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bsj-2167
Developing an Immune Negative Selection Algorithm for Intrusion Detection in NSL-KDD data Set
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With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practical Experiments showed the process to achieve a high rate of detection in the system designer using data NSL-KDD with 12 field without vulnerability to change the radius of the detector or change the number of reagents were obtained as the ratio between detection (0.984, 0.998, 0.999) and the ratio between a false alarm (0.003, 0.002, 0.001). Contrary to the results of experiments conducted on data NSL-KDD with 41 field contact, which affected the rate of detection by changing the radius and the number of the detector as it has been to get the proportion of uncovered between (0.44, 0.824, 0.992) and the percentage of false alarm between (0.5, 0.175, 0.003).

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Publication Date
Fri Sep 02 2022
Journal Name
Frontiers In Built Environment
Thermal analysis of horizontal earth-air heat exchangers in a subtropical climate: An experimental study
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The earth-air heat exchanger (EHX) has a promising potential to passively save the energy consumption of traditional air conditioning systems while maintaining a high degree of indoor comfort. The use of EHX systems for air conditioning in commercial and industrial settings offers several environmental benefits and is capable of operating in both standalone and hybrid modes. This study tests the performance and effectiveness of an EHX design in a sandy soil area in Baghdad, Iraq. The area has a climate of the subtropical semi-humid type. Ambient air temperatures and soil temperatures were recorded throughout the months of 2021. During the months of January and June, the temperatures of the inlet and outflow air at varying air veloci

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Publication Date
Fri May 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Smart grid in the context of industry 4.0: an overview of communications technologies and challenges
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The recent advances in technology, the increased dependence on electrical energy and the emergence of the fourth industrial revolution (Industry 4.0) were all factors in the increased need for smart, efficient and reliable energy systems. This introduced the concept of the Smart Grid (SG). A SG is a potential replacement for older power grids, capable of adapting and distributing energy based on demand. SG systems are complex. They combine various components and have high requirements for real time reliable operation. This paper attempts to provide an overview of SG systems, by outlining SG architecture and various components. It also introduces communication technologies, integration and network management tools that are involved in SG sys

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Publication Date
Thu Sep 16 2021
Journal Name
International Journal Of Clinical Practice
An overview of post‐COVID‐19 complications
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Publication Date
Sun Sep 01 2019
Journal Name
Diabetes & Metabolic Syndrome: Clinical Research & Reviews
Rhabdomyolysis; is it an overlooked DKA complication
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Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Electrofacies Characterization of an Iraqi Carbonate Reservoir
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Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.

The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC

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Publication Date
Sun Mar 04 2018
Journal Name
Baghdad Science Journal
CVOTING: An Anonymous Ballot E-Voting System
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One of the concerns of adopting an e-voting systems in the pooling place of any critical elections is the possibility of compromising the voting machine by a malicious piece of code, which could change the votes cast systematically. To address this issue, different techniques have been proposed such as the use of vote verification techniques and the anonymous ballot techniques, e.g., Code Voting. Verifiability may help to detect such attack, while the Code Voting assists to reduce the possibility of attack occurrence. In this paper, a new code voting technique is proposed, implemented and tested, with the aid of an open source voting. The anonymous ballot improved accordingly the paper audit trail used in this machine. The developed system,

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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information & Communications Technology Applications (ntict)
An efficient color quantization using color histogram
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Publication Date
Tue Sep 14 2021
Journal Name
Nature Reviews Microbiology
Towards an integrative view of virus phenotypes
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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Fri Dec 23 2022
Journal Name
F1000research
Association between polymorphisms within the gene coding for tumor necrosis factor (TNF)-alpha with outcomes of treatment in a sample of Iraqi patients with ankylosing spondylitis taking etanercept: an observational study
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Background:Ankylosing spondylitis (AS) is a progressive, chronic inflammatory illness with an unclear etiology that explicitly targets the vertebral column, peripheral joints, and extraarticular tissues. The purpose of this research was to investigate if the existence of single nucleotide polymorphisms (SNPs) in the promoter region of the tumor necrosis factor-alpha (TNF-α) gene at positions -1031T/C (rs199964), -857C/T (rs1799724) and -806C/T (rs4248158) in a sample of Iraqi AS patients could influence the patients' outcomes with etanercept.

Methods:Sixty patients with established AS receiving only etanercept were selected to enroll in this study, with a mean age of 40.75±8.6

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