In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as  the Bayes method. The comparison was made using the mean error squares (MSE), where the best  estimator  is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).

The article is devoted to the Russian-Arabic translation, a particular theory of which has not been developed in domestic translation studies to the extent that the mechanisms of translation from and into European languages are described. In this regard, as well as with the growing volumes of Russian-Arabic translation, the issues of this private theory of translation require significant additions and new approaches. The authors set the task of determining the means of translation (cognitive and mental operations and language transformations) that contribute to the achievement of the most equivalent correspondences of such typologically different languages as Russian and Arabic. The work summarizes and analyzes the accumulated exper

For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

This paper includes the application of Queuing theory with of Particle swarm algorithm or is called (Intelligence swarm) to solve the problem of The queues and developed for General commission for taxes /branch Karkh center in the service stage of the Department of calculators composed of six  employees , and it was chosen queuing model is a single-service channel  M / M / 1 according to the nature of the circuit work mentioned above and it will be divided according to the letters system for each employee, and  it was composed of data collection times (arrival time , service time, departure time)

In this research, the focus was placed on estimating the parameters of the Hypoexponential distribution function using the maximum likelihood method and genetic algorithm. More than one standard, including MSE, has been adopted for comparison by Using the simulation method