Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

The current research aims to identify the problems and needs for both college of political science and college of engineering’s students. The sample was (100) male and female student. The results showed bunch of problems which could be organized descendingly, the scientific domain ranged between (2 - 2.42), the mean of the psychological domain was (2.85), the moral domain ranged between (2.2 – 2.28)m the problems of study earned (2.30), the material domain got (1.95), the medical and social domain obtained (1.925), and finally, the family domain received (1.887).

To verify the influence of magnetic flux on the characteristics of SAE 10W-30 gasoline engine oil when the engine oil is exposed to different magnetic fluxes 0, 6, 9, and 13 Volt. The following oil characteristics were measured: viscosity at 40 and 100 °C, and total acid number (TAN) mg KOH/g. The research was carried out in a completely randomized design with three replications for each treatment under the 5% probability level to compare the means of the treatments. The results of the experiment showed that there were significant differences in the studied properties when the engine oil was exposed to the above magnetic fluxes and, inversely, especially the magnetic flux of 13 Volt, which led to a decrease in the viscosity of the oils at

   Asphaltenes are a solubility class described as a component of crude oil with undesired characteristics. In this study, Sharqy Baghdad heavy oil upgrading was achieved utilizing the solvent deasphalting approach as asphaltenes are insoluble in paraffinic solvents; they may be removed from heavy crude oil by adding N-Hexane as a solvent to create deasphalted oil (DAO)of higher quality. This method is known as Solvent De-asphalting (SDA). Different effects have been assessed for the SDA process, such as solvent to oil ratio (4-16/1 ml/g), the extraction temperature (23 ºC) room temperature and (68 ºC) reflux temperature at (0.5 h mixing time with 400 rpm mixing speed). The best solvent deasphalting results were obtained at room temp

The study focused on the identification of the natural relation between the organizational components, and the most important is the organizational structure, which not hid its effect on each function and operation of the organizational structure through commanding the individual craters and its forms according to the requirement of these function, also it has relation with an organic synthesis that between the dimensions of the organic synthesis and the practice side in the commission of Integrity.

The problem of the research pensioned in some questions about hypothesis and theoretical parts, in which they go a mention about the hypothesis questions is to use all the knowledge's in this atmosphere and th

Background: techniques of image analysis have been used extensively to minimize interobserver variation of immunohistochemical scoring, yet; image acquisition procedures are often demanding, expensive and laborious. This study aims to assess the validity of image analysis to predict human observer’s score with a simplified image acquisition technique. Materials and methods: formalin fixed- paraffin embedded tissue sections for ameloblastomas and basal cell carcinomas were immunohistochemically stained with monoclonal antibodies to MMP-2 and MMP-9. The extent of antibody positivity was quantified using Imagej® based application on low power photomicrographs obtained with a conventional camera. Results of the software were employed

The objective of this study was to progress another method for coagulation/flocculation of the microalga Chlorella vulgaris via pellet-forming of the fungal species Aspergillus niger which was isolated from municipal wastewater mud and the facultative heterotrophic microalga "C.vulgaris was used. The main factors studies were spore inoculums, organic carbon concentration in medium as well as pH variation which had considerably positive effects on microalgae/fungi co-pelletization formation. The process parameters are an inoculum1×104 spores/ML, 15 g/l sucrose as carbon source and pH ranged from 5 - 7.0 were found optimal for efficient microalgae/fungi co-pelletization formation. For autotrophic growth, when pH of culture broth was adjusted