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Multilevel Analysis to Recognize Original Voucher from Faked Voucher
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Voucher 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 voucher document by using auto crop method. Second, each image is processed in allotted level. Third, the voucher document is classified depending on a result of each level to determine being a genuine or not. Accuracy of 94% for identification process and 95% for verification process were achieved.

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Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Some Statistical Characteristics Depending on the Maximum Variance of Solution of Two Dimensional Stochastic Fredholm Integral Equation contains Two Gamma Processes
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   In this paper, we find the two solutions of two dimensional stochastic Fredholm integral equations contain two gamma processes differ by the parameters in two cases and equal in the third are solved by the Adomain decomposition method. As a result of the solutions probability density functions and their variances at the time t are derived by depending upon the maximum variances of each probability density function with respect to the three cases. The auto covariance and the power spectral density functions are also derived. To indicate which of the three cases is the best, the auto correlation coefficients are calculated.

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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
The Influence of the Magnetic Abrasive Finishing System for Cylindrical Surfaces on the Surface Roughness and MRR
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Abstract

Magnetic abrasive finishing (MAF) is one of the advanced finishing processes, which produces a high level of surface quality and is primarily controlled by a magnetic field. This paper study the effect of the magnetic abrasive finishing system on the material removal rate (MRR) and surface roughness (Ra) in terms of magnetic abrasive finishing system for eight of input parameters, and three levels according to Taguchi array (L27) and using the regression model to analysis the output (results). These parameters are the (Poles geometry angle, Gap between the two magnetic poles, Grain size powder, Doze of the ferromagnetic abrasive powder, DC current, Workpiece velocity, Magnetic poles velocity, and Finishi

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Publication Date
Thu Mar 01 2012
Journal Name
Advances In Materials Physics And Chemistry
Study the Effect of Irradiation Time and HF Concentration on Porosity of Porous Silicon and Study Some of the Electrical Properties of Its Based Device
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ABSTRACT Porous silicon has been produced in this work by photochemical etching process (PC). The irradiation has been achieved using ordinary light source (150250 W) power and (875 nm) wavelength. The influence of various irradiation times and HF concentration on porosity of PSi material was investigated by depending on gravimetric measurements. The I-V and C-V characteristics for CdS/PSi structure have been investigated in this work too.

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Social Media Application for Recruitment Using Pythagorean Fuzzy
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    The growth of social media is now utilized all over the world. In the past several years social media is used to communicate between person for information sharing and entertainment but now social media is also used for the hiring. This work collects data through questionnaire and online dataset on the recruitment process for three social media i.e. Facebook, Twitter, and LinkedIn. Pythagorean Fuzzy Relation (PFR) is an expansion of both Fuzzy Relationship and Fuzzy Intuitionist Relationship. The Pythagorean fuzzy set is a modern conceptual structure with greater capacity to deal with imprecision rooted in decision making. So we used this technique to identify a social media containing more number of positive respondents in recrui

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Recording of an ECG, PCG, and PPG for Feature Extractions
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Recently, the development of the field of biomedical engineering has led to a renewed interest in detection of several events. In this paper a new approach used to detect specific parameter and relations between three biomedical signals that used in clinical diagnosis. These include the phonocardiography (PCG), electrocardiography (ECG) and photoplethysmography (PPG) or sometimes it called the carotid pulse related to the position of electrode.

Comparisons between three cases (two normal cases and one abnormal case) are used to indicate the delay that may occurred due to the deficiency of the cardiac muscle or valve in an abnormal case.

The results shown that S1 and S2, first and second sound of the

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Publication Date
Mon Jan 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
ON-Line MRI Image Selection and Tumor Classification using Artificial Neural Network
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When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

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Publication Date
Sun Jan 01 2017
Journal Name
Iec2017 Proceedings Book
Improving TF-IDF with Singular Value Decomposition (SVD) for Feature Extraction on Twitter
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Publication Date
Fri Jul 18 2014
Journal Name
International Journal Of Computer Applications
3-Level Techniques Comparison based Image Recognition
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Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
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

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Research on Emotion Classification Based on Multi-modal Fusion
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Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

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