In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

Electronic learning was used as a substitute method for learning during the COVID-19 pandemic to conduct scientific materials and perform student assessment; this study aimed to investigate academic staff opinions toward electronic education. A cross-sectional study with a web-based questionnaire distributed to academic staff in different medical colleges in Iraq. After de-identification, data were collected and analyzed with statistical software to determine the significance between variables. A total of 256 participants were enrolled in the study: 83% were not satisfied or neutral to online learning, 80% showed a poor benefit from delivery of the practical electronic knowledge and 25% for theoretical sessions with a significant difference

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Academia Open Vol 8 No 2 (2023): December DOI: 10.21070/acopen.8.2023.8087 . Article type: (Medicine)Impact of COVID-19 on Dental Students' Psychological Health Maryam Hameed Alwan, [email protected], (1) Department of Oral Diagnosis, College of Dentistry, Baghdad University, Iraq, Iraq (1) Corresponding author Abstract This study investigates the psychological impact of the COVID-19 pandemic on dental students at Baghdad University College of Dentistry. Conducted between December 2021 and January 2022, this cross-sectional survey aligns with ethical guidelines and the Helsinki Declaration. The study utilized Cochran's equation to determine a sample size of at least 400, ensuring a 95% confidence level with a 5% margin of e

The possible effects of COVID-19 vaccines on reproductive health and male fertility in particular have been discussed intensely by the scientific community and the public since their introduction during the pandemic. On news outlets and social media platforms, many claims have been raised regarding the deleterious effects of COVID-19 vaccines on sperm quality without scientific evidence. In response to this emerging conflict, we designed this study to evaluate and assess the effect of the Pfizer-BioNTech mRNA COVID-19 vaccine on male fertility represented by the semen analysis parameters.

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

COVID-19 is a coronavirus disease caused by the severe acute respiratory syndrome. According to the World Health Organization (WHO), coronavirus-2 (SARS-CoV-2) was responsible for 87,747,940 recorded infections and 1,891,352 confirmed deaths as of January 9, 2021. Antibodies that target the Sprotein are efficient in neutralizing the virus. Methodology: 180 samples were collected from clinical sources (Blood and Nasopharyngeal swabs) and from different ages and genders at diverse hospitals in Baghdad / IRAQ between November 5, 2021, to January 20, 2022. All samples were confirmed infected with COVID-19 disease by RT-PCR technique. Haematology analysis and blood group were done for all samples, and Enzyme-Linked Immunosorbent Assay used an Ig