Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi

The bank risks has greaten and changed in its nature under the developments of financial liberalization, banking innovation and increasing use for new financial instruments which created by the huge technological advancement happened in the banking  industry. So that, banks in large choose to base the profitability measures adjusted for risks; that is we introduced this research. The most important reason led us to do this is the restriction to use the modern statistical methods by trade bank in Arab countries equally with world banks which were the antecedent to base those models. Therefore, the research problem is embedded in the banks need to use measures that link between profitability and risks and this is what achieved by RARC

The research aims to apply one of the techniques of management accounting, which is the technique of the quality function deployment on the men's leather shoe product Model (79043) in the General Company for Textile and Leather Industries by determining the basic requirements of the customer and then designing the characteristics and specifications of the product according to the preferences of the customer in order to respond to the customer's voice in agreement With the characteristics and technical characteristics of the product, taking into account the products of the competing companies to achieve the maximum customer satisfaction, the highest quality and the lowest costs. Hence, the importance of research has emerged, which indicat

After this systematic presentation of the phenomenon of rotation of formulas, ie the construction of the verb and the verb, and the narrated narratives therein differed among the readers, it became clear to us how the difference was clear between reading and the other, and how readers have varied in their readings of the verb, As we have noted through our modest research that the phenomenon of building the verb for the actor and the effect have included the act of both past and present tense, and not limited to a specific time, and this difference in reading was not limited to a particular environment, but beyond To more than one environment This is evidenced by the readings of various readers from the environment of Kufa, Basra, Mecca,

Dust storms are a common ecological occurrence in many world‘s countries, mainly in dry and semi-dry parts. Dust storms tremendously influence human health, the environment, the climate, and numerous social aspects. In this paper, spatial and temporal analysis, metrological triggers, and trajectory, dust exporting areas of a severe dust storm that occurred in Iraq on May 16, 2022, were investigated. The dust storm's backward trajectory was determined using HYSPLIT model, which is then compared with MODIS and Meteosat satellite images. The weather is then analyzed using the NCEP/NCAR Reanalysis model, and the approximate area of these sources was determined using Landsat 8 satellite image classification method. The results revealed

The research dealt with the case stock repurchase policy of Emaar Real Estate Company one of listed companies in Dubai Stock exchange. The research has launched from the cognitive dimensions of repurchasing policy which took great concern in the literatures of financial management, and also this policy became as substitute for distributing the monitory profit in the last three decades in the international financial markets, but it did not get any importance in the Arab Markets such as that of the Arab Gulf in addition to the Iraqi Stock Exchange.

The research summarized a set of conclusions, the most important one was the consistence of analysis result with the test of the major two hypotheses (The first

Current research aims to analyze the relationship and impact of the explanatory variable transcendental leadership, which includes dimensions (values ​​and attitudes, behavior, spirituality, vision and hope/faith) in the responsive variable university performance dimensions (relationships and resources available, human capital development, scientific research, community service). Field research for the leaders of a number of colleges of the University of Baghdad of the deans of the colleges of research and assistants of deans and heads of departments, the main research problem was the important question (what is the role of transcendent leadership in promotin

                     The research entitled "the attitudes of Iraqi People towards the Logic Propaganda for Terrorist Organization such as Daash Regulation, as-Qaida, and Jabhat al-Nasra". It is a field study on the professors and the students of the College of Mass Media at Baghdad University in 2014.

                      After the global war on terrorism declared on September 11, 2011, the researcher finds it is important to study such subject as it threats the unity and sovereignty of Iraq especially after th

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c