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Deep Learning-Based Approach for Classifying the Severity of Metal Corrosion Using Sem Images
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Publication Date
Thu Mar 01 2012
Journal Name
International Journal For Sciences And Technology
The influence of patient’s age and severity of Pulmonary tuberculosis on serum interlukin-6 levels
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Interleukin-6 (IL-6) is a proinflammatory cytokine implicated in the immunopathogenesis of tuberculosis (TB). TB is recognized worldwide as an important public health issue. To study the relationship between the age of patients with pulmonary TB and serum IL-6 levels, from the other hand, the severity of this disease with IL-6 levels. This study included 30 patients (16 female and 14 male) with pulmonary TB and 10 healthy persons (5 female and 5 male) as control group for comparison. An ELISA assay was used to quantify IL-6 in the sera. The results showed a significant increase of IL-6 levels with increase of age of patients, in (23-38) year old patients the IL-6 levels (median= 17.9 pg/ml, range 12.3-29.1), while in (50-70) year old patien

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Publication Date
Thu Feb 24 2022
Journal Name
Journal Of Educational And Psychological Researches
The Evaluation of Illustrations Images in the Content of the Computer Book for the Second Intermediate Grade from the Point of View of the Teachers of the Subject
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The research aims at evaluating the illustrations images and determining the availability of good image standards in the illustrations images of the content of the second intermediate stage computer's book for the academic year (2019-2020) as seen by computer teachers. The sample was randomly selected, (30) teachers who are actually teaching the subject in schools within the geographical area of the province of Baghdad (Karkh III). To achieve this goal, ten standards were identified: scientific accuracy, suitability for the level of students, image clarity, image freshness, quality of coloring, suitability of its location of the subject, Matching their content glimpsed, The subject matter is appropriate in terms of area, matching its tit

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Publication Date
Tue Mar 01 2016
Journal Name
Minerals Engineering
The application of deep eutectic solvent ionic liquids for environmentally-friendly dissolution and recovery of precious metals
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Publication Date
Sat Feb 01 2025
Journal Name
Chemistryselect
Synthesis of Polypyrrole‐Graphene Oxide (PPy/GO) from Deep Eutectic Solvent and Its Characterization for Determination of Metronidazole Pharmaceutical Substance Using Spectrofluorometric Technique
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Abstract<p> A polypyrrole‐graphene oxide (PPy/GO) nanocomposite was made chemically using a polymerization method in deep eutectic solvents made up of choline chloride and propionic acid in a 1:2 molar ratio. The purpose of this study is to examine the feasibility and efficacy of PPy/GO nanocomposite in the detection of metronidazole in pharmaceutical formulations utilizing spectrofluorometric techniques. Characterization of the synthesized PPy/GO nanocomposite was conducted using several methods such as transmission electron microscopy (TEM), scanning electron microscopy (SEM), Fourier‐transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA), and X</p> ... Show More
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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Influence of Nanoreinforced Particles (Al2O3) on Fatigue Life and Strength of Aluminium Based Metal Matrix Composite
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Abstract

     In this investigation, Al2O3 nano material of 50nm particles size were added to the 6061 Al aluminium alloy by using the stir casting technique to fabricate the nanocomposite of 10wt% Al2O3. The experimental results observed that the addition of 10wt% Al2O3 improved the fatigue life and strength of constant and cumulative fatigue. Comparison between the S-N curves behaviour of metal matrix (AA6061) and the nanocomposite 10wt% Al2O3 has been made. The comparison revealed that 12.8% enhancement in fatigue strength at 107cycles due to 10wt% nano reinforcement. Also cumulative fatigue l

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
The effect of left ventricle ischemia severity on cardiac performance appeared on ejection fraction using radioactive TC <sup>99m</sup> MIBI in comparison with echocardiography
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Abstract<p>Ischemic heart disease is a major causes of heart failure. Heart failure patients have predominantly left ventricular dysfunction (systolic or diastolic dysfunction, or both). Acute heart failure is most commonly caused by reduced myocardial contractility, and increased LV stiffness. We performed echocardiography and gated SPECT with Tc<sup>99m</sup> MIBI within 263 patients and 166 normal individuals. Left ventricular end systolic volume (LVESV), left ventricular end diastolic volume (LVEDV), and left ventricular ejection fraction (LVEF) were measured. For all degrees of ischemia, there was a significant difference between ejection fraction values measured by SPECT and echo</p> ... Show More
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Publication Date
Thu May 31 2018
On the Use of 6th-Order Tunable Complementary Metal-Oxide-Semiconductor Varactor based Filter in Ultra-Wideband Low Noise Amplifier
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Background:

The plethora of the emerged radio frequency applications makes the frequency spectrum crowded by many applications and hence the ability to detect specific application’s frequency without distortion is a difficult task to achieve.

Objective:

The goal is to achieve a method to mitigate the highest interferer power in the frequency spectrum in order to eliminate the distortion.

Method:

This paper presents the application of the proposed tunable 6th-order notch filter on Ultra-Wideband (UWB) Complementary Metal-Oxide-Semiconductor (CMOS) Low Noise

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Publication Date
Wed Apr 01 2026
Journal Name
Neurocomputing
Minion gated recurrent unit for continual learning
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The increasing demand for continual learning in sequential data processing has led to progressively complex training methodologies and larger recurrent network architectures. Consequently, this has widened the knowledge gap between continual learning with recurrent neural networks (RNNs) and their ability to operate on devices with limited memory and compute. To address this challenge, we investigate the effectiveness of simplifying RNN architectures, particularly gated recurrent unit (GRU), and its impact on both single-task and multitask sequential learning. We propose a new variant of GRU, namely the minion recurrent unit (MiRU). MiRU replaces conventional gating mechanisms with scaling coefficients to regulate dynamic updates of hidden

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