Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well-  Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.

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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

The aim: In this study, we present and evaluate the vest-over-pants technique as a simple way to correct urethrocutaneous fistulas after hypospadias. Materials and methods: Between October 2018 and June 2020, twenty male patients aged 5 to 20 years came to us with post hypospadias repair fistula, these patients underwent vest-over-pant repair of their fistula. The size of fistula was ranging between 2.5-5 mm. The distribution of fistula was coronal (3 patients), distal penile (9 patients), midshaft (2 patients) and proximal penile (6 patients). In 14 patients there were single fistula and 6 patients had more than one fistula. Eleven of patients were exposed to a previous failed fistula repair procedure. Results: Six months after the operati

 A biological experiment was done in the green house of Biology Department, college of Education (Ibn – AL haitham), Baghdad university, in pots (2Kg size), for growth season 2009, to study the effect of two concentrations of gibberellic acid which was (50) and (100) ppm, and two levels of Diamonium phosphate fertilizer which was(0.16) and (0.32) gm/2kg pot which equal (40) and (80) kg/d, in growth of root of one lentil cultivar (AL- Baraka), upon compeletely randomized design with three replications. The results showed that there was a significant increase in (root’s length, volumes of roots, fresh and dry weights, number of nodules, and the percents of nitrogen and protein), by increasing of gibberellic acid concentr

Effects of Ozonated Water on Micro Leakage between Enamel and Fissure Sealants Prepared by Different Etching Technique (An in vitro Study), Baraa M Jabar*, Muna S Khalaf

      Low cost Co-Precipitation  method was used for Preparation of novel nickel oxide (NiO) nano particle thin films with Simple, with two different PH values 6, 12 and its effect on structural and optical properties as an active optical filter. Experimental results of structural properties X-ray diffraction (XRD) showed that both Nickel oxide nanoparticles with (PH=6 and 12) have polycrystalline structure smaller average particle size about 8.5 nm for PH=6 in comparison with PH=12. Morphological studies using Scanning electron microscopy (SEM) and  atomic force microscope (AFM)  show uniform nano rod distribution for PH=6 with smaller average diameter, average roughness as compared with NiO with

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

This paper presents a linear fractional programming problem (LFPP) with rough interval coefficients (RICs) in the objective function. It shows that the LFPP with RICs in the objective function can be converted into a linear programming problem (LPP) with RICs by using the variable transformations. To solve this problem, we will make two LPP with interval coefficients (ICs). Next, those four LPPs can be constructed under these assumptions; the LPPs can be solved by the classical simplex method and used with MS Excel Solver. There is also argumentation about solving this type of linear fractional optimization programming problem. The derived theory can be applied to several numerical examples with its details, but we show only two examples