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

Modern machine-learning applications require GPUs, and modern platforms can leverage numerous GPUs on one or more machines to increase performance. Contemporary deep-learning models are too huge for CPU or GPU training. Training these models with many GPUs without performance degradation is necessary to train them rapidly and maximize GPU consumption. Thus, training deep convolutional neural networks (DCNN) with multiple GPUs has become necessary for improving training. Therefore, we presented a parallel design and development of an efficient model for enhancing face mask CNN performance and improving resource efficiency. This DCNN model is a parallel training system over multiple GPUs, a multi-core CPU, and a multi-process GPU platform wit

In this study, new derivatives of 3-C-spiro ring nucleoside analogues were synthesized. The structures of these derivatives were characterized by infrared spectroscopy,1 HNMR (some of them) and elemental analysis. The nucleoside derivatives were tested for inhibition of E-coli and were all found to be active.

This research deals with the qualitative and quantitative interpretation of Bouguer gravity anomaly data for a region located to the SW of Qa’im City within Anbar province by using 2D- mapping methods. The gravity residual field obtained graphically by subtracting the Regional Gravity values from the values of the total Bouguer anomaly. The residual gravity field processed in order to reduce noise by applying the gradient operator and 1st directional derivatives filtering. This was helpful in assigning the locations of sudden variation in Gravity values. Such variations may be produced by subsurface faults, fractures, cavities or subsurface facies lateral variations limits. A major fault was predicted to extend with the direction NE-

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

Copper is a cheaper alternative to various noble metals with a range of potential applications in the field of nanoscience and nanotechnology. However, copper nanoparticles have major limitations, which include rapid oxidation on exposure to air. Therefore, alternative pathways have been developed to synthesize metal nanoparticles in the presence of polymers and surfactants as stabilizers, and to form coatings on the surface of nanoparticles. These surfactants and polymeric ligands are made from petrochemicals which are non- renewable. As fossil resources are limited, finding renewable and biodegradable alternative is promising.The study aimed at preparing, characterizing and evaluating the antibacterial properties of copper nanoparticle

Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce

Background: Cutaneous leishmaniasis (CL) is a neglected disease in tropical countries, including Iraq. Several studies have sought to examine chemotherapies for leishmaniasis treatment but most of them are of toxic and/or undesirable side effect, therefore, the need for investigating new fewer toxic therapies is essential. Aim of study: In this study, the cytotoxic effect of Artemisinin (ART), a novel herbal compound, was screened against the two forms, promastigotes and amastigotes, of the Iraqi isolate of Leishmania tropica, the causative agent of Baghdad boil. Material and methods:  Different concentrations (1000, 500, 250, 125, 62.5, 31.25, 15.6 and 7.8) µM of Artemisinin were screened to investigate the leishmanic

Background: Cutaneous leishmaniasis (CL) is a neglected disease in tropical countries, including Iraq. Several studies have sought to examine chemotherapies for leishmaniasis treatment but most of them are of toxic and/or undesirable side effect, therefore, the need for investigating new fewer toxic therapies is essential. Aim of study: In this study, the cytotoxic effect of Artemisinin (ART), a novel herbal compound, was screened against the two forms, promastigotes and amastigotes, of the Iraqi isolate of Leishmania tropica, the causative agent of Baghdad boil. Material and methods: Different concentrations (1000, 500, 250, 125, 62.5, 31.25, 15.6 and 7.8) µM of Artemisinin were screened to investigate the leishmanicidal activity of th