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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
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
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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Publication Date
Sat Mar 01 2025
Journal Name
Iraqi Journal Of Physics
Design an Efficient Neural Network to Determine the Rate of Contamination in the Tigris River in Baghdad City
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This article proposes a new technique for determining the rate of contamination. First, a generative adversarial neural network (ANN) parallel processing technique is constructed and trained using real and secret images. Then, after the model is stabilized, the real image is passed to the generator. Finally, the generator creates an image that is visually similar to the secret image, thus achieving the same effect as the secret image transmission. Experimental results show that this technique has a good effect on the security of secret information transmission and increases the capacity of information hiding. The metric signal of noise, a structural similarity index measure, was used to determine the success of colour image-hiding t

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Publication Date
Wed Mar 01 2023
Journal Name
Baghdad Science Journal
Minimum Neighborhood Domination of Split Graph of Graphs
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Let  be a non-trivial simple graph. A dominating set in a graph is a set of vertices such that every vertex not in the set is adjacent to at least one vertex in the set. A subset  is a minimum neighborhood dominating set if  is a dominating set and if for every  holds. The minimum cardinality of the minimum neighborhood dominating set of a graph  is called as minimum neighborhood dominating number and it is denoted by  . A minimum neighborhood dominating set is a dominating set where the intersection of the neighborhoods of all vertices in the set is as small as possible, (i.e., ). The minimum neighborhood dominating number, denoted by , is the minimum cardinality of a minimum neighborhood dominating set. In other words, it is 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
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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Publication Date
Sat Jan 01 2011
Journal Name
Journal: Ibn Al-haitham Journal For Pure And Applied Sciences
A Study the effect the direction of the distribution of lighting to improve Images in different lighting by using technique adaptive histogram equalization
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Publication Date
Wed Oct 01 2008
Journal Name
Journal Of Educational And Psychological Researches
البرمجة اللغوية العصبية(NLP)
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* مشكلة البحث والحاجة اليه:

تأتي أهمية هذا العلم وقوته ومدى الحاجة اليه لكل الناس وخاصة اللذين يريدون أن يغيروا عاداتهم السيئة ويأثروا في غيرهم ، أذ اكد المفكرون والقادة والمصلحون ورجال التربية أنه يجب على الإنسان ان يكون مثابراً ومجتهداً ومتقناً لعمله ، ومنظماً لوقته الى اخر القائمة الطويلة من مفردات الجودة ولم يقولوا كيف يمكن للانسان ان يفعل ذلك ؟ أن علم الهندسة النفسية استطاع ان يجيب.&nbsp

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Mon Oct 01 2018
Journal Name
Ieee Transactions On Network Science And Engineering
A Resource Allocation Mechanism for Cloud Radio Access Network Based on Cell Differentiation and Integration Concept
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