This research aims to investigate the approaches adopted by Iraqi newspapers in addressing the COVID-19 pandemic crisis. Employing a descriptive methodology and survey technique, the study conducts content analysis on articles published in three prominent newspapers: Al-Sabah, Al-Mada, and Tareeq Al-Shaab. A multi-stage sampling method was employed, encompassing 260 issues of the aforementioned newspapers. Data collection involved the use of a content analysis questionnaire, with the "How it was said?" method utilized to determine analysis categories.
The results showed that Al-Sabah newspaper adopted a positive approach in addressing COVID-19-related topics, while Al-Mada newspaper remained neutral, and Tare

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

In light of the increasing interest in Child-rearing in nurseries and kindergartens and the most important experiences gained by the child at this stage that form the basis for the subsequent stages of her/his physical mental and social growth.

The significance of the research concentrates the need to asses the affecting variables on the child growth to create opportunities for her/him to have intact rearing.

The research also aims to classify these variables at each age level and highlight its moral role.

The problem of the research is the lack of clarity of different variables impact of the child growth in different age levels in nurseries and kindergart

Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colo

order to increase the level of security, as this system encrypts the secret image before sending it through the internet to the recipient (by the Blowfish method). As The Blowfish method is known for its efficient security; nevertheless, the encrypting time is long. In this research we try to apply the smoothing filter on the secret image which decreases its size and consequently the encrypting and decrypting time are decreased. The secret image is hidden after encrypting it into another image called the cover image, by the use of one of these two methods" Two-LSB" or" Hiding most bits in blue pixels". Eventually we compare the results of the two methods to determine which one is better to be used according to the PSNR measurs

The current research aimed to identify the tasks performed by the internal auditors when developing a business continuity plan to face the COVID-19 crisis. It also aims to identify the recovery and resuming plan to the business environment. The research followed the descriptive survey to find out the views of 34 internal auditors at various functional levels in the Kingdom of Saudi Arabia. Spreadsheets (Excel) were used to analyze the data collected by a questionnaire which composed of 43 statements, covering the tasks that the internal auditors can perform to face the COVID-19 crisis. Results revealed that the tasks performed by the internal auditors when developing a business continuity plan to face the COVID-19 crisis is to en