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Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusion Detection System (IDS). Success is measured by a variety of metrics, including accuracy, precision, recall, F1-Score, and execution time. Applying feature selection approaches such as Analysis of Variance (ANOVA), Mutual Information (MI), and Chi-Square (Ch-2) reduced execution time, increased detection efficiency and accuracy, and boosted overall performance. All classifiers achieve the greatest performance with 99.99% accuracy and the shortest computation time of 0.0089 seconds while using ANOVA with 10% of features.

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Publication Date
Thu Aug 01 2024
Journal Name
Al-kindy College Medical Journal
Through the Eyes of Healthcare Providers, the Necessity and Challenges of Implementing Medication Reconciliation at Hospital Discharge: A Qualitative Study
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Background: Medication reconciliation can include medication reviewing and providing counseling and a list of all the medications during every transition of care. Objectives: to explore in-depth the perspectives of Iraqi physicians and pharmacists regarding the necessity of medication reconciliation at hospital discharge and identify the possible benefits and challenges that could face its implementation. Subjects and Methods: A qualitative study included semi-structured interviews with pharmacists and physicians working at a public teaching hospital in Iraq. The interviews were conducted face-to-face from February to March 2023. Thematic analysis was used to analyze the qualitative data generated from the interviews. Results: In th

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Publication Date
Mon Jan 01 2024
Journal Name
The Scientific World Journal
Efficient Removal of Brilliant Green Dye Using Mesoporous Attapulgite Clay: Investigating Adsorption Kinetics, Isotherms, and Mechanisms
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The study involved the effectiveness of Iraqi attapulgite (IQATP) clay as an environmentally friendly material that easily adsorbs brilliant green (BG) dye from water systems and is identified by various complementary methods (e.g., FTIR, SEM‐EDS, XRD, ICP‐OES, pHpzc, and BET), where the result reported that the IQATP specific surface area is 29.15 m2/g. A systematic analysis was selected to evaluate the impact of different effective adsorption performance variables on BG dye decontamination. These variables included IQATP dosage (0.02–0.8 g/L), solution pH (3.05–8.15), contact time (ranging from 2 to 25 min), and initial BG dye concentration from 20 to 80 mg/L. The parameter

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Publication Date
Sat Aug 30 2025
Journal Name
Iraqi Journal Of Science
A Face Mask Detection Method in the Era of the COVID-19 Pandemic Based on GLCM and YOLO
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In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

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Publication Date
Thu Nov 17 2016
Journal Name
Plos One
Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network
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Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destina

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Publication Date
Wed May 01 2019
Journal Name
Journal Of Engineering
Theoretical Analysis of Seepage through Homogeneous and Non-homogeneous Saturated-Unsaturated Soil
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In this research, the program SEEP / W was used to compute the value of seepage through the homogenous and non-homogeneous earth dam with known dimensions. The results show that the relationship between the seepage and water height in upstream of the dam to its length for saturated soil was nonlinear when the dam is homogenous. For the non-homogeneous dam, the relationship was linear and the amount of seepage increase with the height of water in upstream to its length. Also the quantity of seepage was calculated using the method of (Fredlund and Xing, 1994) and (Van Genuchten, 1980) when the soil is saturated – unsaturated, the results referred to that the higher value of seepage when the soil is saturated and the lowe

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Publication Date
Thu Oct 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Theoretical and Practical Investigation of Blood Flow through Stenosed Coronary Lad Artery
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Atherosclerosis is the most common causes of vascular diseases and it is associated with a restriction in the lumen of blood vessels. So; the study of blood flow in arteries is very important to understand the relation between hemodynamic characteristics of blood flow and the occurrence of atherosclerosis.

looking for the physical factors and correlations that explain the phenomena of existence the atherosclerosis disease in the proximal site of LAD artery in some people rather than others is achieved in this study by analysis data from coronary angiography as well as estimating the blood velocity from coronary angiography scans without having a required data on velocity by using some mathematical equations and physical laws. Fif

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Engineering
Practical comparation of the accuracy and speed of YOLO, SSD and Faster RCNN for drone detection
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

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Publication Date
Fri Oct 01 2021
Monitoring and controlling the speed and direction of a DC motor through FPGA and comparison of FPGA for speed and performance optimization
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<span lang="EN-US">We are living in the 21<sup>st</sup> century, an era of acquiring necessity in one click. As we, all know that technology is continuously reviving to stay ahead of advancements taking place in this world of making things easier for mankind. Technology has been putting his part in introducing different projects as we have used the field programmable gate arrays (FPGAs) development board of low cost and programmable logic done by the new evolvable cyclone software is optimized for specific energy based on Altera Cyclone II (EP2C5T144) through which we can control the speed of any electronic device or any Motor Control IP product targeted for the fan and pump. Altera Cyclone FPGAs’ is a board thro

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Comparison for estimation methods for the autoregressive approximations
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Abstract

      In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min

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Publication Date
Sun Jun 01 2025
Journal Name
Irish Journal Of Medical Science (1971 -)
Enhanced diagnostic accuracy of type 1 diabetes mellitus through the combined use of serum β-catenin and HbA1c
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