Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is openly accessible. It evaluates the performance of a complete arrangement of machine learning algorithms and network traffic features to indicate the best features for detecting the assured attack classes. Our goal is storing the address of destination IP that is utilized to detect an intruder by method of misuse detection.
Quercetin, one of the flavonoids family member, can be found in many vegetables, fruits, and beverages with a noticeable nutritional pharmacological properties. This study was aimed to evaluate the ability of quercetin to inhibit lipopolysaccharide (LPS) that induced lethal toxicity in vivo, and to elucidate the importance of the quercetin as an antitumor agent in breast cancer cell line MCF-7.In vivo experiments included the effect of hesperidin and LPS on the liver and spleen of male mice. In the liver, the antioxidant activity was measured by estimating the concentration of glutathione (GSH), and catalase (CAT), while in the spleen, the concentration of cytokines was measured including IL-33 and TNF-α. In vitro experiments included MTT
... Show MoreThis paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe
... Show MoreIn this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that
Background: Improved glucose level control with insulin injections have allowed for the diabetic population to live longer and healthier lives. Unfortunately diabetes remains a worldwide epidemic disease with multiple health implications. Specifically, its effects upon fracture healing are compromised in diabetics with as high as 87% recovery delay relative to “healthy†counterparts. Current medical treatments for bone injuries have been largely focused on replacing the lost bone with allogenic or autogenous bone grafts, beta-tricalcium phosphate (β -TCP), a ceramic alloplast, has interconnected system of micropores, has been widely used as a biologically safe osteoconductive bone substitute. The aim of this study was histol
... Show MoreIn the present paper a low cost mechanical vibration shaker of rotating unbalanced type with uniaxial shaking table was designed and constructed in an attempt to provide opportunities for experimental testing and application of vibration in experimental modal analysis, stress relief of weldments, effect of vibration on heat transfer and seismic testing of civil engineering structures. Also, it provides unexpressive solution to enhance the knowledge and technical skills of students in mechanical vibration laboratory. The shaker consists of a five main parts shaker frame, shaker table, flexible support, drive motor, and eccentricity mechanism. The experimental results show that the amplitude of the shaker is increased with increasing the f
... Show MoreInformation from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect
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