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 ensure that the plan meets the instructions issued by the government, the Ministry of Health and the World Health Organization, and they performed some tasks remotely before the crisis took place. The most apparent tasks performed by the internal auditors when implementing the business continuity work we're carrying out the tasks using some technological audit devices and recent apps to overcome new working conditions. Other tasks were performed were to participate in the provision of emergency services outside the scope of their work at the request of executive departments and to make major modifications to the risk-based internal audit plan, aiming at evaluating new activities and covering aspects of risk during the COVID-19 crisis. To recover from the COVID-19 crisis and return to the business environment, the internal auditors involved in evaluating the commitment to implement the precautionary measures and recommend following-up alternative procedures for some departments to restore business after the negative impact of organizations resources.
Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat
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Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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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.
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
Background: Coronavirus, which causes respiratory illness, has been a public health issue in recent decades. Because the clinical symptoms of infection are not always specific, it is difficult to expose all suspects to qualitative testing in order to confirm or rule out infection as a test. Methods: According to the scientific studies and investigations, seventy-three results of scientific articles and research were obtained using PubMed, Medline, Research gate and Google Scholar. The research keywords used were COVID-19, coronavirus, blood parameters, and saliva. Results: This review provides a report on the changes in the blood and saliva tests of those who are infected with the COVID-19.COVID-19 is a systemic infection that has
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As contemporary security requires the formulation of a comprehensive strategy based on multidimensional sub-strategies (economic, developmental, social, cybersecurity, military,and diplomatic dimensions to achieve so-called sustainable security and address the unconventional challenges that worsened with the turn of the twenty-first century and concerned with violent extremism, often leading to terrorism, Iraq, despite the reversal of the terrorist group ISIS in 2017, seems urgently needed to formulate effective strategies to counter violent extremism, Violent extremism has multiple internal and external reasons. These causes have increased due to local, regional, and international causes. Violent extremist factors began with the outbreak o
... Show MoreThe two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival
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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
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The Recent days witness an in creasing importanc of Islamic Banks which stems from the wide spread in Islamic and non-Islamic countries,Especially in USA and European countries.the consideration in Islamic Banks came after the financial crisis in 2008.Islamic Banks work with conventional banks in most countries,that is,the formers may face the same risks which face the latters,that represent the larger percent of the International Banking system.the problms that may affect Islamic Banks related to many causes,some related to the working in common economic environment.others related to the possibility of simulation to the method of investment and financing in conventional Banks,this mean,the work with principles not compling with
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