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 study included evaluation of cell surface charge and hydrophobicity of Escherichia coli, Klebsilla aerogenes, Proteus spp, Bacillus cereus, Staphylococcus epidermidis, Staphylococcus aureus(1) and Staphylococcus aureus(2) were determined by hydrocarbon adherence and hydrophobic interaction chromatography. The results showed that the negative charge of cell surface of gram negative bacteria was much higher than on gram positive once when these bacteria were grown on nutrient agar at 37 c for 18 h . E.coli was more negative charged than Klebsilla aerogenes and Proteus spp. The hydrophobicity of gram positive bacteria was much

Controlling public expenditures is one of the main objectives of the public budget. The public budget often suffers from a deficit, whether in developed or developing countries, because expenditures are usually greater than the revenues generated. This requires the existence of financial rules that are adhered to by the government, which in turn leads to discipline. Fiscal policy leads to a reduction in the obligations incumbent on the government.  Adhering to the financial rules would correct the course of fiscal policy in Iraq, with the need to direct oil revenues in the years of financial abundance when global oil prices rise to sovereign funds similar to other rentier countries, which contributes to maintaining the stabi

The aim of this paper is to design feed forward neural network to determine the effects of
cold pills and cascades from simulation the problem to system of first order initial value
problem. This problem is typical of the many models of the passage of medication throughout
the body. Designer model is an important part of the process by which dosage levels are set.
A critical factor is the need to keep the levels of medication high enough to be effective, but
not so high that they are dangerous.

    This study was designed to investigate the capability of gram-negative bacteria that isolated form wound and burn infection to production of Biofilm which included (32) isolates, which have multi – drug resistant to antibiotics. The isolates included (10) Pseudomonas aeruginosa, (9) Klebsiella pneumoniae, (6) Escherichia coli, (5) Proteus mirabilis and (2) Enterobacter cloacae. The method used method links the crystal violet with biofilm and reading by ELISA which was adopted on the values of optical density of violets that linked to the mass of biofilm at the wavelength of (620) nm, the test results showed variation of biofilm composition for all bacterial species depending on the optical density value while th

The research aims to statement the main obstacles that prevent the application of total quality management (TQM) in a number of Iraqi service organizations, and by one organization in each of the sectors (health, finance, education, higher education, tourism), which are, (Al-Yarmouk Teaching Hospital, Rafidain Bank/ Branch of Hay Al-Arabi Al-Jadid, Al-Karkh/1 Directorate of Education, College of administration and Economics/ Baghdad University, International Palestine Hotel). The research also, tries to classify the priority of the obstacles depending on the type of service organization surveyed. And diagnoses the extent to which or the difference of the research sample members views on the order of obstacles of TQM, and also proposes a

The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled