Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

نشاطات فرع الدراسات الدولية

تعددت التعاريف اللغوية والاصطلاحية لمفهوم الفساد الإداري، ويتضح من خلال هذه التعريفات عدم وجود تعريف موحد له، إلا أنه بشكل عام يشير إلى الخروج على القانون والنظام أو استغلال المال العام لتحقيق مصالح سياسية أو اقتصادية أو اجتماعية لفرد أو جماعة معينة، مما يجعله عملًا غير أخلاقي يتميز بإساءة استعمال السلطة أو الموقع الوظيفي لمنح بعض الأفراد أفضلية على الآخرين. كما يتمثل الفساد الإداري في قيام الموظف العام با

وقائع ندوة فرع الدراسات الدولية

In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

The research aims to present and discuss the accounting bases adopted in accounting for fixed assets in the public sector with an emphasis on its importance in the area of ​​accountability and fixed assets management , based on a realistic problem associated with the use of cash basis accounting in the public sector in Iraq, which are difficult  to provide accounting information useful for many users , including the same units and regulatory departments for the purposes of accountability and management of those assets. Search tool has been the organization questionnaire, its results show the importance of financial reporting for provide accounting information about fixed assets relate to the units of the public sector in Iraq fo

Banks represents financial institutions that influence the economy of any country and their evolution and development is the need to seek all states , communities, maintain and control a guarantee of the beneficiaries investors and to promote confidence, so the specialized organizations trying to set principles and rules must be adhered to and are Basel (II) of the necessary effects to be introduced and work on their application.  Banks exposed by various risks one of them operational risks that have multiple effects on the activity of the institution itself, as well as the national economy, so this study was to find out what those effects and to find solutions and appropriate proposals to avoid Iraqi banks from the effects of risk,

       African countries are among the countries in the world that suffer from the phenomenon of child recruitment in wars and conflicts. There are many reasons behind it, including the nature of the human formation of children, the societal violence to which they are exposed, lack of access to education, economic hardships, as well as the role of African wars and conflicts and other reasons that compelled children to join armed groups and participate in military operations. The recruitment of children is divided into two types, compulsory and voluntary, and this leads to many humanitarian and security repercussions that are not limited to a specific period of time but extend to subsequent generations, and due to its seriousness, t