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Molecular and Immunological Detection of Hepatitis C Virus in Patients with Chronic Renal Failure
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Due to its association with hepatocellular carcinoma and being one of the ten most common malignancies worldwide, hepatitis C viral infection has become a severe public health concern. Therefore, establishing an accurate, reliable and sensitive diagnostic test for this infection is strongly advised. Real-time polymerase chain reaction (PCR) has been created to achieve this purpose. The current study was established to investigate the hepatitis C virus among Iraqi patients with chronic renal failure and to detect the virus immunologically by the fourth generation enzyme-linked immunosorbent assay technique and molecularly by real-time PCR. As a result, out of 50 patients with chronic renal failure undergoing dialysis, 39 patients tested positive for anti-HCV IgG by ELISA test and only 9 patients of the total count tested positive and showed growth curves with copy numbers of 1×102, 2.5×102, 3×102, 2.7×103, 2.7×103, 3.5×103, 8.7×104, 3.5×105 and 5.5×106 copies/ml respectively detected for HCV only by real-time PCR. Therefore, real-time PCR is beneficial for precise viral load determination and detection of viral hepatitis in chronic renal failure patients.

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Fri May 15 2026
Journal Name
Journal Of Intelligent & Fuzzy Systems: Applications In Engineering And Technology
Backbone Selection and Timing Optimization for Real-Time Defect Detection on Fast Industrial Conveyors
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This work presents a canned-food defect-detection method using the EfficientDet model with four backbones (MobileNet, EfficientNet, Swin-T, and ConvNeXt). The dataset included 8046 images with a resolution of 512 × 512 pixels. The performance criteria in this study accuracy “mAP”, computational cost “FLOPs”, and Frames Per Second “FPS”. The lightweight backbone with EfficientDet achieves a mean Average Precision (mAP) of 90% with MobileNet, while EfficientNet achieves mAP accuracy of 92% and 94%. The heavy backbone for EfficientDet (Swin-T, and ConvNeXt) achieves mAP accuracy of 96% and 98%. The main contribution of this study is to optimize the speed of conveyor belts in industrial production lines to considers the

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Tue Jun 01 2021
Journal Name
Food Chemistry
Development of cellulose Nanofiber-based substrates for rapid detection of ferbam in kale by Surface-enhanced Raman spectroscopy
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Publication Date
Tue Nov 01 2011
Journal Name
Journal
Frequency of autoimmune diseases and estimation of P53 among vitiligo patients
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KE Sharquie, AA Noaimi, SY Mohsin, 2011 - Cited by 4

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of The Iraqi University
Exclusion optimal portfolio from outlier by using fuzzy c-means clustering - analytical research at the Iraqi Stock Exchange
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This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Fri Jan 01 2021
Journal Name
Chemical Science
Stalling chromophore synthesis of the fluorescent protein Venus reveals the molecular basis of the final oxidation step
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Fluorescent proteins (FPs) have revolutionised the life sciences, but the chromophore maturation mechanism is still not fully understood. Here we photochemically trap maturation at a crucial stage and structurally characterise the intermediate.

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Publication Date
Sat Feb 01 2025
Journal Name
Saudi Medical Journal
Spectrum and classification of ATP7B variants with clinical correlation in children with Wilson disease
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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Serum Vitamin D Levels in a Sample of Iraqi Female Patients
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Background: Recurrent aphthous stomatitis (RAS) is one of the most common oral mucosa diseases characterized by recurrent, shallow, round or oval painful oral ulcers surrounded by inflammatory erythematous halos, the condition is chronic and self-limiting in immunocompetent patients. Aim of the study: to investigate the serum vitamin D levels in Iraqi female patients with RAS and the relationship between vitamin D levels and the severity of RAS. In this cross sectional study 30 female patients with idiopathic RAS, and 30 age and sex matched healthy controls were included, the severity of RAS is assessed by the number of oral aphthous ulcers in each attack and the frequency of attacks. Serum 25(OH) D levels were determined by the Enzy

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