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Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convolutional neural network that uses other activation functions (exponential linear unit (ELU), rectified linear unit (ReLU), Swish, Leaky ReLU, Sigmoid), and the result is that utilizing CWNN gave better results for all performance metrics (accuracy, sensitivity, specificity, precision, and F1-score). The results obtained show that the prediction accuracies of CWNN were 99.97%, 99.9%, 99.97%, and 99.04% when using wavelet filters (rational function with quadratic poles (RASP1), (RASP2), and polynomials windowed (POLYWOG1), superposed logistic function (SLOG1)) as activation function, respectively. Using this algorithm can reduce the time required for the radiologist to detect whether a patient has COVID or not with very high accuracy.</p>

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
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       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

         

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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Publication Date
Wed May 03 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Designing Feed Forward Neural Network for Solving Linear VolterraIntegro-Differential Equations
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The aim of this paper, is to design multilayer Feed Forward Neural Network(FFNN)to find the approximate solution of the second order linear Volterraintegro-differential equations with boundary conditions. The designer utilized to reduce the computation of solution, computationally attractive, and the applications are demonstrated through illustrative examples.

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Publication Date
Fri Apr 28 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Design Optimal Neural Network for Solving Unsteady State Confined Aquifer Problem
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Tue Sep 01 2020
Journal Name
Asian Journal Of Pharmacy And Pharmacology
Clinical manifestations and maternal outcomes of COVID-19 in pregnancy: A systematic review
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Publication Date
Sat Oct 31 2020
Journal Name
The Egyptian Journal Of Otolaryngology
Incidence and recovery of smell and taste dysfunction in COVID-19 positive patients
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Abstract<sec> <title>Background

This study aims to find the chemosensitive dysfunction incidence in COVID-19-positive patients and its recovery.

We collected the data from sixty-five patients, all COVID-19 positive, quarantined in-hospital between 5 April 2020 and 17 May 2020, by a questionnaire distributed in the quarantine ward.

Results

Smell dysfunction appeared in 89.23% with or without other symptoms of COVID-19. 39.66% of them recovered the sense of smell. Taste dysfunction found in 83.08% patients with other COVID-19 symptoms. Only 29.63% of them recovered. The recovery took 1–3 weeks, and most

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Publication Date
Sun Jan 01 2023
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte
THE IMPACT OF COVID-19 ON FOOTBALL CLUB STOCK INTEGRATION AND PORTFOLIO DIVERSIFICATION
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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Realizing the personality traits of Bisha University Employees during the Covid-19 pandemic
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The post-Corona Covid-19 world is not the world before it, the problem of perception of personality traits with two axes: the characteristics of psychological and social compatibility, and the second aspect the mental disorder during the pandemic, and the accompanying precautions and prohibitions during the academic year 2020 AD. The aim of the research is to reveal the perception of the personal characteristics of Bisha University employees (students and faculty) during the Corona Covid-19 pandemic, and to reveal statistically significant differences in the perception of the personality traits of Bisha’s members during the Covid 19 according to the scientific qualification variables (female students -faculty members),  marital st

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Publication Date
Sun Jan 01 2023
Journal Name
Česká A Slovenská Farmacie
Hyperferritinemia as a factor associated with poor prognosis in COVID-19 patients
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Worldwide, hundreds of millions of people have been infected with COVID-19 since December 2019; however, about 20% or less developed severe symptoms. The main aim of the current study was to  assess  the  relationship  between  the  severity of Covid-19 and different clinical and laboratory parameters. A total number of 466 Arabs have willingly joined this prospective cohort. Out of the total number, 297 subjects (63.7%) had negative COVID-19 tests, and thus, they were recruited as controls, while 169 subjects (36.3%) who tested positive for COVID-19 were enrolled as cases. Out of the total number of COVID-19 patients, 127 (75.15%) presented with mild symptoms, and 42 (24.85%) had severe symptoms. The age range for the partic

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