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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
Mon Jul 01 2013
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Prevalence of Hypertension in Deep and Lobar Intracerebral Hemorrhage in a Group of Iraqi Patients
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Background: Non-traumatic Intracerebral Hemorrhage (ICH) results from rupture of blood vessels in the brain. ICH categories can also be considered as being either lobar in location or within the deep white matter. Although hypertension is a major risk factor for ICH in general[11], it is commonly considered to be associated more with patients having deep than with those having lobar haemorrhage.
Objectives: We investigate the relationship between hypertension and deep versus lobar intracerebral hemorrhage (ICH).
Methods: a retrospective review of records of 163 patients aged 18-89 years admitted to Al-Kadhimiya Teaching Hospital (January 2008 - October 2010) and diagnosed with ICH.
Results: There was no significant relationship

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Publication Date
Sun Jan 03 2010
Journal Name
Journal Of The Faculty Of Medicine Baghdad
The use of brain lab navigator in the management of small deep seated brain tumors.
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Background: A comparism study for management of deep seated small brain tumors less than 4 cm in the 3 diameters between cases managed by Brain lab navigator and those without it.
Patients and methods: We took 20 patients from the retrospecture data before the use of Navigator in our country compared with the 20 patients managed after the use of navigator in our hospital (specialized surgical hospital) in the neuro-surgical. Unit since 2002 till now. From 1/8/2002 till 31/12/2007 the study included the type of tumor & surgery & the result of surgery & time & complications ((morbidity & mortality)).
Results: There was a significant increase of the safety of surgery by using the navigator

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Publication Date
Fri May 31 2019
Journal Name
Journal Of Engineering
WSN-WCCS: A Wireless Sensor Network Wavelet Curve Ciphering System
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With wireless sensor network (WSN) wide applications in popularity, securing its data becomes a requirement. This can be accomplished by encrypting sensor node data. In this paper a new an efficient symmetric cryptographic algorithm is presented. This algorithm is called wireless sensor network wavelet curve ciphering system (WSN-WCCS).  The algorithm idea based on discrete wavelet transformation to generate keys for each node in WSN.  It implements on hierarchical clustering WSN using LEACH protocol. Python programming language version 2.7 was used to create the simulator of WSN framework and implement a WSN-WCCS algorithm. The simulation result of the proposed WSN-WCCS with other symmetric algorithms has show

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Publication Date
Fri Jun 16 2023
Journal Name
Acta Scientiarum Polonorum Administratio Locorum
An analysis of Baghdad’s masterplans based on the development of green areas
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Motives: Baghdad is the capital city and an important political, administrative, social, cultural and economic centre of Iraq. Baghdad’s growth and development has been significantly influenced by efforts to accommodate various needs of its steadily growing population. Uncontrolled population and urban growth have exerted negative effects in numerous dimensions, including environmental sustainability because urban expansion occurred in green spaces within the city and the surrounding areas.Aim: The aim of this study was to examine the planning solutions in Baghdad’s green areas in the past and at present, and to identify the key changes in the city’s green areas, including changes in the ratio of green urban spaces to the tota

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Feature Extraction of Human Facail Expressions Using Haar Wavelet and Neural network
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One of the challenging and active research topics in the recent years is Facial Expression. This paper presents the method to extract the features from the facial expressions from still images. Feature extraction is very important for classification and recognition process. This paper involve three stages which contain capture the images, pre-processing and feature extractions. This method is very efficient in feature extraction by applying haar wavelet and Karhunen-Loève Transform (KL-T). The database used in this research is from Cohen-Kanade which used six expressions of anger, sadness fear, happiness, disgust and surprise. Features that have been extracted from the image of facial expressions were used as inputs to the neural networ

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Publication Date
Wed Apr 01 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Hormonal and mineral imbalance effect on bone resorption in predialysis iraqi patients with chronic kidney disease
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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
Smart Routing Protocol Algorithm Using Fuzzy Artificial Neural Network OSPF
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The OSPF cost is proportionally indicated the transmitting packet overhead through a certain interface and inversely proportional to the interface bandwidth. Thus, this cost may minimized by direct packet transmitting to the other side via various probable paths simultaneously. Logically, the minimum weight path is the optimum path. This paper propose a novel Fuzzy Artificial Neural Network to create Smart Routing Protocol Algorithm. Consequently, the Fuzzy Artificial Neural Network Overlap has been reduced from (0.883 ms) to (0.602 ms) at fuzzy membership 1.5 to 4.5 respectively. This indicated the transmission time is two-fold faster than the standard overlapping time (1.3 ms).

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Publication Date
Wed Jan 02 2013
Journal Name
Journal Of The Faculty Of Medicine Baghdad
SYNTAX Scoring In Patients with Coronary Artery Disease and Its Effect on Mode of Revascularization , Single Center Experience.
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Background: revascularization therapy for patients with left main (LM) and/or three vessel coronary disease is a matter of argument for long a time whether bypercutaneous coronary angiography orcoronary artery bypass grafting. SYNTAX trial was designed to assess the optimal revascularization strategy between percutaneous coronary intervention and coronary artery bypass grafting, for patients with left main stem coronary artery disease and/or 3-vessel coronary disease.

Aim: To estimate the complexity of coronary artery disease in patients referred to a tertiary Iraqi cardiac center and its effect on mode of revascularization.

Patients and Method: Ninety nine patients who w

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