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Detection of Parvovirus B19 DNA in pregnant Sudanese women attending The Military hospital using Nested PCR technique : Detection of Parvovirus B19 DNA in pregnant Sudanese women
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Background: Parvovirus B19 is a human pathogenic virus associated with a wide range of clinical conditions. During pregnancy congenital infection with parvovirus B19 can be associated with poor outcome, including miscarriage, fetal anemia and non-immune hydrops.  

Objective: The study aimed to determine the prevalenceof Parvovirus B19 DNA in pregnant women attending the Military hospital in Khartoum, demonstrating the association between the virus and poor pregnancy outcomes.

Subjects and methods: This study was a cross sectional study, testing pregnant Sudanese women whole blood samples (n= 97) for the presence of Parvovirus B19 DNA using nested PCR technique.

Result: Two samples were found positive for Parvovirus B19 DNA out of the total number of samples screened.

Conclusions: The prevalence of Parvovirus B19 DNA among pregnant women attending the Military hospital was 2.1%.

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Publication Date
Fri Jan 01 2016
Journal Name
Iraqi Journal Of Science
Land cover change detection of Baghdad city using multi-spectral remote sensing imagery
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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Tue Oct 01 2019
Journal Name
2019 International Conference On Electrical Engineering And Computer Science (icecos)
An Evolutionary Algorithm for Community Detection Using an Improved Mutation Operator
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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Brain Tumour Detection using Fine-Tuning Mechanism for Magnetic Resonance Imaging
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In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

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Publication Date
Tue Jul 01 2014
Journal Name
Computer Engineering And Intelligent Systems
Static Analysis Based Behavioral API for Malware Detection using Markov Chain
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Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detection capability Alttafaria for some materials using a bacterial mutagenesis system
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Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Wed Jun 24 2015
Journal Name
Chinese Journal Of Biomedical Engineering
Single Channel Fetal ECG Detection Using LMS and RLS Adaptive Filters
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ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

Publication Date
Sat Aug 17 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Analysis of Follicular Fluid Fatty Acids in Iraqi Women Undergoing Intracytoplasmic Sperm Injection
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Background: Oocytes are susceptible to alterations in the various fatty acid contents of follicular fluid (FF), which may influence maturation and embryogenesis. Different fatty acids exert various effects on intracytoplasmic sperm injection (ICSI), which needs further studies to uncover the involved mechanisms. Objectives: To assess FF fatty acids in women undergoing ICSI and to correlate them with ICSI parameters, namely the total count of aspirated oocytes, oocyte maturation rate, fertilization rate and percentage of good-quality embryos. Methods: Fifty women undergoing ICSI were enrolled in this cross-sectional study. FF samples were collected during oocyte retrieval and were analyzed for fatty acids using gas chromatography. Fa

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Publication Date
Thu Oct 01 2015
Journal Name
Al-academy
Artistic features of women form in (Auguste-Dominique Ingres) works: نـدى عايـد يوسـف
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Between decline and appearing dichotomy, art history comes to announce birth of an era that glories past and find new names that are emerged from yearning to past and represented by neo-classical, By refusing the previous approaches and create topics that touché culture and derived from it through s revitalizing ideal beauty standards. One of neo-classical artists, who tried to simulate the classical works, is (Jean-Auguste-Dominique Ingres), who put framework for semantic aesthetic of the art form by revitalizing past glories and deeply searching myths and cultures through finding special artistic features that emphasizes artist own stylistics and identity. This research studies artistic features of women form in (Jean-Auguste-D

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