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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
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

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Publication Date
Sat Jan 01 2022
Journal Name
Ssrn Electronic Journal
The Prospective of Artificial Neural Network (ANN’s) Model Application to Ameliorate Management of Post Disaster Engineering Projects
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Currently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practica

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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field
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   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Wed Aug 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Performance Evaluation Based on Multi-UAV in Airborne Computer Network System
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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Use Pareto Chart to diagnose the level of quality of municipal services
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The aim of the study is to study the quality of services in a sample of the municipalities of Baghdad governorate and identify the deviations in their operations and provide solutions to address the causes of deviations. The research field aims at the same activity related to municipal services and their quality and analysis using some tools for continuous improvement to identify the authorities responsible for the delay and quality of services. In the future, the importance of research is shown by the use of these tools and their use and their application to the data of the directorates (sample of the study) to diagnose and treat problems, especially that they include statistical methods that are clear and easy to understand the

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Publication Date
Sun Jul 01 2018
Journal Name
International Journal Of Medical Research & Health Sciences
Rate of Fetal Macrosomia with Maternal and Early Neonatal Complications in Internally Moved People Affected by Violence
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Background: Fetal macrosomia is usually distressing to obstetricians and neonatologists. In the current study, involved mothers had poor social and medical circumstances, as they were migrated forcefully within the country borders due to war, from their original homeland to safer camps which had miserable situations. Objectives: To study rate, risk factors, and complications of macrosomia in people with low socio-economic living conditions and missed medical follow up. Methods: All internally displaced pregnant women who gave birth to neonates weighed ≥4000 g were involved in the study. All required history, examination, care, and investigations were practiced by the attending obstetrician and neonatologist. Cases of normal birth weight n

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Publication Date
Wed May 16 2018
Journal Name
Route Educational And Social Science Journal I
Graphing skills of Chemistry students at Ibn Al-Haytham Education college of pure sciences in Baghdad
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The aim of this research is to investigate the skills of the chemistry students from the Ibn Al-Haytham Education college of pure sciences in Baghdad in understanding and constructing graphical representations of data. The research sample consisted of (101) male and female students in their fourth year of study during the 2016-2017 academic year. This sample represents 71% of the total number of students in this group.The research methodology used consisted of two parts relating to 19 issues. The first part is an objective multi choice type of test to measure the student’s skill in selecting the right representation of specific subject graph amongst many provided. The second part concentrated on measuring the student’s skill in construc

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
edge detection using modification prewitt operators
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in this paper we adopted ways for detecting edges locally classical prewitt operators and modification it are adopted to perform the edge detection and comparing then with sobel opreators the study shows that using a prewitt opreators

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