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joe-2223
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypted HTTP subset traffic of DARPA 1999 data set, from 55.234% in the PAYL system alone to 99.94% in the proposed system; due to the existence of the neural network self-organizing map (SOM). In addition SOM decreases the ratio of false positive from 44.676% in the PAYL system alone to 5.176% in the proposed system. The proposed system provides 80% detection ability of smart worms that are meant to invade the PAYL detector in the PAYL system alone, due to the existence of the randomization stage in the proposed system.

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Publication Date
Fri Jan 01 2021
Journal Name
Clinical Epidemiology And Global Health
Association of overweight/obesity with the severity of periodontitis using BPE code in an iraqi population
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Publication Date
Sun Jun 23 2019
Journal Name
American Rock Mechanics Association
Using an Analytical Model to Predict Collapse Volume During Drilling: A Case Study from Southern Iraq
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Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assump

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
A new smart approach of an efficient energy consumption management by using a machine-learning technique
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Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

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Publication Date
Tue Jan 01 2019
Journal Name
The 53rd U.s. Rock Mechanics/geomechanics Symposium
Using an analytical model to predict collapse volume during drilling: A case study from southern Iraq
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Publication Date
Wed Sep 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
The Usefulness of Mandibular Ramus as an Indicator in Sex Differentiation Using 3D Reconstructed Computed Tomography
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Background: Determination of sex from an unknown human bone is an important role in forensic and anthropology field. The mandible is the largest and hardest facial bone, that commonly resist postmortem damage and forms an important source of information about sexual dimorphism. Mandibular ramus can be used to differentiate between sexes and it also expresses strong univariate sexual dimorphism. This study was undertaken to assess the usefulness of mandibular ramus as an aid in sex differentiation using CT scanning among Iraqi population. Materials and methods: 3D reconstructed computed tomography scanning of 140 Iraqi Arab subjects, (7 0 males and 70 females) were analyzed with their age range from 20-60 years old. The linear measurements w

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
The Impact of Black Marketing on Purchasing Decisions: An Exploratory Study Using AI-Driven Analytical Tools
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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Prediction of pore and fracture pressure using well logs in Mishrif reservoir in an Iraqi oilfield
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Publication Date
Sun Apr 13 2025
Journal Name
Scientific Reports
Optimized image segmentation using an improved reptile search algorithm with Gbest operator for multi-level thresholding
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Abstract<p>Image segmentation using bi-level thresholds works well for straightforward scenarios; however, dealing with complex images that contain multiple objects or colors presents considerable computational difficulties. Multi-level thresholding is crucial for these situations, but it also introduces a challenging optimization problem. This paper presents an improved Reptile Search Algorithm (RSA) that includes a Gbest operator to enhance its performance. The proposed method determines optimal threshold values for both grayscale and color images, utilizing entropy-based objective functions derived from the Otsu and Kapur techniques. Experiments were carried out on 16 benchmark images, which inclu</p> ... Show More
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Publication Date
Tue Nov 01 2022
Journal Name
Isa Transactions
Robust adaptive active disturbance rejection control of an electric furnace using additional continuous sliding mode component
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The temperature control process of electric heating furnace (EHF) systems is a quite difficult and changeable task owing to non-linearity, time delay, time-varying parameters, and the harsh environment of the furnace. In this paper, a robust temperature control scheme for an EHF system is developed using an adaptive active disturbance rejection control (AADRC) technique with a continuous sliding-mode based component. First, a comprehensive dynamic model is established by using convection laws, in which the EHF systems can be characterized as an uncertain second order system. Second, an adaptive extended state observer (AESO) is utilized to estimate the states of the EHF system and total disturbances, in which the observer gains are updated

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Publication Date
Fri Apr 23 2021
Journal Name
International Journal Of Environmental Analytical Chemistry
Removal of levofloxacin and ciprofloxacin from aqueous solutions and an economic evaluation using the electrocoagulation process‏
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For this research, the utilisation of electrocoagulation (EC) toremove theciprofloxacin (CIP) and levofloxacin (LVX) from aqueous solutions was examined. The effective removal efficiencies are 93.47% for CIP and 88.00% for LVX, under optimum conditions. The adsorption isotherm models with suitable mechanisms were applied to determine the elimination of CIP and LVX utilizingtheEC method. Thefindingsshowed the adsorption of CIP and LVX on iron hydroxide flocs followed the Sips isotherm, with correlation coefficient values (R2) of 0.939 and 0.937. Threekinetic models were reviewed to determine the accurate CIP and LVX elimination methods using the EC method. The results showed that itfittedfor the second-order model, which indicated that the c

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