The importance of this research is to clarify the nature and the relationship between the indicators of financial policy and banking stability in Iraq, as well as to find a composite index reflects the state of banking stability in Iraq in order to provide an appropriate means to help policymakers in making appropriate decisions before the occurrence of financial crises.

     Hence, the problem of research is that the fiscal policy has implications for the macro economy and does not rule out its impact on banking stability. Moreover, the central bank does not possess a single indicator that reflects the stability of the banking system, rather than the scattered indicators that depend o

        Throughout this paper, three concepts are introduced namely stable semisimple modules, stable t-semisimple modules and strongly stable t-semisimple. Many features co-related with these concepts are presented. Also many connections between these concepts are given. Moreover several relationships between these classes of modules and other co-related classes and other related concepts are introduced.

المقدمة

تعد السياحة احد مستلزمات الحضارة الحديثة لما تفرزه من آثار ايجابية ودور متميز في دعم الاقتصاد الوطني وتقليل نسبة البطالة وتنشيط الحركة التجارية بين البلدان، اذ لا يمكن ان نتصور وجود بلد متحضر بلا فنادق ولا سياحة وتقديم مختلف السلع والخدمات سياحية التي يمكن ان تسبع الحاجات والرغبات واذواق السياح من خلال  وجود منشآت سياحية تعكس النمط السياحي القائم على اختلاف انواعه

This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan

Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and

Due to the increasing number of people with in Iraq, it has become necessary to treat seriously this problem, which was not considered significantly to the best of researcher knowledge. Thus, the current research aims to construct a scale to measure the physical down syndromes, which distinguish them from others. It consisted of (39) items. The researcher has presented some related literature that addressed the current problem

        The study aims to show the correlation between inflation rates and the volume of private sector deposits in Jordan on one hand, and Amman Stock Exchange index for the period of 1999-2017. The study used the “Vector Auto Regression” model. Different types of tests are used such as: The “Johansen Co integration” test of joint integration, “Granger causality” test, the “Analysis of Variance Decomposition”, and “Impulse response Function” test.

The results showed there is a positive-one-way causal effect from Amman Stock Exchange index to inflation. Also, a one-way causal effect that comes from Amman Stock Exchange index to the size of private sec

   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