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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 Sep 20 2025
Journal Name
مجلة آداب المستنصرية
Translating the Syntactic Features of Legal Texts from English into Arabic
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This paper examines some syntactic features of English legal texts, and the changes that may be reflected on these features when they are translated into Arabic. For example, passivization, nominalization, complex sentences and modality. The researcher tries to demonstrate why it is difficult to suggest a specific translation of each syntactic feature, especially the modal verbs. The researcher also attempts to provide translations for some legal sentences written in some charters and international organizations. The descriptive methodology is used to identify the characteristics of these syntactic features in order to provide a proper translation of each legal sentence. It has been concluded that the translator has to be aware of the preci

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Comparative Study of Image Denoising Using Wavelet Transforms and Optimal Threshold and Neighbouring Window
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NeighShrink is an efficient image denoising algorithm based on the discrete wavelet
transform (DWT). Its disadvantage is to use a suboptimal universal threshold and identical
neighbouring window size in all wavelet subbands. Dengwen and Wengang proposed an
improved method, which can determine an optimal threshold and neighbouring window size
for every subband by the Stein’s unbiased risk estimate (SURE). Its denoising performance is
considerably superior to NeighShrink and also outperforms SURE-LET, which is an up-todate
denoising algorithm based on the SURE. In this paper different wavelet transform
families are used with this improved method, the results show that Haar wavelet has the
lowest performance among

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Publication Date
Tue Sep 30 2025
Journal Name
Medical Journal Of Babylon
Pompe Disease (A Rare Metabolic Disease) in Basrah, the South of Iraq
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Pompe disease is a progressive, multisystemic, debilitating, often fatal neuromuscular disease caused by a pathogenic variant in the acid α-glucosidase gene leading to GAA enzyme deficiency and lysosomal glycogen accumulation. Objectives: This study aimed to determine the prevalence of early onset Pompe disease in Basra, using the dried blood spot (DBS) as a screening tool, also to determine the spectrum of presentation. Materials and Methods: In a prospective study conducted in Basrah, Iraq, from October 2021 to September 2023, all infants with a family member diagnosed as a case of Pompe disease, hypotonia, or ventricular hypertrophy referred to the pediatric cardiology unit in Basra Cardiac Hospital were subjected to echocardiographic e

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Publication Date
Sat May 04 2024
Journal Name
Sar Journal Of Pathology And Microbiology
Association between Celiac Disease and Human Leukocyte Antigen
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Coeliac disease is an immunologically mediated disease of the small intestinal mucosa, characterized by flattening of the small intestinal villi, increased numbers of intra-epithelial lymphocytes and inflammatory cell infiltrates in the lamina propria, resulting in gut damage and nonspecific malabsorption of nutrients. The disease is elicited by ingestion of gluten, a protein found in several cereals, principally wheat, but also barley and to a lesser extent, oats. Successful treatment is avoidance of dietary gluten. Long-standing evidence suggests a T-cell-mediated response to peptides derived from the gliadin fraction of wheat gluten, leading to immunologically mediated intestinal injury in genetically susceptible individuals. The

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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
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Excision of Soft Tissue Oral Lesions by 810 nm Diode Laser
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The present study was conducted on 20 patients suffering from different types of lesion like
pyogenic granuloma, peripheral giant cell granuloma, mucoceles, pregnancy tumour, Fordyce's granules
and irritating fibroma.The cases were selected from outpatient clinic of the Al Kydhemya Teaching
Hospital. Patients were treated by diode laser (810±20 nm) at the affected areas of the oral cavity with
continuous contact focused mode until excision of the lesion with coagulation of the oozing area after
excision. Patients were followed up after 2 days, 7 days and 2 weeks to assess healing process and any
post operative complication. Some of undiagnosed lesion sent for histopathological examination. No
serious complications w

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Programming a Pneumatic Processes Sequence based on PLC by Demonstration
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Abstract

Pneumatic processes sequence (PPS) is used widely in industrial applications. It is common to do a predetermined PPS to achieve a specific larger task within the industrial application like the PPS achieved by the pick and place industrial robot arm. This sequence may require change depending on changing the required task and usually this requires the programmer intervention to change the sequence’ sprogram, which is costly and may take long time. In this research a PLC-based PPS control system is designed and implemented, in which the PPS is programmed by demonstration. The PPS could be changed by demonstrating the new required sequence via the user by following simple series of manual steps without h

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Detection of Physical and Chemical Parameters Using Water Indices (NDWI, MNDWI, NDMI, WRI, and AWEI) for Al-Abbasia River in Al-Najaf Al-Ashraf Governorate Using Remote Sensing and Geographic Information System (GIS) Techniques
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The purpose of this study was to find out the connection between the water parameters that were examined in the laboratory and the water index acquired from the examination of the satellite image of the study area. This was accomplished by analysing the Landsat-8 satellite picture results as well as the geographic information system (GIS). The primary goal of this study is to develop a model for the chemical and physical characteristics of the Al-Abbasia River in Al-Najaf Al-Ashraf Governorate. The water parameters employed in this investigation are as follows: (PH, EC, TDS, TSS, Na, Mg, K, SO4, Cl, and NO3). To collect the samples, ten sampling locations were identified, and the satellite image was obtained on the

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