Support Vector Machine (SVM) is supervised machine learning technique which has become a popular technique for e-mail classifiers because its performance improves the accuracy of classification. The proposed method combines gain ratio (GR) which is feature selection method with one-class training SVM to increase the efficiency of the detection process and decrease the cost. The results show high accuracy up to 100% and less error rate with less number of feature to 5 features.

Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assump

A large number of researchers had attempted to identify the pattern of the functional relationship between fertility from a side and economic and social characteristics of the population from another, with the strength of effect of each. So, this research aims to monitor and analyze changes in the level of fertility temporally and spatially in recent decades, in addition to estimating fertility levels in Iraq for the period (1977-2011) and then make forecasting to the level of fertility in Iraq at the national level (except for the Kurdistan region), and for the period of (2012-2031). To achieve this goal has been the use of the Lee-Carter model to estimate fertility rates and predictable as well. As this is the form often has been familiar

In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

In this paper, the Monte-Carlo simulation method was used to compare the robust circular S estimator with the circular Least squares method in the case of no outlier data and in the case of the presence of an outlier in the data through two trends, the first is contaminant with high inflection points that represents contaminant in the circular independent variable, and the second the contaminant in the vertical variable that represents the circular dependent variable using three comparison criteria, the median standard error (Median SE), the median of the mean squares of error (Median MSE), and the median of the mean cosines of the circular residuals (Median A(k)). It was concluded that the method of least squares is better than the

There are different types of young isolated NSs: radio pulsars, compact central X-ray sources in supernova, magentas: anomalous x-ray pulsars (AXPs) and soft gamma-ray repeaters (SGRs).This paper shows that the value of magnetic field (B), characteristic age ( ), spin down luminosity ( equilibrium period ( and Flux density ( ) was determined depending on some properties of pulsar star, such as the value of period of the pulsar (P) and the time derivative period ( for sample stars which were adopted. The model that which adopted is Hallo Cone Model. The results showed that the Normal pulsar stars have a big magnetic field, equilibrium period and Spin down than the Millisecond pulsar stars.But Millisecond pulsar stars have large values of

Abstract

The research examined with the importance banking merger to address the situation of Troubled banks in Iraq, Through The use of Logistic Regression Model. . The study attempted to present a conceptual aspect of banking merger and logistic regression, as well as the applied aspect which includes a sample consisting of six private Iraqi banks, and the hypothesis of the study is that the promotion of mergers among banks has positive impacts on improving the efficiency of performance of troubled banks, which contributes to the increase of banking services, raise of their financial indicators and the high liquidity and profits of the new banking entity as it is a way to overcome the prevailing banking crises.