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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
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study
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Publication Date
Sat Dec 17 2022
Journal Name
Iraqi Journal Of Laser
PDF Biosensing technique for detection of H.pylori bacteria: Israa M.L. SaQari*, Layla M.H. Al-ameri
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Abstract :H.pylori is an important cause of gastric duodenal disease, including gastric ulcers, Mucosa-associated lymphoid tissue (MALT), and gastric carcinoma. biosensors are becoming the most extensively studied discipline because the easy, rapid, low-cost, highly sensitive, and highly selective biosensors contribute to advances in next-generation medicines such as individualized medicine and ultrasensitive point-of-care detection of markers for diseases.  Five of ten patients diagnosed with H.pylori ranging in age from 15–85 participated in this research. who [gastritis, duodenitis, duodenal ulcer (DU), and peptic ulcer (PU)] Suspected H.pylori colonies w

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Voice Identification Using MFCC and Vector Quantization
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The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi

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Publication Date
Thu Jul 31 2025
Journal Name
Lecture Notes In Networks And Systems
Integration Between Network Analysis and Business Process Reengineering and Their Role in Reduce Project Costs/Applied Research in the Oil Projects Company
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Publication Date
Thu May 18 2023
Journal Name
College Of Islamic Sciences
Human right rule in self-defense And its prohibitions in Islamic jurisprudence
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God, may He be glorified and exalted be He, has given every human being the right to life and a dignified life, and has warned against transgression against any of its sanctities without a legitimate right. No one, regardless of his status or authority, can deprive a person of his rights that the Sharia came to preserve, and whoever does that has declared all people to war, as all humanity is in solidarity. In raising the hand that is simplified to harm a person and oppress him unjustly and exalted in the land.
If this is the case, the Sharia came to establish the right of people, groups and individuals, to defend their sanctities, preserve their security, recover their usurped rights, repel the aggression of the aggressors, and oppre

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Publication Date
Sat Aug 27 2022
Journal Name
International Journal Of Health Sciences
Heterocyclic compounds-based liquid crystals: Synthesis and mesomorphic properties
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A series of liquid crystals comprising a heterocyclics dihydro pyrrole and 1,2,3-triazole rings [VII]-[X] were synthesized by many steps starting from a reaction of 3,3'-dimethyl-[1,1'-biphenyl]- 4,4'-diamine with chloroacetyl chloride in a mixture of solutions DMF and TEA to synthesise the compounds [I], then the compounds [I] reacted with malononitrile in 1,4-dioxane and TEA solutions to produce compounds [II], then the first step is repeated with compound [II] where it reacted with chloroacetyl chloride in mixture of DMF and TEA to give compound [III], this compound reacted with sodium azide in the presence of sodium chloride and DMF as solvent to produce the compound [IV], which reacted with acrylic acid by a 1.3 dipolar reaction in sol

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Pilot Based Channel Estimation and Synchronization in OFDM System
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Channel estimation and synchronization are considered the most challenging issues in Orthogonal Frequency Division Multiplexing (OFDM) system. OFDM is highly affected by synchronization errors that cause reduction in subcarriers orthogonality, leading to significant performance degradation. The synchronization errors cause two issues: Symbol Time Offset (STO), which produces inter symbol interference (ISI) and Carrier Frequency Offset (CFO), which results in inter carrier interference (ICI). The aim of the research is to simulate Comb type pilot based channel estimation for OFDM system showing the effect of pilot numbers on the channel estimation performance and propose a modified estimation method for STO with less numb

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Multifocus Images Fusion Based On Homogenity and Edges Measures
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Image fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM,

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Unmasking Deepfakes Based on Deep Learning and Noise Residuals
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The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
IMPROVED IMAGE COMPRESSION BASED WAVELET TRANSFORM AND THRESHOLD ENTROPY
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In this paper, a method is proposed to increase the compression ratio for the color images by
dividing the image into non-overlapping blocks and applying different compression ratio for these
blocks depending on the importance information of the block. In the region that contain important
information the compression ratio is reduced to prevent loss of the information, while in the
smoothness region which has not important information, high compression ratio is used .The
proposed method shows better results when compared with classical methods(wavelet and DCT).

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