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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
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Fri Jul 12 2024
Journal Name
International Journal Of Advances In Scientific Research And Engineering (ijasre), Issn:2454-8006, Doi: 10.31695/ijasre
A Proposed Blockchain-Based Digital-Identity Management using ERC 725/735
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In modern technology, the ownership of electronic data is the key to securing their privacy and identity from any trace or interference. Therefore, a new identity management system called Digital Identity Management, implemented throughout recent years, acts as a holder of the identity data to maintain the holder’s privacy and prevent identity theft. Therefore, an overwhelming number of users have two major problems, users who own data and third-party applications will handle it, and users who have no ownership of their data. Maintaining these identities will be a challenge these days. This paper proposes a system that solves the problem using blockchain technology for Digital Identity Management systems. Blockchain is a powerful techniqu

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Publication Date
Fri Apr 21 2023
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees22fr
Study of the x-ray diffraction lines of calcium titanate nanoparticle using SSP method and Scherrer method
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In this study, the modified size-strain plot (SSP) method was used to analyze the x-ray diffraction lines pattern of diffraction lines (1 0 1), (1 2 1), (2 0 2), (0 4 2), (2 4 2) for the calcium titanate(CaTiO3) nanoparticles, and to calculate lattice strain, crystallite size, stress, and energy density, using three models: uniform (USDM). With a lattice strain of (2.147201889), a stress of (0.267452615X10), and an energy density of (2.900651X10-3 KJ/m3), the crystallite was 32.29477611 nm in size, and to calculate lattice strain of Scherrer (4.1644598X10−3), and (1.509066023X10−6 KJ/m3), a stress of(6.403949183X10−4MPa) and (26.019894 nm).

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Solving Whitham-Broer-Kaup-Like Equations Numerically by using Hybrid Differential Transform Method and Finite Differences Method
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This paper aims to propose a hybrid approach of two powerful methods, namely the differential transform and finite difference methods, to obtain the solution of the coupled Whitham-Broer-Kaup-Like equations which arises in shallow-water wave theory. The capability of the method to such problems is verified by taking different parameters and initial conditions. The numerical simulations are depicted in 2D and 3D graphs. It is shown that the used approach returns accurate solutions for this type of problems in comparison with the analytic ones.

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Paleoclimatic Insights on the Paleocene-Eocene Thermal Maximum in Central Iraq, Based on Calcareous Nannofossils, Ostracoda and Geophysical Data
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    The Paleocene-Eocene Thermal Maximum (PETM) event, which represented a sudden and abnormal rise in temperature during the early Cenozoic Era, is regarded as one of the most important global geologic phenomena. Two important index microfossils (nannoplankton and Ostracoda) were utilised to understand and predict the paleoenvironment and describe the changes during this period. The basis of the study was 12 cutting samples taken from Aaliji and the lower part of Jaddala formations of a subsurface section of (Ba-8) borehole in central Iraq. Some geophysical data were used to determine the upper and lower contacts of the Aaliji Formation and define the shale rate in the studied formations. The micropaleontologic investigation reveals

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Rock facies classification and its effect on the estimation of original oil in place based on petrophysical properties data
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The most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
The Effects of Conductance on Metastable Switches in Memristive Devices Based on Anti-Hebbian and Hebbian (AHaH) Learning Rules
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     In the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each MMS rather t

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
The Effects of Conductance on Metastable Switches in Memristive Devices Based on Anti-Hebbian and Hebbian (AHaH) Learning Rules
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     In the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each M

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Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
Synthesis, Characterization and Quantum Chemical Studies of Inhibition Ability of Novel 5-Nitro Isatin Derivatives on The Corrosion of Carbon Steel in Sea Water
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This research includes synthesis of new 5-Nitro isatin derivatives starting from 5-Nitro-3-(ethyl imino acetate)-2-oxo indole (1) namely 5-nitro-3-[(imino acetyl) semicarbazide]-2-oxo indole (2); 5-nitro-3-[(imino acetyl) phenylsemicarbazide]-2-oxo indole (3); 5-nitro-3-[(imino acetyl) thiosemicarbazide]-2-oxo indole (4); 5-nitro-3-[(iminoacetyl) phenylthiosemi carbazide]-2-oxo indole (5); 5-nitro-3-[(methyl imino)-4H-1, 2, 4-triazol-5-ol-3-yl]-2-oxo indole (6); 5-nitro-3-[(methyl imino) 4-phenyl-1, 2, 4-triazol-5-ol-3-yl]-2-oxo indole (7); 5-nitro-3-[(methyl imino) 4-phenyl-1, 2, 4-triazol-5-thiol-3-yl]-2-oxo indole (8) and 5-nitro-3-[(methyl imino) 4H-1, 2, 4-triazol-5-thiol-3-yl]-2-oxo indole (9). The derivatives were characterized us

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Series Solutions of Delay Integral Equations via a Modified Approach of Homotopy Analysis Method
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In this paper, the series solutions of a non-linear delay integral equations are considered by a modified approach of homotopy analysis method (MAHAM). We split the function   into infinite sums. The outcomes of the illustrated examples are included to confirm the accuracy and efficiency of the MAHAM. The exact solution can be obtained using special values of the convergence parameter.

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