Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

        Educational services in Iraq face many problems that have reduced the efficiency of the educational process, as a result of the difficult conditions experienced by educational services in Iraq. This led to the accumulation of these problems and their exacerbation significantly over the years, as there was no fundamental solution to these problems. The study proposes a planning method for managing the educational system in Iraq, especially for the primary and secondary levels, where these negative phenomena are very prominent, especially the deficit in school buildings and the phenomenon of overcrowding in classrooms.      &am

     The searching process using a binary codebook of combined Block Truncation Coding (BTC) method and Vector Quantization (VQ), i.e. a full codebook search for each input image vector to find the best matched code word in the codebook, requires a long time.   Therefore, in this paper, after designing a small binary codebook, we adopted a new method by rotating each binary code word in this codebook into 900 to 2700 step 900 directions. Then, we systematized each code word depending on its angle  to involve four types of binary code books (i.e. Pour when , Flat when  , Vertical when, or Zigzag). The proposed scheme was used for decreasing the time of the coding procedure, with very small distortion per block, by designing s

The effect of using three different interpolation methods (nearest neighbour, linear and non-linear) on a 3D sinogram to restore the missing data due to using angular difference greater than 1° (considered as optimum 3D sinogram) is presented. Two reconstruction methods are adopted in this study, the back-projection method and Fourier slice theorem method, from the results the second reconstruction proven to be a promising reconstruction with the linear interpolation method when the angular difference is less than 20°.

FG Mohammed, HM Al-Dabbas, Iraqi journal of science, 2018 - Cited by 6

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Cadmium has been known to be harmful to human healthy , manily Via contaminated drinking water , food supplies , tobacco and industrial pollutant . The aim of this study was to determine the toxicity of new Cadmium (II) complex ( Bis[ 5- ( P- nitrophenyl ) – ? 4 – Phenyl- 1,2,4- triazole -3- dithiocarbamatohydrazide] cadmium (II) Hydra ( 0.5) and compare it with anticancer drug cyclophosphamide ( CP) in female albino mice . This complex causes to several alterations in Enzymatic activity of Glutamate Pyruvate Transaminase (GPT) and Alkaline Phosphatase (ALP ) in three organs after the treatment of mice with different doses of a new cadmium (II) complex ( 0.09 / 0.25ml , 0.18/ 0.5ml and 0.25mg /0.7 ml /30 gm of mous

In this article, new Schiff base ligand LH-prepared Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), Hg(II), Pd(II), and Pt(II) materials were analyzed using spectroscopy (1 Metal: 2 LH). The ligand was identified using techniques such as FTIR, UV-vis, 1H-13C-NMR, and mass spectra, and their complexes were identified using CHN microanalysis, UV-vis and FTIR spectral studies, atomic absorption, chloride content, molar conductivity measurements, and magnetic susceptibility. According to the measurements, the ligand was bound to the divalent metal ions as a bidentate through oxygen and nitrogen atoms. The complexes that were created had microbicide activity against two different bacterial species and one type of fungus. DPPH techniques were bei

New heterocyclic compounds derived from 2-Morpholino-1,8-naphthyridine-4-carboxylic acid such as oxadiazolo, thiadiazolo – thione and triazolo-thione have been prepared and characterized on the basis of IR and 1H NMR spectra data. The hydrizide compound was utilized as a starting material for preparing of these compounds. The second part of this study involves the biological studies of some of these naphthyridine derivatives by using three different kinds of bacteria namely: Staphylococcus aureus, Pseudomonas aeruglnosa and Escherichia coli. The data indicated that some of these compounds have a good activity against the tested bacteria in comparison to antibiotics.