A research study in which a methodology for quality indicators that can be adopted to evaluate the educational process in educational institutions within a specific strategy helps individuals in charge of educational education to make appropriate decisions based on accurate and properly approved plans to achieve successful outcomes.

These indicators can be used to judge the quality of educational institutions in order to improve, improve and develop them. This study has concluded the necessity of putting quality into actual application in order to benefit from it in evaluating the future action of Iraqi educational institutions.

The external changes brought about by technology and family life have made the

the most important purposes and uses of the test results in the educational sector. This is because the quality of tests is related to their ability to predict the learner's behavior in the future, and the accuracy of the educational and administrative decisions that are taken in light of their results. The study aimed accordingly to reveal the predictive ability of the university Grade Point Average (GPA) in the Score of the specialized test for the position of teacher in the Ministry of Education in the Sultanate of Oman. It further aimed to investigate the differences in the predictive ability according to the specialization and academic year using the descriptive approach. The sample of the study consisted of (349) s/he students enro

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                The research aims to identify the concept of trading securities in Iraq and to propose a new mechanism for the taxation of trading profits and the extent of its impact on tax revenues, as it was observed that there are professional investors in the trading market and some of them achieve huge annual profits. and this profit should be like other taxable profits. The General Commission of Taxes and in cooperation with the Iraq Stock Exchange should identifying those profits, subjecting them to income tax, and adding them to the tax base. The researcher relied on the use of the descriptive and analytical approach bas

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

 Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need

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Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al

Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

     This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s