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A Decision Tree-Aware Genetic Algorithm for Botnet Detection
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     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from the whole features set. Thus, it obtains efficient botnet detection results in terms of F-score, precision, detection rate, and  number of relevant features, when compared with DT alone.

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Publication Date
Sat Jun 25 2022
Journal Name
International Journal Of Drug Delivery Technology
Preparation of Posaconazole Nanosponges for Improved Topical Delivery System
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The objective of the current research was to develop the posaconazole (PCZ) loaded NS into the carbopol 934 polymeric gel for prolonged drug release and improved topical delivery; seven different nanosponge formulations of PCZ were formulated using the emulsion solvent diffusion method using various amounts of polymer (ethylcellulose, EC). The aqueous and dispersed phases were prepared using polyvinyl alcohol (PVA) and dichloromethane. The prepared nanosponges (NS) were studied for particle size, structural appearance, and in vitro drug release. Furthermore, the selected formula was formulated as hydrogel and was evaluated for physical characteristics, drug content, and in-vitro drug release. Morphological studies revealed irregular

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Estimation of (S-S) reliability for inverted exponential distribution
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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Interdisciplinary Mathematics
Study on approximate analytical methods for nonlinear differential equations
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In this work, an analytical approximation solution is presented, as well as a comparison of the Variational Iteration Adomian Decomposition Method (VIADM) and the Modified Sumudu Transform Adomian Decomposition Method (M STADM), both of which are capable of solving nonlinear partial differential equations (NPDEs) such as nonhomogeneous Kertewege-de Vries (kdv) problems and the nonlinear Klein-Gordon. The results demonstrate the solution’s dependability and excellent accuracy.

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Vertical Stress Prediction for Zubair Oil Field/ Case Study
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Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods

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Publication Date
Thu Aug 13 2020
Journal Name
Journal Of Imaging
On Computational Aspects of Krawtchouk Polynomials for High Orders
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Discrete Krawtchouk polynomials are widely utilized in different fields for their remarkable characteristics, specifically, the localization property. Discrete orthogonal moments are utilized as a feature descriptor for images and video frames in computer vision applications. In this paper, we present a new method for computing discrete Krawtchouk polynomial coefficients swiftly and efficiently. The presented method proposes a new initial value that does not tend to be zero as the polynomial size increases. In addition, a combination of the existing recurrence relations is presented which are in the n- and x-directions. The utilized recurrence relations are developed to reduce the computational cost. The proposed method computes app

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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Optical properties for prepared polyvinyl alcohol/ polyaniline/ ZnO nanocomposites
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The optical energy gap and optical constants such as the reflective index, dielectric constant have been evaluated due to The optical transmission and UV-VIS absorption spectra have been recorded in the wavelength (200 - 1100 nm) for PVA/PANI polymer blends and PVA/PANI/ZnO nanocomposites with different concentrations of ZnO (0.02, 0.05, 0.07, 0.1and 0.2) wt %. The results indicate that the materials have allowed direct transition. The reflection index and dielectric constant are increase with wavelength

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
The Operational Matrices Methods for Solving Falkner-Skan Equations
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     The method of operational matrices is based on the Bernoulli and Shifted Legendre polynomials which is used to solve the Falkner-Skan equation. The nonlinear differential equation converting to a system of nonlinear equations is solved using Mathematica®12, and the approximate solutions are obtained. The efficiency of these methods was studied by calculating the maximum error remainder ( ), and it was found that their efficiency increases as  increases. Moreover, the obtained approximate solutions are compared with the numerical solution obtained by the fourth-order Runge-Kutta method (RK4), which gives  a good agreement.

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Publication Date
Fri Jun 06 2025
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
Some parameters for the resize graph of G2(4)
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Topological indices provide important insights into the structural characteristics of molecular graphs. The present investigation proposes and explores a creative graph on a finite group G, which is known as the RIG. This graph is designated as ΓRS G2(4) indicating a simple undirected graph containing elements of G. Two distinct ertices are regarded as nearly the same if and only if their sum yields a non-trivial involution element in G. RIGs have been discovered in various finite groups. We examine several facets of the RIG by altering the graph through the conjugacy classes of G. Furthermore, we investigate the topological indices as applications in graph theory applying the distance matrix of the G2(4) group.

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Publication Date
Fri Jul 19 2019
Journal Name
Iraqi Journal Of Science
Efficient Iterative Method for Solving Korteweg-de Vries Equations
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The Korteweg-de Vries equation plays an important role in fluid physics and applied mathematics. This equation is a fundamental within study of shallow water waves. Since these equations arise in many applications and physical phenomena, it is officially showed that this equation has solitary waves as solutions, The Korteweg-de Vries equation is utilized to characterize a long waves travelling in channels. The goal of this paper is to construct the new effective frequent relation to resolve these problems where the semi analytic iterative technique presents new enforcement to solve Korteweg-de Vries equations. The distinctive feature of this method is, it can be utilized to get approximate solutions for travelling waves of 

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Compression-based Data Reduction Technique for IoT Sensor Networks
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Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

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