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Noise Modeling and Removal from Electrocardiogram Signals: A Study Using Wavelet Transform with Graphical User Interface
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The electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI) system is developed for visual representation and adaptive enhancement on noise modeling in ECG-based signal processing. Percentage root mean square difference (PRD) was measured between the modeled noisy signals and the samples of the original ECG. Moreover, cross correlation (XCorr) and root mean square error (RMSE) were performed between the noisy ECG signals and the denoised ones which resulted from WT denoising technique initially to evaluate the effectiveness of the WT denoising technique. The results show that the WT was successfully removed different types of proposed models of noises. The PRD was reasonable and are within the acceptable range, which is less than 50%, with 17% for BW and 47% for PLI indicating that the models and methods used for prediction are ideal for high precision signal applications. This study will help medical doctors, clinicians, physicians, and technicians to eliminate different types of noise.

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Publication Date
Sun Dec 25 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synthesis, Molecular Docking Study and Cytotoxicity Evaluation of some Quinazolinone Derivatives as Nonclassical Antifolates and Potential Cytotoxic Agents
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Abstract

A series of new 4(3H)-quinazolinone derivatives (S1-S4) were synthesized and characterized   by FTIR,1HNMR and 13CNMR .Their cytotoxic activity against a set of human cancer cell lines MCF-7 (breast) and A549 (lung) was evaluated using MTT assay. To detect their selectivity toward cancer cells, the compounds were also tested against epithelial cells derived from normal human fibroblast (NHF). Methotrexate (MTX) was used as a reference for comparison . All the tested compounds exhibited toxicity against the normal cells lower than cancer cells. All the tested compounds displayed higher cytotoxicity against lung cancer cell line (A549) than MTX with the most

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Publication Date
Thu May 24 2018
Journal Name
Aip Conference Proceedings
The study effect of weight fraction on thermal and electrical conductivity for unsaturated polyester composite alone and hybrid
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In this research prepared two composite materials , the first prepared from unsaturated polyester resin (UP) , which is a matrix , and aluminum oxide (Al2O3) , and the second prepared from unsaturated polyester resin and aluminum oxide and copper oxide (CuO) , the two composites materials (Alone and Hybrid) of percentage weight (5,10,15)% . All samples were prepared by hand layup process, and study the electrical and thermal conductivity. The results showed decrease electrical conductivity from (10 - 2.39) ×10-15 for (Up+ Al2O3) and from (10 - 2.06)×10-15 for (Up+ Al2O3+ CuO) .But increase thermal conductivity from( 0.17 - 0.505) for (Up+ Al2O3) and from (0.17 - 0.489) for (Up+ Al2O3+ CuO).

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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Publication Date
Tue Nov 21 2017
Journal Name
Lecture Notes In Computer Science
Emotion Recognition in Text Using PPM
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In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Bilinear System Identification Using Subspace Method
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In this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white . Simulation of these algorithms shows that the " four-block " gives fast convergence and the dimensions of the matrices involved are significantly smaller so that the computational complexity is lower as a comparison with " three-block " algorithm .

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Reinforce organizational communication using Information Technology
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Abstract<p>The purpose of this research is to enhance the role of organizational communication in organizations using IT technologies. The results showed that there is a strong relationship with information technology technologies in enhancing the role of organizational communication, which in turn helps to improve the performance of organizations in general</p>
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Publication Date
Sun Mar 03 2024
Journal Name
The Science Teacher
Using Scenarios to Assess Student Learning
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Sat Jan 23 2016
Journal Name
Computer Science &amp; Information Technology ( Cs &amp; It )
Modelling Dynamic Patterns Using Mobile Data
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Publication Date
Fri Oct 01 2010
Journal Name
Iraqi Journal Of Physics
Smoothing Image using Adaptive Median Filter
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Median filter is adopted to match the noise statistics of the degradation seeking good quality smoothing images. Two methods are suggested in this paper(Pentagonal-Hexagonal mask and Scan Window Mask), the study involved modified median filter for improving noise suppression, the modification is considered toward more reliable results. Modification median filter (Pentagonal-Hexagonal mask) was found gave better results (qualitatively and quantitatively ) than classical median filters and another suggested method (Scan Window Mask), but this will be on the account of the time required. But sometimes when the noise is line type the cross 3x3 filter preferred to another one Pentagonal-Hexagonal with few variation. Scan Window Mask gave bett

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