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A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a new RNA encoding method and ResNet50 Model, where the encoding is done by splitting the training records into different groups. These groups are protocol, service, flag, and digit, and each group is represented by the number of RNA characters that can represent the group's values. The RNA encoding phase converts network traffic records into RNA sequences, allowing for a comprehensive representation of the dataset. The detection model, utilizing the ResNet architecture, effectively tackles training challenges and achieves high detection rates for different attack types. The KDD-Cup99 Dataset is used for both training and testing. The testing dataset includes new attacks that do not appear in the training dataset, which means the system can detect new attacks in the future. The efficiency of the suggested anomaly intrusion detection system is done by calculating the detection rate (DR), false alarm rate (FAR), and accuracy. The achieved DR, FAR, and accuracy are equal to 96.24%, 6.133%, and 95.99%. The experimental results exhibit that the RNA encoding method can improve intrusion detection.

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Semi parametric Estimators for Quantile Model via LASSO and SCAD with Missing Data
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In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

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Publication Date
Mon Aug 21 2023
Journal Name
Communications In Mathematical Biology And Neuroscience
Delay in eco-epidemiological prey-predator model with predation fear and hunting cooperation
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It is recognized that organisms live and interact in groups, exposing them to various elements like disease, fear, hunting cooperation, and others. As a result, in this paper, we adopted the construction of a mathematical model that describes the interaction of the prey with the predator when there is an infectious disease, as well as the predator community's characteristic of cooperation in hunting, which generates great fear in the prey community. Furthermore, the presence of an incubation period for the disease provides a delay in disease transmission from diseased predators to healthy predators. This research aims to examine the proposed mathematical model's solution behavior to better understand these elements' impact on an eco-epidemi

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Publication Date
Sat Jul 05 2025
Journal Name
Journal Of Machine And Computing
Cyber Neutrosophic Model for Secure and Uncertainty Aware Evaluation in Indoor Design Projects
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To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

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Publication Date
Fri Mar 28 2014
Journal Name
Advances In Life Science And Technology
Synthesis and Characterization of Novel Schiff Bases, N-Acyl and Diazetines Derived from 3-((5-hydrazinyl-4-phenyl-4H-1,2,4- triazol-3-yl)methyl)-1H-indole
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This work involves synthesis of some new heterocyclic compounds including 1, 3-diazetine. The new Schiff bases [VI] ad derived from 3-((5-hydrazinyl-4-phenyl-4H-1, 2, 4-triazol-3-yl) methyl)-1H-indole [V] which was synthesized by refluxing 5-((1H-indol-3-yl) methyl)-4-phenyl-4H-1, 2, 4-triazole-3-thiol [IV] with hydrazine hydrate in absolute ethanol and this amino compound [V] condensation with different aromatic aldehydes in absolute ethanol to yielded a new Schiff bases [VI] ad. N-acyl compounds [VII] ad were synthesized by addition reaction of acetyl chloride to imine group of Schiff bases in dry benzene. The new diazetine derivatives [VIII] ad synthesized by the reaction of N-acyl compounds [VII] ad with sodium azide in dimethylformamid

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Determination of Sulfacetamide Sodium in Pure and Their Pharmaceutical Formulations by Using Cloud Point Extraction Method
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      In this study, simple, low cost, precise and speed spectrophotometric methods development for evaluation of sulfacetamide sodium are described. The primary approach contains conversion of sulfacetamide sodium to diazonium salt followed by a reaction with p-cresol as a reagent in the alkaline media.  The colored product has an orange colour with absorbance at λmax 450 nm. At the concentration range of (5.0-100 µg.mL-1), the Beer̆ s Low is obeyed with correlation coefficient (R2= 0.9996), limit of detection as 0.2142 µg.mL-1, limit of quantification as 0.707 µg.mL-1 and molar absorptivity as 1488.249 L.mol-1.cm-1. The other approach, cloud point extraction w

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Publication Date
Mon Jun 22 2020
Journal Name
Baghdad Science Journal
Splitting the One-Dimensional Wave Equation. Part I: Solving by Finite-Difference Method and Separation Variables
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In this study, an unknown force function dependent on the space in the wave equation is investigated. Numerically wave equation splitting in two parts, part one using the finite-difference method (FDM). Part two using separating variables method. This is the continuation and changing technique for solving inverse problem part in (1,2). Instead, the boundary element method (BEM) in (1,2), the finite-difference method (FDM) has applied. Boundary data are in the role of overdetermination data. The second part of the problem is inverse and ill-posed, since small errors in the extra boundary data cause errors in the force solution. Zeroth order of Tikhonov regularization, and several parameters of regularization are employed to decrease error

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Publication Date
Fri Oct 01 2010
Journal Name
2010 Ieee Symposium On Industrial Electronics And Applications (isiea)
Distributed t-way test suite data generation using exhaustive search method with map and reduce framework
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Publication Date
Wed Feb 01 2012
Journal Name
Ibn Al-haytham Journal For Pure And Applied Science
Using Restricted Least Squares Method to Estimate and Analyze the Cobb-Douglas Production Function with Applicatio
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Publication Date
Tue Nov 01 2022
Journal Name
Chemical Methodologies
Study of Optical and Structural Properties of CdTe Quantum Dots Capped with 3MPA Using Hydrothermal Method
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Quantum dots (QDs) can be defined as nanoparticles (NPs) in which the movement of charge carriers is restricted in all directions. CdTe QDs are one of the most important semiconducting crystals among other various types where it has a direct energy gap of about 1.53 eV. The aim of this study is to exaine the optical and structural properties of the 3MPA capped CdTe QDs. The preparation method was based on the work of Ncapayi et al. for preparing 3MPA CdTe QDs, and hen, the same way was treated as by Ahmed et al. via hydrothermal method by using an autoclave at the same temperature but at a different reaction time. The direct optical energy gap of CdTe QDs is between 2.29 eV and 2.50 eV. The FTIR results confirmed the covalent bonding betwee

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