Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Border

In this paper, three approximate methods namely the Bernoulli, the Bernstein, and the shifted Legendre polynomials operational matrices are presented to solve two important nonlinear ordinary differential equations that appeared in engineering and applied science. The Riccati and the Darcy-Brinkman-Forchheimer moment equations are solved and the approximate solutions are obtained. The methods are summarized by converting the nonlinear differential equations into a nonlinear system of algebraic equations that is solved using Mathematica®12. The efficiency of these methods was investigated by calculating the root mean square error (RMS) and the maximum error remainder (𝑀𝐸𝑅n) and it was found that the accuracy increases with increasi

In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using  the simulation.

In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

Uropathogenic Escherichia coli is the main cause of urinary tract infections, the ability of this bacteria to cause urinary tract infections is related to a variety of virulence factors that enhance colonization and evade the immune response, one of these virulence factors is cytotoxic necrotizing factor 1 toxin which converts the glutamine residue to glutamic acid to activated GTPase Rho family. The study was meant to find out the prevalence rate of the cnf1 gene in Uropathogenic Escherichia coli isolated from Iraqi patients. Conventional laboratory methods were used for primary bacterial identification and molecular methods were used to confirm bacterial identity and gene detection. Escherichia coli was identified in 89/165 (53.93%) of th

The vegetable cover plays an important role in the environment and Earth resource sciences. In south Iraq, the region is classified as arid or semiarid area due to the low precipitations and high temperature among the year. In this paper, the Landat-8 satellite imagery will be used to study and estimate the vegetable area in south Iraq. For this purpose many vegetation indices will be examined to estimate and extract the area of vegetation contain in and image. Also, the weathering parameters must be investigated to find the relationship between these parameters and the arability of vegetation cover crowing in the specific area. The remote sensing packages and Matlab written subroutines may be use to evaluate the results.

Background: Saliva is one of the most important etiological host factors in relation to dental caries. It affects the carious process by its organic and inorganic constituents; in addition to its physiological functions as (flow rate, pH and buffer capacity). The aims of this study were to determine the concentrations of major elements (calcium and phosphorus) and trace elements (ferrous iron, nickel, chromium and aluminum) in saliva among a group of adolescent girls, and to explore the relation of these elements, flow rate and pH with dental caries. Material & Methods: The study group consisted of 25 girls with an age of 13-15 years old. Dental caries was diagnosed by both clinical and radiographical examinations following the criteria of