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A New Intrusion Detection Approach Based on RNA Encoding and K-Means Clustering Algorithm Using KDD-Cup99 Dataset
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Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the disadvantages of these two methods. In this paper, a new hybrid IDS is proposed based on the RNA encoding idea and applying the K-means clustering algorithm. Firstly, choosing random records for both training and testing. Secondly, propose RNA encoding by calculating all possible record values within dataset and generating RNA characters for each value, then dividing it into blocks. The third step is done by searching and extracting normal keys based on the most repeated blocks, and the same procedure is applied to extract the attack keys. Finally, the Kmeans clustering method is used to classify the testing records based on extracted keys. The proposed method is evaluated by calculating the detection rate (DR), false alarm rate (FAR), and accuracy, where the achieved DR, FAR, and accuracy are equal to 91.13%, 0.46%, and 92.02% respectively. Based on the achieved results, it can be said that the proposed hybrid IDS has high DR and accuracy results, can detect new attacks, and can solve the problem of anomaly IDS by getting a low false alarm rate result.

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Publication Date
Wed Dec 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
Online medical consultation: covid-19 system using software object-oriented approach
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The internet has been a source of medical information, it has been used for online medical consultation (OMC). OMC is now offered by many providers internationally with diverse models and features. In OMC, consultations and treatments are available 24/7. The covid-19 pandemic across-the-board, many people unable to go to hospital or clinic because the spread of the virus. This paper tried to answer two research questions. The first one on how the OMC can help the patients during covid-19 pandemic. A literature review was conducted to answer the first research question. The second one on how to develop system in OMC related to covid-19 pandemic. The system was developed by Visual Studio 2019 using software object-oriented approach. O

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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Publication Date
Sat Feb 01 2025
Journal Name
Algorithms
Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
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Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Parametric Nonlinear Programming Approach with Fuzzy Queues Using Hexagonal Membership Functions
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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
Proposed Framework for Semantic Segmentation of Aerial Hyperspectral Images Using Deep Learning and SVM Approach
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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of The College Of Languages (jcl)
Investigating English Composition Writing Problems Encountered by Preparatory School Students and Finding Solutions to These Problems through Schema- Based Approach
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Writing in English is one of the essential factors for successful                      EFL learning .Iraqi students at the preparatory schools encounter problems when using their background knowledge in handling subskills                                  of writing(Burhan,2013:164).Therefore, this study aims to investigate the 4thyear preparatory school students’ problems in English composition writing, and find solutions to these pro

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Engineering
Valuation of Construction Projects Based on of Quantity Scale by using Expert System
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The subject of an valuation of quality of construction projects is one of the topics which it becomes necessary of the absence of the quantity standards in measuring the control works and the quality valuation standards in constructional projects. In the time being it depends on the experience of the workers which leads to an apparent differences in the valuation.

The idea of this research came to put the standards to evaluate the quality of the projects in a special system depending on quantity scale nor quality specifying in order to prepare an expert system “ Crystal “ to apply this special system to able the engineers to valuate the quality of their projects easily and in more accurate ways.

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Publication Date
Sun Jun 07 2026
Journal Name
Sciences Journal Of Physical Education
Use different means rehabilitative according some bio-kinematics variables and their impact on increasing range of motion for people with shoulder joint
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Publication Date
Fri Jun 30 2023
Journal Name
Samarra Journal Of Pure And Applied Science
New Ligand-Based Metal Complexes: Synthesis, Spectroscopic Characterization, Thermal Behavior, Anticancer Properties, and Biological Activity
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New ligands, N1, N4-bis (benzo[d]thiazol-2- ylcarbamothioyl) succinamide (L1) and N1, N4- bis (benzylcarbamothioyl)succinamide (L2), derived from succinyl chloride and 2-amino benzothiazole or benzylamine, respectively, have been used to prepare a set of transition metal complexes with the general formula [M2(L)Cl4], where L=L1 or L2, M = Mn(II), Ni(II), Cu(II), Cd(II), Co(II), Zn(II) or Hg(II). The synthesized compounds were characterized using various analytical techniques including TGA, 13C NMR, mass spectroscopy, 1H and Fourier-transform infrared (FTIR) spectroscopy, magnetic measurement, molar conductivity, electronic spectrum, (%M, %C, %H, %N) and atomic absorption flame (AAF) analysis. The results showed that (L1, L2) bin

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Publication Date
Wed Mar 01 2023
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Design and implementation monitoring robotic system based on you only look once model using deep learning technique
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<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in

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