Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

A sensitivity-turbidimetric method at (0-180^o) was used for detⁿ. of mebeverine in drugs by two solar cell and six source  with C.F.I.A.. The method was based on the formation  of  ion pair for the pinkish banana color  precipitate by the reaction of Mebeverine hydrochloride with Phosphotungstic acid. Turbidity was measured via the reflection of incident light that collides on the surface particles of   precipitated at 0-180^o. All variables were optimized. The linearity ranged of Mebeverine hydrochloride was 0.05-12.5mmol.L^-1, the L.D. (S/N= 3)(3S_B) was 521.92 ng/sample depending on dilution for the minimum concentration , with correlation coefficient r = 0.9966while was R.S.D%

The Inhbititory effect of cocentrated and non-cocentrated supernatant of the probiotic Lactobacillus salivarius against growth of some potential pathogenic microorganisms which included Pseudomonas eruginosa, Klebsiella spp, Escherichia coli and Candida albicans. The results were diffusion assay revealed that concentrated and non-concentrated supernatant had inhitory effect against pathogenic bacteria with inhibition zone renged between 13-17mm while inhibition effect of concentrated supernatant against C.albicans was inhibition zone 8mm. On the other hand, the effect of these suprnatant against biofilm formation of the tested microorganisms was studied. The result showed that the concentrated supernatant had inhibitory effect on biofil

The genus Ziziphus is one of the Family Rhamnaceae and consists of more than 170 species distributed in tropical and subtropical regions. All the species in the genus are of economical and medical importance. This study was conducted to identify the morphologically and anatomically features of the genus in Iraq.  The field survey was conducted across the study area where 4 species (Ziziphus jujube, Z. mauritiana, Z. nummularia and Z. spina-christi) were collected and used in the study.  The result showed that there is variation in morphological and anatomical features among the species in the stem cross-section and longitudinal section of leaves also the differences appeared in the epidermis of leaves.

This investigation showed (31) species belonging to (15) genera under (five) families and two orders. The leafminers Dipter families (Agromozidae, Anthomyiidae, Drosophilidae), Agromyzid flies is the highest level of investigated many host plants, but other families have lowest host plants. The synonyms of species were provided from GBIF scarlet's. The date and localities of sampling collection were recorded.