Face Identification system is an active research area in these years. However, the accuracy and its dependency in real life systems are still questionable. Earlier research in face identification systems demonstrated that LBP based face recognition systems are preferred than others and give adequate accuracy. It is robust against illumination changes and considered as a high-speed algorithm. Performance metrics for such systems are calculated from time delay and accuracy. This paper introduces an improved face recognition system that is build using C++ programming language with the help of OpenCV library. Accuracy can be increased if a filter or combinations of filters are applied to the images. The accuracy increases from 95.5% (without ap

        The research aims to improve the effectiveness of internal control system according to a model COSO, by identifying the availability of system components according to the model and then improve the effectiveness of each component by focusing on areas for improvement in each component, as it was addressed to a model COSO and then Maamth with the environment, the current Iraqi by introducing some improvements on the form of some mechanisms of corporate governance of the Council of Directors, and senior management, the Audit Committee, Committee appointments, especially that supplies application available in the laws and legislation, the current Iraqi, taking into consideration to make some

This  world is moving towards knowledge economy which basically depends on knowledge and information. So, the economic units need to develop its financial reporting system which helps to provide useful information in timeliness for investors in accordance with the requirements of  the knowledge economy and meets the needs of those investors. This  research aims to revealing the reflects of knowledge economy on the approaches of financial reporting and suggesting a financial reporting model in the environment of knowledge economy,  depending on combining the value approach with the events approach using database and communication technology and providing useful accounting information for all users regardless of

     The goal of the research is to develop a sustainable rating system for roadway projects in Iraq for all of the life cycle stages of the projects which are (planning, design, construction and operation and maintenance). This paper investigates the criteria and its weightings of the suggested roadway rating system depending on sustainable planning activities. The methodology started in suggesting a group of sustainable criteria for planning stage and then suggesting weights from (1-5) points for each one of it. After that data were collected by using a closed questionnaire directed to the roadway experts group in order to verify the criteria weightings based on the relative importance of the roadway related impacts

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         The research aims to measure the impact of infor

This paper aims to build a modern vision for Islamic banks to ensure sustainability and growth, as well it aims to highlight the positive Iraqi steps in the Islamic banking sector. In order to build this vision, several scientific research approaches were adopted (quantitative, descriptive analytical, descriptive). As for the research community, it was for all the Iraqi private commercial banks, including Islamic banks. The research samples varied according to a diversity of the methods and the data availability. A questionnaire was constructed and conducted, measuring internal and external honesty. 50 questionnaires were distributed to Iraqi academic specialized in Islamic banking. All distributed forms were subject to a thorough analys

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par