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.
The purpose of this research is to identify the youth issues in Talk Shows in the Iraqi satellite channels via monitoring a sample of episodes of the Talk Shows episodes which are concerned and analyzed the youth issues in the Iraqi satellite channels, namely, «Hala Shabab Program» at Al-Iraqia satellite Channel and «Shabab wa Banat Program» at Al-Sumaria satellite Channel by recording and re-watching them again. This research is classified as one of descriptive researches. The survey method was adopted in this study.
For this purpose, the researcher prepared an analysis form. The researcher de
... Show MoreThe increasing amount of educational data has rapidly in the latest few years. The Educational Data Mining (EDM) techniques are utilized to detect the valuable pattern so that improves the educational process and to obtain high performance of all educational elements. The proposed work contains three stages: preprocessing, features selection, and an active classification stage. The dataset was collected using EDM that had a lack in the label data, it contained 2050 records collected by using questionnaires and by using the students’ academic records. There are twenty-five features that were combined from the following five factors: (curriculum, teacher, student, the environment of education, and the family). Active learning ha
... Show MoreVoucher documents have become a very important information carrier in daily lives to be used in many applications. A certain class of people could exploit the trust and indulge in forging or tampering for short or long term benefits unlawfully. This holds a serious threat to the economics and the system of a nation. The aim of this paper is to recognize original voucher document through its contents. Forgery of voucher document could have serious repercussions including financial losses, so the signature, logo and stamp that are used to determine being a genuine or not by using multilevel texture analysis. The proposed method consists of several operations. First, detection and extraction of signature, logo and stamp images from original
... Show MoreThis paper presents on the design of L-Band Multiwavelength laser for Hybrid Time Division Multiplexing/ Wavelength Division Multiplexing (TDM/WDM) Passive Optical Network (PON) application. In this design, an L-band Mulltiwavelength Laser is designed as the downstream signals for TDM/WDM PON. The downstream signals ranging from 1569.865 nm to 1581.973 nm with 100GHz spacing. The multiwavelength laser is designed using OptiSystem software and it is integrated into a TDM/WDM PON that is also designed using OptiSystem simulation software. By adapting multiwavelength fiber laser into a TDM/WDM network, a simple and low-cost downstream signal is proposed. From the simulation design, it is found that the proposed design is suitable to be used
... Show MoreWe propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
... Show MoreAn investigation was conducted effect of addition co- solvent on solvent extraction process for two types of a lubricating oil fraction (spindle) and (SAE-30) obtained from vacuum distillation unit of lube oil plant of Daura Refinery. In this study two types of co-solvents ( formamide and N-methyl, 2, pyrrolidone) were blended with furfural to extract aromatic hydrocarbons which are the undesirable materials in raw lubricating oil, in order to improve the viscosity index, viscosity and yield of produced lubricating oil. The studied operating condition are extraction temperature range from 70 to 110 °C for formamide and 80 to 120 °C for N-methyl, 2, pyrrolidone, solvent to oil ratio range from 1:1 to 2:1 (wt./wt.) for furfural with form
... Show MoreThe reaction of LAs-Cl8 : [ (2,2- (1-(3,4-bis(carboxylicdichloromethoxy)-5-oxo-2,5- dihydrofuran-2-yl)ethane – 1,2-diyl)bis(2,2-dichloroacetic acid)]with sodium azide in ethanol with drops of distilled water has been investigated . The new product L-AZ :(3Z ,5Z,8Z)-2- azido-8-[azido(3Z,5Z)-2-azido-2,6-bis(azidocarbonyl)-8,9-dihydro-2H-1,7-dioxa-3,4,5- triazonine-9-yl]methyl]-9-[(1-azido-1-hydroxy)methyl]-2H-1,7-dioxa-3,4,5-triazonine – 2,6 – dicarbonylazide was isolated and characterized by elemental analysis (C.H.N) , 1H-NMR , Mass spectrum and Fourier transform infrared spectrophotometer (FT-IR) . The reaction of the L-AZ withM+n: [ ( VO(II) , Cr(III) ,Mn(II) , Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) and Hg(II)] has been i
... Show MoreThe dubbing process for the Foreign Dramas by the Kurdish language became a serious phenomenon in the Kurdish satellite TV, especially in the past few years. It attracted a wide audience, especially young adolescents. And prepared by some breakthrough hostile to Kurdish culture and value coordinated by others remedy for the structural gaps and lapses have, as a result of climate which is brought into existence globalization and secretions variety dimensional, saturated value and cognitive effects bearing a strong identity of its elements. From here, the problem of this research is the ambiguity of their role in a series of developmental processes Kurdish awareness of young people and the extent of the impact that caused it.
This
... Show MoreBreast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we
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