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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
Tue Dec 30 2008
Journal Name
Al-kindy College Medical Journal
Chest Radiographic Finding in Neonatal Dyspnea
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Background: Respiratory distress is one of the
commonest disorders within the firs 48 - 72 hours of live
and any sign of postnatal respiratory distress is an
indication for roentgenogram of the chest.
Objectives: Is to show the range of chest radiographic
findings in full term newborn babies suffering from
respiratory distress, at or soon after birth.
Method: This is a prospective study that was conducted
in the special care baby units in Baghdad teaching
hospital and Children welfare teaching hospital during
2002. Anteroposterior chest radiograph in supine
position of (129) full term newborn babies, presented
with a chief complaint of respiratory distress were
examined.
Results: The commonest ca

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Publication Date
Thu May 01 2025
Journal Name
2025 3rd International Conference On Business Analytics For Technology And Security (icbats)
Comparison of Deep Neural Network Models (LSTM, Bi-LSTM, GRU and Bi-GRU) for Gold Price Prediction
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This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff

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Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Thu Sep 28 2023
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Distinct Architectures of Feed Forward Neural Network for Implementing A Human Swing Leg System
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The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Under that paper, we think the fuzzy controller plan issue for yield following flawed genuine investigation of nonlinear systems. For examination, an essential fuzzy control plot has been bristly developed dependent on a current methodology delegate under the field. In this paper, the Feedforward Neural Network has been implemented with integer, fixed point and floating point data representations. Additionally, The Fuzzy Logic Controllers in both analog and digital forms has been implemented in hardware. Both designs use les

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Publication Date
Sat Sep 30 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Performance Auditing Of Hotels Sector Under (Covid-19) And It’s Reflection On The Outcome Of Activity
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Abstract:

              The hotel sector is one of the most vital sectors exposed to risks, and the authorities concerned with control must take their active and influential role in putting the hotel sector on the right track and compatible with the internationally approved approaches, and the importance of auditing the performance of the hotel sector in light of the (Covid-19) pandemic is embodied in the fact that it gives a clear and realistic picture to the management and regulatory bodies about the performance and activities of this sector and the shortcomings and deviations that must be addressed, and also helps government decision makers to ob

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Publication Date
Wed Mar 09 2022
Journal Name
American Journal Of Orthopsychiatry
Intersected Discrimination Through the Lens of COVID-19: The Case Example of Christian Minority in Iraq
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Compelling evidence proved that coronavirus disease (COVID-19) disproportionately affects minorities. The goal of the present study was to explore the effects of intersected discrimination and discrimination types on COVID-19, mental health, and cognition. A sample of 542 Iraqis, 55.7% females, age ranged from 18 to 73, with (M = 31.16, SD = 9.77). 48.7% were Muslims, and 51.3% were Christians (N = 278). We used measures for COVID-19 stressors, executive functions, intersected discrimination (gender discrimination, social groups-based discrimination, sexual orientation discrimination, and genocidal discrimination), posttraumatic stress disorder (PTSD), depression, anxiety, status and death, existential anxieties, and health. We conducted in

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Publication Date
Wed Jan 01 2025
Journal Name
Science Progress
Impact of COVID-19 on the prevalence of oral and maxillofacial disorders: A retrospective cohort study
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Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
Health Anxiety Related to Coronavirus (Covid 19) and Its Relationship to Health Behavior among Baghdad University Employees
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The aim of the research is to identify the relationship between health anxiety associated with Coronavirus (Covid 19) and its relationship to health behavior among Baghdad University employees, as well as to identify the differences in health anxiety and health behavior according to the variables (gender, occupation, and age). To achieve the objectives of the research, a scale was designed to measure the health anxiety in addition to the adoption of the health behavior scale prepared by (Renner & Schwarzer, 2005). The two scales were applied to a sample of (277) academics and (206) employees, while the number of students was (667). The sample was chosen by electronic application from a number of colleges at Al-Jadiriyah Complex. Afte

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Publication Date
Tue Jul 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Classification and monitoring of autism using svm and vmcm
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Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

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