reduce the cost of waiting.

Has emerged study a set of conclusions, including the use of model queue (G / G / C) and the mome

The aims of this reserch is identify  evaluate the organizational commitment level of (emotional, standard, continuous) and the level of discipline dimensions (functional duties, professional responsibility and ethics) for medical doctors in Ramadi Teaching Hospital due to their relationship with the organization effectiveness the level of completion work and the importance of the expected results in the field respondent

sample of (50) doctors has from all branches and specialties, including specialist doctors consultants and practitioners as well as branches of residence and senior the most prominent results reached are the emotional and the  st

This paper presents the design and analysis of composite right left hand (CRLH) electromagnetic bandgap (EBG) structure. The proposed unit cell is consistent of a dielectric substrate with dimensions of 5×5×1 mm 3 made of FR4-Epoxy with εr = 4.4 underneath of a conductive patch with dimensions of 4.4×4.4mm 2 . The unit cell is structured to perform a negative permittivity (ε) and negative permeability (µ) in different bands. The proposed unit cell is developed to 5G systems in the sub-6GHz bands. In this work, a complete analysis of the unit cell in terms of Sparameters, constitutive parameters and refraction index are evaluated using HFSS simulation package based on Finite Element Method (FEM).

The UN plans to achieve several development objectives by 2030. These objectives address global warming, a major issue. This method aims to improve sustainable accounting performance (AP). In this circumstance, AI is being applied in various fields, notably in economic, social, and environmental (ESE) domains. This research investigates how sustainable development (SD) influences AI methodologies and AP improvement. The research examined a sample of Iraqi banks listed on the Iraq Stock Exchange from 2014 to 2022. AI was measured by ATM and POS prevalence. A three-dimensional approach examined economic, social, and environmental (ESE) sustainability. Meanwhile, the performance of sustainable accounting was measured through the return on asse

After a temporary halt to forced thghebr in different cities of Iraq this methodlogy
opeations returned directiy in the areas of political conflict on the ground which are translated
operations and forced displacement violence es they operations aimed at completing the
forced displacement that occurred after the occupation in(2003)which took an upward curve
publicly after these events and some of which are aimed at the liquidation of some provinces
than any demographic diversity of religious or sectarian or alhens and others aimed at
redemographic distribution within the province itself to produce a net sectarian zones as is the
case in Diyala Nineveh and Babylon Baghdad has the epicenter of sectarian violence and th

The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD).  In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve