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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
Sat Aug 30 2025
Journal Name
Iraqi Journal Of Science
A Face Mask Detection Method in the Era of the COVID-19 Pandemic Based on GLCM and YOLO
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In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and

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Publication Date
Sun Oct 30 2022
Journal Name
Revista Iberoamericana De Psicologia Del Ejercicio Y El Deporte
THE EFFECT OF (HIT) TRAINING ON IMMUNE GLOBULINS AND WHITE BLOOD CELLS FOR AMATEUR WEIGHTLIFTERS AFTER THE RETURN OF ACTIVITY FROM THE MANDATORY QUARANTINE FOR THE COVID-19 EPIDEMIC
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The aim of the research is to identify an appropriate training method that raises the levels of immune globulins (IgA, IgM, IgG) and white blood cells and the effect of training by (HIT) method using resistance (weights) as a training curriculum that increases immunity and ensures the continuation of the pills after the return of activity from the stone The response to the Covid-19 epidemic among amateur weightlifters, the researchers relied on the method of trace analysis in an experimental way by conducting a pre-, medial and post-test with the same experimental one agroup on a sample of amateur weightlifters in the Fury private hall for weightlifting and body building in Adhamiya, the number of sample members reached (15 players) who int

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Publication Date
Sun May 15 2022
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Computational Thinking (CT) Among University Students
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Publication Date
Tue May 24 2022
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Computational Thinking (CT) Among University Students
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Computational Thinking (CT) is very useful in the process of solving everyday problems for undergraduates. In terms of content, computational thinking involves solving problems, studying data patterns, deconstructing problems using algorithms and procedures, doing simulations, computer modeling, and reasoning about abstract things. However, there is a lack of studies dealing with it and its skills that can be developed and utilized in the field of information and technology used in learning and teaching. The descriptive research method was used, and a test research tool was prepared to measure the level of (CT) consisting of (24) items of the type of multiple-choice to measure the level of "CT". The research study group consists of

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Publication Date
Sun Sep 30 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
FINGERPRINTS MATCHING USING THE ENERGY AND LOW ORDER MOMENT OF HAAR WAVELET SUBBANDS
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Fingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on

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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Comparative analysis of parameter estimation methods for Meixner process using wavelet packet transform
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The current research creates an overall relative analysis concerning the estimation of Meixner process parameters via the wavelet packet transform. Of noteworthy presentation relevance, it compares the moment method and the wavelet packet estimator for the four parameters of the Meixner process. In this paper, the research focuses on finding the best threshold value using the square root log and modified square root log methods with the wavelet packets in the presence of noise to enhance the efficiency and effectiveness of the denoising process for the financial asset market signal. In this regard, a simulation study compares the performance of moment estimation and wavelet packets for different sample sizes. The results show that wavelet p

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Publication Date
Sun Jun 01 2014
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Medical Image Compression using Wavelet Quadrants of Polynomial Prediction Coding & Bit Plane Slicing
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Publication Date
Mon Jan 01 2018
Journal Name
Matec Web Of Conferences
Investigation of surface area of lakes and marshes from satellite images by using remote sensing and geographic information system integration in Iraq
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Water level and distribution is very essential in almost all life aspects. Natural and artificial lakes represent a large percentage of these water bodies in Iraq. In this research the changes in water levels are observed by calculating the areas of five different lakes in five different regions and two different marshes in two different regions of the country, in a period of 12 years (2001 - 2012), archived remotely sensed images were used to determine surface areas around lakes and marshes in Iraq for the chosen years . Level of the lakes corresponding to satellite determined surface areas were retrieved from remotely sensed data .These data were collected to give explanations on lake level and surface area fluctuations. It is imp

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

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Publication Date
Sun Apr 09 2023
Journal Name
Bmj
COVID-19 Vaccine Uptake And Its’ Associated Factors among general population In Basmaia City in Baghdad 2022
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Abstract<sec><title>Objective

Vaccination is a vital cornerstone of public health, which has saved countless lives throughout history. Therefore, achieving high vaccination uptake rates is essential for successful vaccination programs. Unfortunately, vaccine uptake has been hindered by deferent factors and challenges. The objective of this study is to assess COVID-19 vaccine uptake and associated factors among the general population.

Methods

This study is a descriptive cross-sectional study conducted in Basmaia city, Baghdad from June to October 2022. Data were collected through a semi-structured questionnaire using multi-stag

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