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Noise Detection and Removing in Heart Sound Signals via Nuclear Norm Minimization Problems
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Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix contains zeros, so the problem is to find a low-rank matrix. Matrix completion is a heuristic NP-hard problem. It is a minimization problem defined by the matrix nuclear norm. In this paper, nuclear norm, and weighted nuclear norm minimization problems are derived to find a low-rank matrix of implemented Hankel matrix from the signal. A Robust Principal Component used to solve a low-rank-sparse matrix finds a low-rank Hankel matrix by solving a minimization problem numerically. The results show that the given methods are efficient in reconstructing and recovering the signals with a rate of more than 96%, with small values of mean square errors

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Publication Date
Wed Sep 20 2023
Journal Name
Journal Of Applied And Natural Science
Detection of some virulence genes (esp, agg, gelE, CylA) in Enterococcus faecalis isolated from different clinical cases at Baghdad
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The virulent genes are the key players in the ability of the bacterium to cause disease. The products of such genes that facilitate the successful colonization and survival of the bacterium in or cause damage to the host are pathogenicity determinants. This study aimed to investigate the prevalence of virulence factors (esp, agg, gelE, CylA) in E. faecalis isolated from diverse human clinical collected in Iraqi patient , as well as to assess their ability to form biofilm and to determine their haemolytic and gelatinase activities. Thirty-two isolates of bacteria Enterococcus faecalis were obtained, including 15 isolates (46.87%) of the urine, 6 isolates (18.75%) for each of the stool and uterine secretions, and 5 isolates (15.62%) of the wo

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Publication Date
Mon Nov 14 2022
Journal Name
Biomedicine
Cytotoxic effect of cloned EGFP gene on NCI-H727 cell line via genetically engineered gene transfer system
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Introduction and Aim: Cancers are a complex group of genetic illnesses that develop through multistep, mutagenic processes which can invade or spread throughout the body. Recent advances in cancer treatment involve oncolytic viruses to infect and destroy cancer cells. The Newcastle disease virus (NDV), an oncolytic virus has shown to have anti-cancer effects either directly by lysing cancer cells or indirectly by activating the immune system. The green fluorescent protein (GFP) has been widely used in studying the anti-tumor activity of oncolytic viruses. This study aimed to study the anticancer effect of a recombinant rNDV-GFP clone on NCI-H727 lung carcinoma cell line in vitro.   Materials and Methods: The GFP gene was inserted t

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Publication Date
Sat Jul 01 2017
Journal Name
Al–bahith Al–a'alami
The Digital Presence of Algerian Females via Virtual Satellite Channels: Analytical Study of Women Issues through Facebook
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The platforms of social networking sites, with their distinctive communication and technological features, create a social movement that led to the establishment of a new pattern of communication in a modern context. This allows the users on the internet to carry out many social interactions based on the interests and commonalities among them. Algerian women have a share of this digital presence by representing their views and discussing their issues on several sites like Facebook, for example.
In this research, we have analyzed the pages of Algerian women on Facebook site to find out the most important issues addressed by Algerian women so that we can organize their concerns in the digital channels and discover their different orie

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Publication Date
Mon Nov 14 2022
Journal Name
Biomedicine
Cytotoxic effect of cloned EGFP gene on NCI-H727 cell line via genetically engineered gene transfer system
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Introduction and Aim: Cancers are a complex group of genetic illnesses that develop through multistep, mutagenic processes which can invade or spread throughout the body. Recent advances in cancer treatment involve oncolytic viruses to infect and destroy cancer cells. The Newcastle disease virus (NDV), an oncolytic virus has shown to have anti-cancer effects either directly by lysing cancer cells or indirectly by activating the immune system. The green fluorescent protein (GFP) has been widely used in studying the anti-tumor activity of oncolytic viruses. This study aimed to study the anticancer effect of a recombinant rNDV-GFP clone on NCI-H727 lung carcinoma cell line in vitro.   Materials and Methods: The GFP gene was inserted t

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Robust Color Image Encryption Scheme Based on RSA via DCT by Using an Advanced Logic Design Approach
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Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to

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Publication Date
Sun Jun 01 2025
Journal Name
International Communications In Heat And Mass Transfer
Enhanced thermal management of lithium-ion pouch cells via hybrid approach of phase change material-liquid cooling
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Publication Date
Sat Oct 05 2019
Journal Name
Journal Of Engineering And Applied Sciences
Study the Effect of Coating by TiO2 Nano-Particles on Carbon Steel Behavior via. Sol-Gel Method
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Publication Date
Sun Jun 02 2019
Journal Name
Baghdad Science Journal
New Fluorometric Method for the Determination of Ketotifen Fumarate Using Continuous Flow Injection Analysis via ISNAG-fluorimeter
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        A newly developed analytical method was conducted for the determination of Ketotifen fumarate (KTF) in pharmaceuticals drugs via quenching of continuous fluorescence of 9(10H)-Acridone (ACD). The method was applied using flow injection system of a new homemade ISNAG fluorimeter with fluorescence measurements at ± 90◦ via 2×4 solar cell. The calibration graph was linear in the range of 1-45 mmol/L, with correlation coefficient r = 0.9762 and the limit of detection 29.785 µg/sample from the stepwise dilution for the minimum concentration in the linear dynamic ranged of the calibration graph. The method was successfully applied to the determination of Ketotifen fumarate in two different pharma

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Publication Date
Sun May 11 2014
Journal Name
World Journal Of Experimental Biosciences
Detection of hydrolytic enzymes produced by Azospirillum brasiliense isolated from root soil
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Publication Date
Tue Sep 01 2026
Journal Name
International Journal Of Advances In Applied Sciences
COVID-19 infection detection using convolutional self-attention network with voting classifier
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Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,

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