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A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Publication Date
Sat Aug 01 2020
Journal Name
Surgical Neurology International
Unilateral absence of the internal carotid artery associated with anterior communicating artery aneurysms: Systematic review and a proposed management algorithm
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Background:

Absence or hypoplasia of the internal carotid artery (ICA) is a rare congenital anomaly that is mostly unilateral and highly associated with other intracranial vascular anomalies, of which saccular aneurysm is the most common. Blood flow to the circulation of the affected side is maintained by collateral pathways, some of which include the anterior communicating artery (Acom) as part of their anatomy. Therefore, temporary clipping during microsurgery on Acom aneurysms in patients with unilateral ICA anomalies could jeopardize these collaterals and place the patient at risk of ischemic damage. In this paper, we review the literature on cases with a unilaterally absent ICA associa

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Measuring and Analyzing of the Relationship between the Financial Development, Economic growth, and Poverty in Iraq with the Autoregressive Distributed lag Model framework for the period (1980-2010)
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The developed financial system is essential for increasing economic growth and poverty reduction in the world. The financial development helps in poverty reduction indirectly via intermediate channel which is the economic growth. The financial development enhancing economic development through mobilization of savings and channel them to the most efficient uses with higher economic and social returns. In addition, the economic growth reduces the poverty through two channels. The first is direct by increasing the introduction factors held by poor and improve the situations into the sectors and areas where the poor live. The second is indirect through redistribution the realized incomes from the economic growth as well as the realiz

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Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Influence Activation Function in Approximate Periodic Functions Using Neural Networks
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The aim of this paper is to design fast neural networks to approximate periodic functions, that is, design a fully connected networks contains links between all nodes in adjacent layers which can speed up the approximation times, reduce approximation failures, and increase possibility of obtaining the globally optimal approximation. We training suggested network by Levenberg-Marquardt training algorithm then speeding suggested networks by choosing most activation function (transfer function) which having a very fast convergence rate for reasonable size networks.             In all algorithms, the gradient of the performance function (energy function) is used to determine how to

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
On Gradient Descent Localization in 3-D Wireless Sensor Networks
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Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Multiwavelet based-approach to detect shared congestion in computer networks
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Internet paths sharing the same congested link can be identified using several shared congestion detection techniques. The new detection technique which is proposed in this paper depends on the previous novel technique (delay correlation with wavelet denoising (DCW) with new denoising method called Discrete Multiwavelet Transform (DMWT) as signal denoising to separate between queuing delay caused by network congestion and delay caused by various other delay variations. The new detection technique provides faster convergence (3 to 5 seconds less than previous novel technique) while using fewer probe packets approximately half numbers than the previous novel technique, so it will reduce the overload on the network caused by probe packets.

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Publication Date
Thu Jul 11 2024
Journal Name
Maaen Journal For Medical Sciences
Pharmacological Supplements Efficacy in Management of chronic pain associated with Sickle Cell Disease: A narrative review
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Sickle cell disease (SCD) is a hereditary ailment that can cause severe pain and suffering to people who are affected. However, with continued investment in research and treatment options, we can make progress towards improving the lives of those with SCD. Over 40% of patients experience painful vaso-occlusive crises (VOCs), so we must work towards finding solutions and providing support for those living with this condition, These episodes, a hallmark of SCD, significantly contribute to morbidity, mortality, and a diminished quality of life, while also incurring substantial healthcare costs. Chronic pain particularly affects older adolescents and adults with SCD, with over half reporting daily discomfort. Opioid-based analgesics, though sti

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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Publication Date
Wed May 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Detection for The Production of Siderophore in Burkholderia cepacia Isolated From the Rhizosphers of Some Plants and studing the Effect of the Bacterial Filtrate and Extract on Some Pathogenic Fungi
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bstract         This study was performed to isolate and identify the Burkholderia cepacia from rhizosphers of different plants and study their ability to produce Siderophore, the study was also aimed to assess the antifungal activity of the bacterial filtrate and extracts of the isolates against some pathogenic fungi.     The isolate which showed higher inhibitory effects was selected for extraction of some active metabolites produced by it, and evaluate the activity in vitro, via inhibition of the growth of the fungi using different concentrations of extract (50, 100, 200 )µL/ml , The results showed that out of  (250) samples of soil , (8) isolates (3.2%) gave positive

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Publication Date
Tue Oct 18 2022
Journal Name
Ieee Access
Plain, Edge, and Texture Detection Based on Orthogonal Moment
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Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

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Crossref (14)
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Publication Date
Tue Oct 04 2022
Journal Name
Ieee Access
Plain, Edge, and Texture Detection Based on Orthogonal Moment
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Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

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