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MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the use of Gray Level Co-occurrence Matrix (GLCM) features and DBN classifier provides 98.26% accuracy with the two specific classes were tested. Improvements/Applications: AD is a neurological condition affecting the brain and causing dementia that may affect the mind and memory. The disease indirectly impacts more than 15 million relatives, companions and guardians. The results of the present research are expected to help the specialist in decision making process.

Publication Date
Tue Sep 19 2017
Journal Name
Al-academy
Process of artistic conception of nature's images Between becoming and buration
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This research deals with process of artistic conception of nature's images between becoming and buration, as an attempt to transfer the philosophical concepts to art via it's structural applications in forming the picture, due to the importance of these concepts which might be engaged with the vision of the artist in his own and subjective contention with the nature. The research consists of four chapters, first one included the problem of the research, importance, need to the research and the aim of the research represented by process of artistic conception of nature's images between becoming  and buration. Also included the limits of research and most important terms. Second chapter included theoretical frame that consists of thre

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Publication Date
Wed Nov 13 2024
Journal Name
Innovation And Technological Advances For Sustainability
Ecofriendly method to control fusarium wilt on tomato
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Fusarium wilt causes economic losses on tomatoes every year. Thus, a variety of chemicals have been used to combat the disease. Pesticides have been effective in managing the disease, but they keep damaging the environment. Recently, eco-friendly approaches have been used to control plant diseases. This study aimed to achieve an environmentally safe solution using biological agents to induce systemic resistance in tomato plants to control Fusarium wilt disease caused by Fusarium oxysporum f.sp. lycopersici (FOL) in the greenhouse. The pathogen (FOL) has been molecularly confirmed and the biological agents have been isolated from the Iraqi environment. The effectiveness of the biological agents has been tested and confirmed. Results showed t

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Publication Date
Fri Oct 13 2023
Journal Name
Engineering, Technology & Applied Science Research
The Experimental and Theoretical Effect of Fire on the Structural Behavior of Laced Reinforced Concrete Deep Beams
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A Laced Reinforced Concrete (LRC) structural element comprises continuously inclined shear reinforcement in the form of lacing that connects the longitudinal reinforcements on both faces of the structural element. This study conducted a theoretical investigation of LRC deep beams to predict their behavior after exposure to fire and high temperatures. Four simply supported reinforced concrete beams of 1500 mm, 200 mm, and 240 mm length, width, and depth, respectively, were considered. The specimens were identical in terms of compressive strength (  40 MPa) and steel reinforcement details. The same laced steel reinforcement ratio of 0.0035 was used. Three specimens were burned at variable durations and steady-state temperatures (one

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Publication Date
Sat Dec 01 2018
Journal Name
Al-nahrain Journal Of Science
Image Classification Using Bag of Visual Words (BoVW)
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In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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Publication Date
Sun Sep 01 2019
Journal Name
Dental Hypotheses
Possible Role of Statins on the Inflammatory Biomarkers in Patients With Periodontal Disease: A Cross-Sectional Study
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The aim of the present study was to demonstrate the possible role of statins on the inflammatory biomarkers in patients with periodontal disease (PD) This cross-sectional study involved 74 patients with PD and/or dyslipidemia divided into Group A: 34 patients with PD (nonstatins users); Group B: 40 patients with PD (statins users); and Group C: 30 healthy controls. Total cholesterol (TC), triglyceride (TG) and high-density lipoprotein, C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and malondialdehyde (MDA) were measured . Blood pressure prolife and indices of PD were evaluated in each group. Statistical analysis was conducted by using SPSS version 20.0.

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Publication Date
Sun Mar 15 2020
Journal Name
Journal Of Baghdad College Of Dentistry
The impact of histopathological celiac disease activity on dental enamel defects and dental caries
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Background: Celiac disease is an autoimmune chronic disease that affects the human’s intestine and subsequently reflects its effect on the entire body health by retardation the absorption and immune mediated complications cause the involvement of oral health. The present study intended to evaluate the impact of the histopathological disease activity upon dental enamel defects and dental caries.

Subjects and methods: Forty celiac-diseased patients aged 7-11 years were collected from 3 different teaching hospitals in Baghdad classified by means of the histopathological activity of the intestinal disease according to modified Marsh-Ros

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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Effect of Some Demographic Changes on Some Oral Immune Aspects in Periodontal Disease Patients
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Periodontal diseases (PD) are worldwide diseases of humans either in childhood or adults. The present study aimed to find the correlation between some demographic and saliva immunological factors including the determination of saliva TLR-2, IL6, CRP, and α- amylase in patients with periodontal diseases. For this purpose, 60 patients out of which 33were males and 27 were females participated in this study from different Dental treatment Centers (Amirya Specialized Dental Center and Almaamon Specialized Dental Center ) in Baghdad/ Iraq, for the period starting from November / 2021 to February / 2022. Both age ranges for patients and control are (13-70) years, and patients’ mean ages are 34.29±15.01. Additionally, the control speci

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Influence of A River Water Quality on The Efficiency of Water Treatment Using Artificial Neural Network
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Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and

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