In light of the limited sources of funding suffered by the Iraqi economy, it highlights the importance of enhancing the efficiency of public expenditure, and if the measurement of the efficiency of public expenditure and identify benchmarks first step of promoting efficiency, the adoption of scientific methods of analysis imperative in promoting the efficiency. Under this framework, the focus was on the methodologies used to measure the efficiency of public spending and supply analysis with trying statement strengths and weaknesses, and make use of it in the measurement of the efficiency of public spending in the Iraqi economy. As well as devise measurable indicators take into account the specificity of the Iraqi economy and the

سلمان، ندى نجيب. 2015. التباين المكاني السكان الأميين في الوطن العربي للمدة 1990-2009. مجلة آداب ذي قار،مج. 4، ع. 15، ص ص. 101-126.

The research aimed to evaluate the financial performance of the Public Company for the manufacture of medicines and medical supplies / Samarra - Iraq to know the strengths and weaknesses that affect its performance, as well as to compare its performance in the years between (2017-2019), which are characterized by security stability with its performance in previous years (2014 -2016) which is characterized by security instability, to assess the extent of its ability to achieve growth in performance, by answering the main question, what is the evaluation of the performance of the Public Company for the manufacture of medicines and medical supplies / Samarra - Iraq in the light of financial indicators?

Abstract
The use of electronic valves is commonly available. yet, the most
common is the techniques of communications as prod casting transmitter that
are used by these valves in addition to their use in communication tools as far
distance telephone, electronic measuring techniques , and others.
In this study, an attempt is endeavored for improving the efficiency of the
vacuum micro- valves(GI-19b) through activating their internal surfaces by the
use of ionic pumping which is used for treating valves which are out of order
(because of sedimentation some materials and oxide on its poles). The
existence of these materials and oxide increase the sum of current leakage
moving in between. The use of ionic pumpin

The aim of robot path planning is to search for a safe path for the mobile robot. Even though there exist various path planning algorithms for mobile robots, yet only a few are optimized. The optimized algorithms include the Particle Swarm Optimization (PSO) that finds the optimal path with respect to avoiding the obstacles while ensuring safety. In PSO, the sub-optimal solution takes place frequently while finding a solution to the optimal path problem. This paper proposes an enhanced PSO algorithm that contains an improved particle velocity. Experimental results show that the proposed Enhanced PSO performs better than the standard PSO in terms of solution’s quality. Hence, a mobile robot implementing the proposed algorithm opera

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings