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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
Thu Oct 12 2023
Journal Name
Egyptian Journal Of Biological Pest Control
Evaluation of the effectiveness of some mycorrhizal fungi isolates against charcoal rot disease
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Abstract<sec> <title>Background

The sunflower plants are attacked by serious seed and soil-borne pathogens including charcoal rot disease that caused by Macrophomina phaseolina. This disease has serious damages to sunflower crop. This study aimed to assess the efficacy of Arbuscular mycorrhizal fungus against charcoal rot disease as fungicide alternative.

Results

Morphological and molecular identification was done, using universal primers for molecular identification. Finally, a greenhouse experiment was conducted, and

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study
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Publication Date
Sun Jul 17 2022
Journal Name
Al–bahith Al–a'alami
Features of news coverage during Covid-19 crisis: Content analysis on a sample of global news accounts on Twitter
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This study aims to analyze the messages of a number of global news outlets on Twitter. In order to clarify the news outlets tactics of reporting, the subjects and focus during the crisis related to the spread of the Covid-19 virus. The study sample was chosen in a deliberate manner to provide descriptive results. Three news sites were selected: two of the most followed, professional and famous international news sites: New York Times and the Guardian, and one Arab news site: Al-Arabiya channel.

A total of 18,085 tweets were analyzed for the three accounts during the period from (1/3/2020) to (8/4/2020). A content analysis form was used to analyze the content of the news coverage.   The results indicate an increase in th

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Publication Date
Tue Mar 08 2022
Journal Name
Multimedia Tools And Applications
Comparison study on the performance of the multi classifiers with hybrid optimal features selection method for medical data diagnosis
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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Financial reporting of grants and assistance in self-financing units according IAS 20
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The objective of the research is to clarify the grants and aids as a conceptual input, identify the factors of obtaining them and their objectives, and the statement of the need to produce accounting information that enhances financial reporting related to grants and assistance, especially the presentation of the accounting treatments provided by the unified accounting system and determining the shortcomings of that system, The accounting requirements of IAS20 to limit the variation of treatments with application to the economic unit (the research sample) are presented.

The study reached a set of conclusions, the most important of which is the absence of an accounting base in Iraq that determines the basi

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Publication Date
Wed May 03 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

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Publication Date
Mon Dec 28 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
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The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

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Publication Date
Sun Oct 01 2023
Journal Name
Medical Journal Of Babylon
Prevalence of coronary artery disease in patients with left bundle branch block and its association with risk factors hypertension and diabetes mellitus
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Abstract<sec> <title>Background:

Left bundle branch block (LBBB) is a common finding in electrocardiography, there are many causes of LBBB.

Objectives:

The aim of this study is to discuss the true prevalence of coronary artery disease (CAD) in patients with LBBB and associated risk factors in the form of hypertension and diabetes mellitus.

Materials and Methods:

Patients with LBBB were admitted to the Iraqi heart center for cardiac disea

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Publication Date
Fri Sep 30 2022
Journal Name
International Journal Of Health Sciences
Relation of retinol binding protein4, visfatin and vitamin a in obese and non obese Iraqi patients with non alcoholic fatty liver disease
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One of the most common public liver diseases over the world is fatty liver which contain alcoholic and non-alcoholic fatty liver. One-fourth among general population are impact Non-Alcoholic Fatty Liver Disease (NAFLD) in the worldwide.Retinol binding protein 4 (RBP4) is known as an adipokine, mainly synthesized and secreted from the liver and form adipose tissues. RBP4 acts as a transporter and specifically bound to retinol from liver to others tissues. Visfatin is an adipocytokine and mainly produced from visceral fat tissue, skeletal muscles as well as liver. Vitamin A absorbed, transported as retinyl esters to the liver then hydrolyzed to the retinol form and storage in hepatic stellate cells (HSCs) after reesterified with rigly

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Effect of some induce chemical and biological agents against (Tilletia tritici (Bjerk) and T.laevis (Kühn) causal agents of wheat Common bunt disease
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This study was conducted to evaluate the efficiency of some chemicals and biological agents to induce systemic resistance (ISR) against to wheat common bunt disease caused by the two species of fungus Tilletia tritici (Bjerk.) Wint (T. caries (Dac.) Tul.) and T. laevis Kuhn (T. foetida (Wall.) Liro. Trails in the efforts to find an alternative, safe and environmentally friendly means to control the disease. Results of this study which carried out during two consecutive seasons for the years 2012 - 2013 and 2013 - 2014 at two different environmental locations. Seed treatment by (SA 100 and 200 mg/L, 500 ?–aminobutyric acid (BABA) and 1000 mg/L, Effective Microorganisms (EM1) 40 and 150 ml/kg seeds) have led to high significant redu

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