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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
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
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Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

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Publication Date
Sun Sep 01 2013
Journal Name
Baghdad Science Journal
Determination of Testosterone level as predictor for insulin resistance in young men with family history of type2 diabetes and hypertension.
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Background: Insulin resistance is associated with metabolic syndrome , type 2 diabetes and representing a risk factor for cardiovascular disease . This relationship may be modulated to some extent by age related changes in sex hormone status.. In particular, reduced total testosterone (TT) levels have been associated with insulin resistance and subsequent risk for developing type 2 diabetes. Aim of study: we examined whether low total testosterone level were associated with insulin resistance in young adult men. Methods: a total of 83 men (young adult men) divided into 2 group : (group1 ) 49 men with a risk factor for insu

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CT scan and deep learning for COVID-19 detection
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Partial Encryption for Colored Images Based on Face Detection
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HIDDEN FEATURES DETECTION USING HISTOGRAM MODIFICATION IN MRI IMAGES
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Magnetic Resonance Imaging (MRI) uses magnetization and radio waves, rather than x-rays to make very detailed, cross- sectional pictures of the brain. In this work we are going to explain some procedures belongs contrast and brightness improvement which is very important in the improvement the image quality such as the manipulation with the image histogram. Its has been explained in this worked the histogram shrink i.e. reducing the size of the gray level gives a dim low contrast picture is produced, where, the histogram stretching of the gray level was distributed on a wide scale but there is no increase in the number of pixels in the bright region. The histogram equalization has also been discuss together with its effects of the improveme

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Journal Name
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A New Face Swap Detection Technique for Digital Images
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Tue Oct 18 2022
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Plain, Edge, and Texture Detection Based on Orthogonal Moment
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Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

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Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Nano Fluid Detection for HPHE System Using Different Lasers
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Among the different passive techniques heat pipe heat exchanger (HPHE) seems to be the most effective one for energy saving in heating ventilation and air conditioning system (HVAC). The applications for nanofluids with high conductivity are favorable to increase the thermal performance in HPHE. Even though the nanofluid has the higher heat conduction coefficient that dispels more heat theoretically but the higher concentration will make clustering .Clustering is a problem that must be solved before nanofluids can be considered for long-term practical uses. Results showed that the maximum value of relative power is 0.13 mW at nanofluid compared with other concentrations due to the low density of nanofluid at this concentration. For highe

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