A graduation project is a form or work that the study authority requests from the student to measure what he made during the study. Designed an expert system for students’ graduation projects at the University of Basrah for students who are obligated to submit a project that qualifies them to graduate from the university. The system works according to a set of requirements, the most important is first: The student's possession of a high rate that qualifies him for the project. Second: he must possess half of the skills required for the project provided that it includes at least one programming language example (c ++, java, PHP, c #, etc ...). The system has many features that help the Supervisors and Students Committee to manage students' projects efficiently. System is built as a web-based system, with access limited only to the university's local network.

<span lang="EN-US">Oil prices are inherently volatile, and they used to suffer from many fluctuations and changes. Therefore, oil prices prediction is the subject of many studies in the field, some researchers concentrated on the key factors that could influence the prediction accuracy, while the others focused on designing models that forecast the prices with high accuracy. To help the institutions and companies to hedge against any sudden changes and develop right decisions that support the global economy, in this project the concept of cascade networks model to predict the crude oil prices has been adopted, that can be considered relatively as new initiative in the field. The model is used to predict the Iraqi oil prices since as its commonly known that the economy in Iraq is totally depend on oil. Therefore, it is vital to develop a better perception about the crude oil price dynamics because its volatility can cause a sudden economic crisis.</span>

Important paper-based documents exposed to forgery such as: official certificates, birth, marriage, death certificates, selling and buying documents and other legal documents is more and more serious and sophisticated. With the purposes of fraud, appropriation of property, job application and assignment in order to swindle public authorities, this forgery has led to material loss, belief deterioration as well as social instability. There are many techniques has been proposed to overcome this issue such as: ink stamps, live signatures, documented the transaction in third party like the court or notary. In this paper, it's proposed a feasible solution for forgery prevention for paper-based documents using cloud computing application. With the application of quick response bidirectional barcode and the usage of hash algorithm. The study aims at developing an electronic verification system for official and issued books (documents, endorsements, and other official books) to/from different sections of the Institute using QR technology.

The enormous efforts of software systems and unexpected efforts in the late phases of software development in software engineering field led to using methods to estimate software effort at early stages of software preparing phases. Therefore, the question remains how can develop an estimation method to be more accurate and gives a prediction for future software efforts. This paper presents a proposed method for software effort prediction, to enhance software effort estimation phase. The proposed method utilizes feed-forward neural network in recurrent fashion to make a prediction and adapt to handle with varying software types in software engineering. The proposed method (RFFNN) used to enhance the results of ordinary software effort estimation methods, RFFNN gives more efficient results by making a prediction for future software efforts. General TermsSoftware engineering

The global economy is assured to be very sensitive to the volatility of the oil market. The beneficial from oil prices collapse are both consumers and developed countries. Iraq economy is a one-sided economy which is completely depends on oil revenue to charge the economic activity. Hence, the current decline in oil prices will produce serious concerns. Some factors stopped most investment projects, rationalize the recurrent outflow, and decrease the development of economic activity. The study of forecast oil prices is considered among the most complex studies because of the different dynamic variables that affects the strategic goods. Moreover, the laws of economics controlling the prices of oil such as the supply and demand law. Some other variables that control the oil prices are the political conditions when these conditions contribute to the world production. The subject of forecasting has been extremely developing during recent years and some modern methods have been appeared in this regards, for example, Artificial Neural Networks. In this study, an artificial neural network (FFNN) is adopted to extract the complex relationships among divergent parameters that have the abilities to predict oil prices serving as an inputs to the network data collected in this research represent monthly time series data are Oil prices series in (US dollars) over a period of 11 years (2008–2018) in Iraq