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Detection and Diagnosis of Induction Motor Faults by Intelligent Techniques
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This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosis system is developed to determine the status of the motor without the need for an expert. This system is based on artificial neural network (ANN) and it is characterized by speed and accuracy and the ability to detect more than one fault at the same time.
 

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Publication Date
Mon Sep 15 2014
Journal Name
Journal Of Clinical And Biomedical Sciences
Detection of EGFR Mutations in Bronchial Wash from Iraqi patients with nonsmall Cell Lung Cancer (NSCLC)
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Background: Non-small cell lung cancer (NSCLC) is caused of 85% of all lung cancers. Among the most important factors for lung tumor growth and proliferation are the tyrosine kinase receptors that coded by the epidermal growth factor recep-tor (EGFR) gene. Activation of EGFR ultimately leads to developing of lung cancer. The present study was undertaken with an objective to detect EGFR mutations in bronchial wash from Iraqi patients with NSCLC before treatment. Methods: DNA was extracted from bronchial wash samples collected from 50 patients with NSCLC by using a Qiamp DNA Mini Kit (Qiagen, Hilden, Germany). Then, EGFR mutations were determined by using real-time RCR combined with two technologies, Amplification Refractory Mutation System (

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Publication Date
Sun Jun 27 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Depression among Nurses Providing Care for Patients with COVID-19 at Baqubah Teaching Hospital
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Objectives: The present study aims at detecting the depression among nurses who provide care for infected patients with corona virus phenomenon and to find out relationships between the depression and their demographic characteristics of age, gender, marital status, type of family, education, and years of experience of nurses in heath institutions, infection by corona virus, and their participation in training courses.
Methodology: A descriptive study is established for a period from October 10th, 2020 to April 15th, 2021. The study is conducted on a purposive (non-probability) sample of (100) nurse who are providing care for patients with COVID-19 and they are selected from the isolation wards. The instrument of the study is develope

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Publication Date
Tue Sep 30 2014
Journal Name
J Clin Biomed Sci
Detection of EGFR Mutations in Bronchial Wash from Iraqi patients with nonsmall Cell Lung Cancer (NSCLC)
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Background: Non-small cell lung cancer (NSCLC) is caused of 85% of all lung cancers. Among the most important factors for lung tumor growth and proliferation are the tyrosine kinase receptors that coded by the epidermal growth factor recep-tor (EGFR) gene. Activation of EGFR ultimately leads to developing of lung cancer. The present study was undertaken with an objective to detect EGFR mutations in bronchial wash from Iraqi patients with NSCLC before treatment. Methods: DNA was extracted from bronchial wash samples collected from 50 patients with NSCLC by using a Qiamp DNA Mini Kit (Qiagen, Hilden, Germany). Then, EGFR mutations were determined by using real-time RCR combined with two technologies, Amplification Refractory Mutation System (

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Publication Date
Sun Jan 01 2023
Journal Name
Bionatura
Detection of lukf-pv gene in Staphylococcus aureus isolated from pregnant women with Urinary tract infection
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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Overlapping Structure Detection in Protein-Protein Interaction Networks Using a Modified Version of Particle Swarm Optimization
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In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

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Publication Date
Wed Nov 17 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Pearson coefficient matrix for studying the correlation of community detection scores in multi-objective evolutionary algorithm
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Publication Date
Sun Sep 22 2019
Journal Name
Baghdad Science Journal
Detection of CTX-M-type ESBLs from Escherichia coli Clinical Isolates from a Tertiary Hospital, Malaysia
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The present study aims to detect CTX-M-type ESBL from Escherichia coli clinical isolates and to analyze their antibotic susceptibility patterns. One hundred of E. coli isolates were collected from different clinical samples from a tertiary hospital. ESBL positivity was determined by the disk diffusion method. PCR used for amplification of CTX-M-type ESBL produced by E. coli. Out of 100 E. coli isolates, twenty-four isolates (24%) were ESBL-producers. E. coli isolated from pus was the most frequent clinical specimen that produced ESBL (41.66%) followed by urine (34.21%), respiratory (22.23%), and blood (19.05%).  After PCR amplification of these 24 isolates, 10 (41.66%) isolates were found to possess CTX-M genes. The CTX-M type ESBL

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Flow Injection Analysis with Turbidity Detection for the Quantitative Determination of Mebeverine Hydrochloride in Pharmaceutical Formulations
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The main objective of this paper is to develop and validate flow injection method, a precise, accurate, simple, economic, low cost and specific turbidimetric method for the quantitative determination of mebeverine hydrochloride (MbH) in pharmaceutical preparations.  A homemade NAG Dual & Solo (0-180º) analyser which contains two identical detections units (cell 1 and 2) was applied for turbidity measurements. The developed method was optimized for different chemical and physical parameters such as perception reagent concentrations, aqueous salts solutions, flow rate, the intensity of the sources light, sample volume, mixing coil and purge time. The correlation coefficients (r) of the developed method were 0.9980 and 0.9986 for cell

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Publication Date
Sun Jul 01 2018
Journal Name
Computers And Electronics In Agriculture
Detection of charcoal rot (Macrophomina phaseolina) toxin effects in soybean (Glycine max) seedlings using hyperspectral spectroscopy
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Publication Date
Sun Jan 01 2017
Journal Name
Kufa Journal For Nursing Sciences
Effectiveness of Simulation Techniques on the Nursing Students Knowledge toward Cardiopulmonary Resuscitation for Adults at College of Nursing/University of Baghdad
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MM Abdulwahhab, kufa Journal for Nursing sciences, 2017 - Cited by 1

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