The aim of the research is to provide an analytical study to promote financial inclusion in Iraq by clarifying the opportunities and challenges of the economic and demographic situation in Iraq, studying the structure of the financial system and introducing non-bank financial institutions operating in Iraq, and using the descriptive approach. Analytical in the study of the phenomenon of research, the research reached a number of conclusions, the most prominent of which were:

• Iraqi society is a young society.
• The majority of the population is 70 percent. They live almost in urban areas.
• The coverage of bank branch networks is concentrated in only four provinces, leaving other provinces outside financial

This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.

Calculating the Inverse Kinematic (IK) equations is a complex problem due to the nonlinearity of these equations. Choosing the end effector orientation affects the reach of the target location. The Forward Kinematics (FK) of Humanoid Robotic Legs (HRL) is determined by using DenavitHartenberg (DH) method. The HRL has two legs with five Degrees of Freedom (DoF) each. The paper proposes using a Particle Swarm Optimization (PSO) algorithm to optimize the best orientation angle of the end effector of HRL. The selected orientation angle is used to solve the IK equations to reach the target location with minimum error. The performance of the proposed method is measured by six scenarios with different simulated positions of the legs. The proposed

Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Border

A field experiment was carried out in the fields of the Field Crops Department - Faculty of Agricultural Engineering Sciences. The study included five inbred lines (ZM43W (ZE), ZM60, ZM49W3E, ZM19, CDCN5), given numbers 1, 2, 3, 4 and 5) to study the hybrid vigor and both general and special combing ability (GCA, SCA) of the half diallel mating method, for the spring and fall seasons (2016). The genetic analysis shows that all crosses gave a positive hybrid vigor for grain yield per unit area at the two population densities. the highest value is 116.20% for cross (3´5 )at low density, and 89.22% for cross( 1´4 )at high density. The hybrid vigor for all crosses is positive at two densities for dry matter yield, crop growth rate an