The trade balance is considered as a way to join the national economy with the world, So it is the mirror that reflect the economic center of the country and it is point to competitive ability of it, The tariff and the exchange rate perform a great role to motivate the domestic production and improve the trade balance if we direct them to achieve the same purpose. The Iraqi economic has trade balance which achieve overabundant during the years of studying because of the oil exports, while the other exports represent a small percentage it is hardly remember, and expansion in imports from other side causes exhaustion in oil revenues, and this make the trade balance in permanent

Is the subject of environmental analysis of the important issues that should occupy the attention of the departments of banks in general and banks in particular, the research sample, regardless of their size and the nature of its activity, So if the current era and witnessing rapid developments and changes, making the banking environment is more complex and interconnected than ever, And it became not possible for banks to be aware and understand the external environment variables without an analysis of the various constituent elements and influential heavily in its financial and administrative,Therefore research aims to find out the relationship between the external environment and banking facilities analysis application on the Rafidain

Biped robots have gained much attention for decades. A variety of researches has been conducted to make them able to assist or even substitute for humans in performing special tasks. In addition, studying biped robots is important in order to understand the human locomotion and to develop and improve control strategies for prosthetic and orthotic limbs. Some challenges encountered in the design of biped robots are: (1) biped robots have unstable structures due to the passive joint located at the unilateral foot-ground contact. (2) They have different configuration when switching from walking phase to another. During the singlesupport phase, the robot is under-actuated, while turning into an over-actuated system during the double-support pha

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

This paper shows that there are few studies on errors and difficulties with unstressed pronouns in Spanish. Similarly, when consulting teaching methods, we find that the most consulted texts are ELE manuals. In this sense, the purpose of this paper is to verify the teaching proposal regarding unstressed pronouns in the ELE manuals most used at the Faculty of Languages - University of Baghdad, Iraq. It is urgently needed for ELE teachers in Iraq and students to obtain the most recent ELE manuals, as this will help them teach and learn about unstressed pronouns with texts that contain more didactic and engaging exercises. Furthermore, teachers will be able to plan strategies and lessons for the correct use of these texts.

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p