The objective of the research is to measure the impact of social responsibility on the financial performance of the Bank of Baghdad for the period from 2014 to 2016 (3 years) through discussing and analyzing the level of practice of the Bank of Baghdad for social responsibility and the impact on their financial performance during the period. To measure the independent variable (CSR), the researcher used the CSR Disclosure Index and relied on the ROA as an indicator to measure the dependent variable (financial performance).The results of the research showed the main hypothesis of the research, which states that the social responsibility of the banks has no significant impact on the financial performance. In relation to the disclosure of s

The current research aims to identify the " impact of strategic warheads numbered ( NHT) in the collection average second grade students in the article of history). " To achieve this, I assumed the researcher that there is no different between the statistically significant the average score for the collection of experimental group who teaches the Arab Islamic history on and a strategic warheads numbered and the average score for the collection of the control group who were studying the same article according to the classic method ( traditional) . The study sample consisted of 64 students from the second grade average in the secondary warka bin nawfal in the general Directorate for education first karkh in Baghdad for the annual cources 2

The research aims at demonstrating the role of the formulation of the green strategy in adopting the areas of the green strategy at the level of jobs in the municipal institutions in the province of Babylon, specifically the Directorate of the municipality of Hilla. The most important areas related to the green strategy were highlighted directly or indirectly, after the indicators of environmental damage emerged from the actions of companies and institutions. The research included a sample size of 222 individual of municipal institutions with different job titles and specializations between the technical and administrative and different levels of academic achievement within the institutions within the Ministry of Construction, Ho

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa