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Classification of Cardiac Arrhythmia using ID3 Classifier Based on Wavelet Transform
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Accurate detection of Electro Cardio Graphic (ECG) features is an important demand for medical purposes, therefore an accurate algorithm is required to detect these features. This paper proposes an approach to classify the cardiac arrhythmia from a normal ECG signal based on wavelet decomposition and ID3 classification algorithm. First, ECG signals are denoised using the Discrete Wavelet Transform (DWT) and the second step is extract the ECG features from the processed signal. Interactive Dichotomizer 3 (ID3) algorithm is applied to classify the different arrhythmias including normal case. Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia Database is used to evaluate the ID3 algorithm. The experimental result shows that the accuracy of ID3 is 92% in the case of Haar transform and 94% with Daubeshies4 transform.

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Mon Feb 25 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Using Classification of Brown risks in Evaluation of the internal control system: Application Research in Karbala University
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Internal control system is a safety valve that preserves economic units assets and ensure the accuracy of financial data, as well as to obligation in the laws, regulations, administrative policies ,and improve the efficiency, effectiveness and economic of operation, so it has become imperative for these units attention to internal and developed control system The research problem in exposure the economic units when the exercise of their business to many of the risks to growth or hinder the achievement of its objectives and the risks (financial, operational, strategy, risk) and not it rely on risk Assessment according to modern scientific methods, as in Brown's risk Classification, Which led to the weakness of the internal control identif

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Publication Date
Sat Dec 01 2012
Journal Name
2012 Ieee-embs Conference On Biomedical Engineering And Sciences
Compatibility of mother wavelet functions with the electroencephalographic signal
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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
A Novel Approach to Improving Brain Image Classification Using Mutual Information-Accelerated Singular Value Decomposition
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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
Alterations of Obestatin, Cardiac Markers and Lipid Profile Levels in Type 2 Diabetes Mellitus
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The current investigation aimed to test the alterations of the levels of obestatin hormone, lipid profile and cardiac function markers in relation to hyperglycemia in patients with non-insulin diabetes mellitus. The study included 118 diabetic subjects (56 males, 62 females) and 60 healthy non-diabetic subjects (30 males, 30 females). Diabetic and healthy subjects were age-matched. Serum levels of obestatin, lipid profile markers including total cholesterol (STC), triglycerides (STG), low and high density lipoproteins (LDL-C and HDL-C), as well as cardiac function markers including, creatine kinase and lactate dehydrogenase enzymes were determined in all subjects. The findings revealed a remarkable decrease in the level of serum obestati

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Refractive Index Sensor Based on Micro- Structured Optical Fibers with Using Finite Element Method
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In this paper a refractive index sensor based on micro-structured optical fiber has been proposed using Finite Element Method (FEM). The designed fiber has a hexagonal cladding structure with six air holes rings running around its solid core.  The air holes of fiber has been infiltrated  with different liquids such as water , ethanol, methanol, and toluene then sensor characteristics like ; effective refractive index , confinement loss, beam profile of the fundamental mode, and sensor resolution are investigated by employing the FEM. This designed sensor characterized by its low confinement loss and high resolution so a small change in the analyte refractive index could be detect which is could be useful to detect the change of

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Digital Data Encryption Using a Proposed W-Method Based on AES and DES Algorithms
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This paper proposes a new encryption method. It combines two cipher algorithms, i.e., DES and AES, to generate hybrid keys. This combination strengthens the proposed W-method by generating high randomized keys. Two points can represent the reliability of any encryption technique. Firstly, is the key generation; therefore, our approach merges 64 bits of DES with 64 bits of AES to produce 128 bits as a root key for all remaining keys that are 15. This complexity increases the level of the ciphering process. Moreover, it shifts the operation one bit only to the right. Secondly is the nature of the encryption process. It includes two keys and mixes one round of DES with one round of AES to reduce the performance time. The W-method deals with

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Solving Nonlinear Boundary Value Problem Arising of Natural Convection Porous Fin By Using the Haar Wavelet Collocation Method and Temimi and Ansari Method
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      In this article, the boundary value problem of convection propagation through the permeable fin in a natural convection environment is solved by the Haar wavelet collocation method (HWCM). We also compare the solutions with the application of a semi-analytical method , namely the Temimi and Ansari (TAM), that is characterized by accuracy and efficiency.The proposed method is also characterized by simplicity and efficiency. The possibility of applying the proposed method to many types of  linear or nonlinear ordinary and partial differential equations.

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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