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Early detection of first degree relatives to type-II diabetes mellitus
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Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questionnaire was constructed for the purpose of the study, it is composed of (3) major parts, and
overall items, which are included in the questionnaire are (76) items. Reliability and validity of the questionnaire
were determined through a pilot study which is carried out during the period of August, 1
st
, 2008 to February, 30th
2009. The study instrument and structured interview technique were used as means of data collection. The data
were analyzed through the application of the descriptive statistical data analysis approach (Frequency and
Percentage) and the inferential statistical data analysis approach Chi-square, Pearson correlation coefficient.
Results: The results of the study confirmed that the mean of age is (55.7) year, and the majority of the sample are
male, first degree relatives with diabetes mellitus type-II are within positive bio-social aspect and laboratory
screening had an effect on the incidence of diabetes mellitus type-II for first degree relatives to type-II diabetes
mellitus.
Recommendations: The study recommends that the number of diabetes centers should be increased in Baghdad
and Governorates, promote of HbA1c test from general hospitals laboratories, guide notebook about the
predisposing factors of diabetes mellitus in his family, periodic screening for pre-diabetes and diabetes in high risk,
asymptomatic, undiagnosed adults within the health care setting, prevention program to prevent and control on
the predisposing risk factors for nondependent diabetes mellitus type-II and complication

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Wearable Detection Systems for Epileptic Seizure: A review
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The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.

Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.

The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple

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Publication Date
Tue Oct 12 2021
Journal Name
Engineering, Technology And Applied Science Research
Automated Pavement Distress Detection Using Image Processing Techniques
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Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Disc damage likelihood scale recognition for Glaucoma detection
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Abstract<p>Glaucoma is a visual disorder, which is one of the significant driving reason for visual impairment. Glaucoma leads to frustrate the visual information transmission to the brain. Dissimilar to other eye illness such as myopia and cataracts. The impact of glaucoma can’t be cured; The Disc Damage Likelihood Scale (DDLS) can be used to assess the Glaucoma. The proposed methodology suggested simple method to extract Neuroretinal rim (NRM) region then dividing the region into four sectors after that calculate the width for each sector and select the minimum value to use it in DDLS factor. The feature was fed to the SVM classification algorithm, the DDLS successfully classified Glaucoma d</p> ... Show More
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Scopus (6)
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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for Facial Image Detection System
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HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

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Scopus (6)
Scopus
Publication Date
Sun Dec 01 2024
Journal Name
Al-khwarizmi Engineering Journal
Defect Detection Using Thermography Camera Techniques: A review
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Individuals across different industries, including but not limited to agriculture, drones, pharmaceuticals and manufacturing, are increasingly using thermal cameras to achieve various safety and security goals. This widespread adoption is made possible by advancements in thermal imaging sensor technology. The current literature provides an in-depth exploration of thermography camera applications for detecting faults in sectors such as fire protection, manufacturing, aerospace, automotive, non-destructive testing and structural material industries. The current discussion builds on previous studies, emphasising the effectiveness of thermography cameras in distinguishing undetectable defects by the human eye. Various methods for defect

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Crossref
Publication Date
Wed Sep 11 2019
Journal Name
Journal Of Mechanical Engineering Research And Developments
INDUSTRIAL TRACKING CAMERA AND PRODUCT VISION DETECTION SYSTEM
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Publication Date
Sun Jan 01 2006
Journal Name
Acta Crystallographica Section E
(OC-6-32)-Bis[5-bromo-2-(4-bromophenyldiazenyl) phenyl]dicarbonylruthenium(II)
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The title compound, [Ru(C12H7Br2N2)2(CO)2], possesses a distorted octahedral environment about the Ru atom, with two cyclometallated 4,40-dibromoazobenzene ligands and two mutually cis carbonyl ligands. The donor atoms are arranged such that the N atoms are respectively trans to a carbonyl ligand and an aryl C atom. Comment The title compound, (I), has been prepared as a minor product of the reaction of Ru3(CO)12 and 4,40-dibromoazobenzene in refluxing n-octane; the major product is the cluster complex Ru3(3-NC6H4Br)2(CO)9 (Willis et al., 2005). Two strong (CO) absorptions at 2039 and 1991 cm1 in the IR spectrum of (I) are consistent with the presence of two mutually cis carbonyl groups. The crystal structure was investigated to ascertai

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Publication Date
Sat Jun 15 2024
Journal Name
Iraqi Journal Of Laser
Estimation of mean photon number based on single photon detection of weak coherent pulses
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The demand for single photon sources in quantum key distribution (QKD) systems has necessitated the use of weak coherent pulses (WCPs) characterized by a Poissonian distribution. Ensuring security against eavesdropping attacks requires keeping the mean photon number (µ) small and known to legitimate partners. However, accurately determining µ poses challenges due to discrepancies between theoretical calculations and practical implementation. This paper introduces two experiments. The first experiment involves theoretical calculations of µ using several filters to generate the WCPs. The second experiment utilizes a variable attenuator to generate the WCPs, and the value of µ was estimated from the photons detected by the BB

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Survival estimation for singly type one censored sample based on generalized Rayleigh distribution
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This paper interest to estimation the unknown parameters for generalized Rayleigh distribution model based on censored samples of singly type one . In this paper the probability density function for generalized Rayleigh is defined with its properties . The maximum likelihood estimator method is used to derive the point estimation for all unknown parameters based on iterative method , as Newton – Raphson method , then derive confidence interval estimation which based on Fisher information matrix . Finally , testing whether the current model ( GRD ) fits to a set of real data , then compute the survival function and hazard function for this real data.

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