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bsj-9740
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of Alzheimer's disease. The system employs MRI and feature extraction methods to categorize images. This paper adopts the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset includes functional MRI and Positron-Version Tomography scans for Alzheimer's patient identification, which were produced for people with Alzheimer's as well as typical individuals. The proposed technique uses MRI brain scans to discover and categorize traits utilizing the Histogram Features Extraction (HFE) technique to be combined with the Canny edge to representing the input image of the Convolutional Neural Networks (CNN) classification. This strategy keeps track of their instances of gradient orientation in an image. The experimental result provided an accuracy of 97.7% for classifying ADNI images.

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Publication Date
Wed Sep 15 2021
Journal Name
Al-academy
Design features of medicine box packaging for children: منى محمود حسين
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Graphic design constitutes the human necessity for the design action, so there is no design achievement that is not considered in its founding project and its final realization as a response to a specific necessity. As a result of knowledge, which is the product of experience and is the result of applied science, design is based on observation, study and development, leading to the main goal, which is the utilitarian and aesthetic function that is put into the final consideration of design, and drug packaging design has an important role in all marketing fields, as companies compete with each other to attract the largest number Possible from consumers in a way that guarantees them material profit, and in order to achieve this, it always

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Prediction of Brain Stroke at an Early Stage
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     The healthcare sector has traditionally been an early adopter of technological progress, gaining significant advantages, particularly in machine learning applications such as disease prediction. One of the most important diseases is stroke. Early detection of a brain stroke is exceptionally critical to saving human lives. A brain stroke is a condition that happens when the blood flow to the brain is disturbed or reduced, leading brain cells to die and resulting in impairment or death. Furthermore, the World Health Organization (WHO) classifies brain stroke as the world's second-deadliest disease. Brain stroke is still an essential factor in the healthcare sector. Controlling the risk of a brain stroke is important for the surviv

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Determination of Nickel and Cobalt in Cosmetic Products Marketed in Iraq Using Spectrophotometric and Microfluidic Paper-based Analytical Device (µPADs) Platform
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Two quantitative, environment-friendly and easily monitored assays for Ni (II) and Co (III) ions analysis in different lipstick samples collected from 500-Iraqi dinars stores located in Baghdad were introduced. The study was based on the reaction of nickel (II) ions with dimethylglyoxime (DMG) reagent and the reaction of cobalt (III) ions with 1-nitroso-2-naphthol (NN) reagent to produce colored products. The color change was measured by spectrophotometric method at 565 nm and 430 nm for Ni and Co, respectively, with linear calibration graphs in the concentration range 0.25-100 mg L-1 (Ni) and 0.5-100 mg L-1 (Co) and LOD and LOQ of 0.11 mg L-1 and 0.36 mg L-1 (Ni), and 0.15 mg L-1 an

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental and Theoretical Study for Performance Enhancement of Air Solar Collectors by Using Different Absorbers
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An experimental and theoretical study has been done to investigate the thermal performance of different types of air solar collectors, In this work air solar collector with a dimensions of (120 cm x90 cm x12 cm) , was tested under climate condition of  Baghdad city with a (43° tilt angel)  by using  the absorber plate (1.45 mm thickness, 115 cm height x 84 cm width), which was manufactured from iron painted with a black matt.

The experimental test deals with five types of absorber:-

 Conventional smooth flat plate absorber , Finned absorber , Corrugated absorber plate, Iron wire mesh on absorber And matrix of porous media  on absorber .

The hourly and average efficiency of the collectors

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

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Publication Date
Thu Jun 30 2016
Journal Name
Al-kindy College Medical Journal
Association between periodontitis and acquired coronary heart disease
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Background: The association between oral microbial infection and systemic disease is not a new concept. A major confounding issue is that oral infections often are only one of the many important factors that can influence systemic diseases .Objective: This study was conducted to evaluate the periodontal health status of patients with acquired coronary heart disease. Type of the study: Cross-sectional study.Methods: The study group consisted of 200 patients with an age range (35-70) years, having coronary heart disease .This study group were compared to a control group of non-coronary heart disease (200 individuals ) matching with age and gender. The oral parameters were examined including the periodontal conditions, assessment of periodo

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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
The Relationship between Celiac Disease and Unexplained Infertility
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To determine the relationship between celiac disease and reproductive complication, twenty five women with clinically definite unexplained infertility aged (22-35) have been investigated and compared to fifteen apparently healthy women. All the studied groups were subjected to measurement of anti-tissue transglutaminase antibodies IgA and IgG by ELISA technique and anti-endomysial antibodies IgA and IgG by IFAT technique .There was a highly significant elevation (P< 0.01) in the concentration of anti- tTG IgA Abs compared to control group, Also, there was significant elevation (P< 0.05) in the concentration of anti- tTG IgG Abs compared to control group .The results illustrated that the prevalence of anti-EMA IgA and IgG Abs were (

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Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
Diagnostic Evaluation of Uterine Artery Doppler Imaging for the Prediction of Early Abnormal Pregnancy
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Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy.

Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when a

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Publication Date
Thu Jan 14 2021
Journal Name
Iraqi Journal Of Science
Boosting the Network Performance using Two Security Measure Scenarios for Service Provider Network
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Network security is defined as a set of policies and actions taken by a network administrator in order to prevent unauthorized access, penetrated the defenses and infiltrated the network from unnecessary intervention. The network security also involves granting access to data using a pre-defined policy. A network firewall, on the other hand, is a network appliance that controls incoming and outgoing traffic by examining the traffic flowing through the network. This security measure establishes a secure wall [firewall] between a trusted internal network and the outside world were a security threat in shape of a hacker or a virus might have existed

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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