This paper argues the accuracy of behavior based detection systems, in which the Application Programming Interfaces (API) calls are analyzed and monitored. The work identifies the problems that affecting the accuracy of such detection models. The work was extracted (4744) API call through analyzing. The new approach provides an accurate discriminator and can reveal malicious API in PE malware up to 83.2%. Results of this work evaluated with Discriminant Analysis

In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .

Background: The main purpose of this study is to find if there is any correlation between the level of C-reactive protein (CRP) in gingival crevicular fluid with its serum level in chronic periodontitis patients and to explore the differences between them according to the probing depth. Materials and methods: Forty seven male subjects enrolled in this study. Thirty males with chronic periodontitis considered as study group whom further subdivided according to probing depth into subgroup 1 with pocket depth ≤6mm, subgroup 2 with pocket depth >6mm. The other 17 subjects considered as controls. For all subjects, clinical examination where done for periodontal parameters plaque index (PLI), gingival index (GI), bleeding on probing (BOP),

Background: The posterior slope of the articular eminence of completely edentulous patients compared to patients with maintained occlusion shows significant flattening. This study aimed to correlate between the flattening of the posterior slope of the articular eminence, with dental status, age, genders, on both sides using computed tomography. Materials and Methods: The sample of the present study was a total of 117 Iraqi subjects, who admitted to the maxillofacial department at Al-Sadr Teaching Hospital in Al-Najaf city. The examination was performed on CT scanner; the eminence inclination was measured in two methods using sagittal section. Results: Clinically, the inclination of articular eminence was higher in edentulous subjects than i

The reinforced fiberglass in cement slurry reflects the effect on its properties compared to usual additives. Fiberglass is typically used in cement slurry design for one or another of the following goals: (Earth earthquake, bearing storage, and with differential stresses, to enhance cement durability and increase its compressive strength). The main goal is to use glass fiber and ground fiberglass to improve the tensile strength and moderate compressive strength significantly. On the other hand, the use of glass fibers led to a slight increase in the value of thickening time, which is a desirable effect. Eleven glass fiber samples and milled glass fiber were used to show these materials' effect on Iraqi cement with (0.125, 0.25, 0.5

This contribution provides an atomistic understanding into the impact of W, Nb, and Mo co-substitution at Hf-site of cubic HfO2 lattice to produce Hf1−xTMxO2 system at x = 25%. The calculations have been performed under the framework of density functional theory supported by Habbured parameter (DFT+U). Structural analysis demonstrates that the recorded lattice constants is in good coherence with the previously published results. For the lattice parameters, contraction by 1.33% comparing with the host system has been reported. Furthermore, the doping effect of TM on the band gap leads to its reduction in the resulting Hf0.75TM0.25O2 configurations. The partial density of states (PDOS) indicate that hybridization through localized electroni

Diabetes is a disease caused by high sugar levels. Currently, diabetes is one of the most common diseases in the number of people with diabetes worldwide. The increase in diabetes is caused by the delay in establishing the diagnosis of the disease. Therefore, an initial action is needed as a solution that requires the most appropriate and accurate data mining to manage diabetes mellitus. The algorithms used are artificial neural network algorithms, namely Restricted Boltzmann Machine and Backpropagation. This research aims to compare the two algorithms to find which algorithm can produce high accuracy, and determine which algorithm is more accurate in detecting diabetes mellitus. Several stages were involved in this research, including d